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|---|---|---|---|---|---|---|
case w
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.5993, u_1} C
inst✝² : Category.{?u.5997, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasLimit (F ⋙ eval C c n)
n m : ι
h : ¬ComplexShape.Rel c n m
j : J
⊢ limit.π (F ⋙ eval C c n) j ≫ (NatTrans.mk fun j => d (F.obj j) n m).app j = 0 ≫ limit.π (F ⋙ eval C c m) j
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
|
dsimp
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.55_0.gJN7GlsIU4rmUTz
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case w
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.5993, u_1} C
inst✝² : Category.{?u.5997, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasLimit (F ⋙ eval C c n)
n m : ι
h : ¬ComplexShape.Rel c n m
j : J
⊢ limit.π (F ⋙ eval C c n) j ≫ d (F.obj j) n m = 0 ≫ limit.π (F ⋙ eval C c m) j
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
|
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp]
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.55_0.gJN7GlsIU4rmUTz
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.5993, u_1} C
inst✝² : Category.{?u.5997, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasLimit (F ⋙ eval C c n)
i j : J
φ : i ⟶ j
⊢ ((Functor.const J).obj
(mk (fun n => limit (F ⋙ eval C c n)) fun n m => limMap (NatTrans.mk fun j => d (F.obj j) n m))).map
φ ≫
(fun j => Hom.mk fun n => limit.π (F ⋙ eval C c n) j) j =
(fun j => Hom.mk fun n => limit.π (F ⋙ eval C c n) j) i ≫ F.map φ
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
|
ext n
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.55_0.gJN7GlsIU4rmUTz
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.5993, u_1} C
inst✝² : Category.{?u.5997, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasLimit (F ⋙ eval C c n)
i j : J
φ : i ⟶ j
n : ι
⊢ Hom.f
(((Functor.const J).obj
(mk (fun n => limit (F ⋙ eval C c n)) fun n m => limMap (NatTrans.mk fun j => d (F.obj j) n m))).map
φ ≫
(fun j => Hom.mk fun n => limit.π (F ⋙ eval C c n) j) j)
n =
Hom.f ((fun j => Hom.mk fun n => limit.π (F ⋙ eval C c n) j) i ≫ F.map φ) n
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
|
dsimp
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.55_0.gJN7GlsIU4rmUTz
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.5993, u_1} C
inst✝² : Category.{?u.5997, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasLimit (F ⋙ eval C c n)
i j : J
φ : i ⟶ j
n : ι
⊢ 𝟙 (limit (F ⋙ eval C c n)) ≫ limit.π (F ⋙ eval C c n) j = limit.π (F ⋙ eval C c n) i ≫ Hom.f (F.map φ) n
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
|
erw [limit.w, id_comp]
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.55_0.gJN7GlsIU4rmUTz
|
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝⁴ : Category.{?u.35711, u_1} C
inst✝³ : Category.{?u.35715, u_3} J
c : ComplexShape ι
inst✝² : HasZeroMorphisms C
inst✝¹ : HasFiniteLimits C
K L : HomologicalComplex C c
φ : K ⟶ L
inst✝ : Mono φ
n : ι
⊢ Mono (Hom.f φ n)
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
|
change Mono ((HomologicalComplex.eval C c n).map φ)
|
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.96_0.gJN7GlsIU4rmUTz
|
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n)
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝⁴ : Category.{?u.35711, u_1} C
inst✝³ : Category.{?u.35715, u_3} J
c : ComplexShape ι
inst✝² : HasZeroMorphisms C
inst✝¹ : HasFiniteLimits C
K L : HomologicalComplex C c
φ : K ⟶ L
inst✝ : Mono φ
n : ι
⊢ Mono ((eval C c n).map φ)
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
|
infer_instance
|
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.96_0.gJN7GlsIU4rmUTz
|
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n)
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
i i' : ι
x✝ : ComplexShape.Rel c i i'
⊢ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i ≫ d t.pt i i' =
d s.pt i i' ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i'
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
|
apply IsColimit.hom_ext (hs i)
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
i i' : ι
x✝ : ComplexShape.Rel c i i'
⊢ ∀ (j : J),
((eval C c i).mapCocone s).ι.app j ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i ≫ d t.pt i i' =
((eval C c i).mapCocone s).ι.app j ≫ d s.pt i i' ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i'
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
|
intro j
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
i i' : ι
x✝ : ComplexShape.Rel c i i'
j : J
⊢ ((eval C c i).mapCocone s).ι.app j ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i ≫ d t.pt i i' =
((eval C c i).mapCocone s).ι.app j ≫ d s.pt i i' ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i'
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
|
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
i i' : ι
x✝ : ComplexShape.Rel c i i'
j : J
eq :
∀ (k : ι) (j : J),
((eval C c k).mapCocone s).ι.app j ≫ IsColimit.desc (hs k) ((eval C c k).mapCocone t) =
((eval C c k).mapCocone t).ι.app j
⊢ ((eval C c i).mapCocone s).ι.app j ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i ≫ d t.pt i i' =
((eval C c i).mapCocone s).ι.app j ≫ d s.pt i i' ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i'
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
|
simp only [Functor.mapCocone_ι_app, eval_map] at eq
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
i i' : ι
x✝ : ComplexShape.Rel c i i'
j : J
eq : ∀ (k : ι) (j : J), Hom.f (s.ι.app j) k ≫ IsColimit.desc (hs k) ((eval C c k).mapCocone t) = Hom.f (t.ι.app j) k
⊢ ((eval C c i).mapCocone s).ι.app j ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i ≫ d t.pt i i' =
((eval C c i).mapCocone s).ι.app j ≫ d s.pt i i' ≫ (fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) i'
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
|
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
i i' : ι
x✝ : ComplexShape.Rel c i i'
j : J
eq : ∀ (k : ι) (j : J), Hom.f (s.ι.app j) k ≫ IsColimit.desc (hs k) ((eval C c k).mapCocone t) = Hom.f (t.ι.app j) k
⊢ Hom.f (s.ι.app j) i ≫ IsColimit.desc (hs i) ((eval C c i).mapCocone t) ≫ d t.pt i i' =
Hom.f (s.ι.app j) i ≫ d s.pt i i' ≫ IsColimit.desc (hs i') ((eval C c i').mapCocone t)
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
|
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm]
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
j : J
⊢ s.ι.app j ≫ (fun t => Hom.mk fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) t = t.ι.app j
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
|
ext i
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
j : J
i : ι
⊢ Hom.f (s.ι.app j ≫ (fun t => Hom.mk fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) t) i =
Hom.f (t.ι.app j) i
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
|
apply (hs i).fac
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
m : s.pt ⟶ t.pt
hm : ∀ (j : J), s.ι.app j ≫ m = t.ι.app j
⊢ m = (fun t => Hom.mk fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) t
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
|
ext i
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
m : s.pt ⟶ t.pt
hm : ∀ (j : J), s.ι.app j ≫ m = t.ι.app j
i : ι
⊢ Hom.f m i = Hom.f ((fun t => Hom.mk fun i => IsColimit.desc (hs i) ((eval C c i).mapCocone t)) t) i
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
|
apply (hs i).uniq ((eval C c i).mapCocone t)
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h.x
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
m : s.pt ⟶ t.pt
hm : ∀ (j : J), s.ι.app j ≫ m = t.ι.app j
i : ι
⊢ ∀ (j : J), ((eval C c i).mapCocone s).ι.app j ≫ Hom.f m i = ((eval C c i).mapCocone t).ι.app j
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
|
intro j
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h.x
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
m : s.pt ⟶ t.pt
hm : ∀ (j : J), s.ι.app j ≫ m = t.ι.app j
i : ι
j : J
⊢ ((eval C c i).mapCocone s).ι.app j ≫ Hom.f m i = ((eval C c i).mapCocone t).ι.app j
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
|
dsimp
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h.x
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝² : Category.{?u.39790, u_1} C
inst✝¹ : Category.{?u.39794, u_3} J
c : ComplexShape ι
inst✝ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
s : Cocone F
hs : (i : ι) → IsColimit ((eval C c i).mapCocone s)
t : Cocone F
m : s.pt ⟶ t.pt
hm : ∀ (j : J), s.ι.app j ≫ m = t.ι.app j
i : ι
j : J
⊢ Hom.f (s.ι.app j) i ≫ Hom.f m i = Hom.f (t.ι.app j) i
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
|
simp only [← comp_f, hm]
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.105_0.gJN7GlsIU4rmUTz
|
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.45485, u_1} C
inst✝² : Category.{?u.45489, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasColimit (F ⋙ eval C c n)
n m : ι
h : ¬ComplexShape.Rel c n m
⊢ (fun n m => colimMap (NatTrans.mk fun j => d (F.obj j) n m)) n m = 0
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
|
ext j
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.131_0.gJN7GlsIU4rmUTz
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case w
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.45485, u_1} C
inst✝² : Category.{?u.45489, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasColimit (F ⋙ eval C c n)
n m : ι
h : ¬ComplexShape.Rel c n m
j : J
⊢ colimit.ι (F ⋙ eval C c n) j ≫ (fun n m => colimMap (NatTrans.mk fun j => d (F.obj j) n m)) n m =
colimit.ι (F ⋙ eval C c n) j ≫ 0
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
|
rw [ι_colimMap]
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.131_0.gJN7GlsIU4rmUTz
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case w
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.45485, u_1} C
inst✝² : Category.{?u.45489, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasColimit (F ⋙ eval C c n)
n m : ι
h : ¬ComplexShape.Rel c n m
j : J
⊢ (NatTrans.mk fun j => d (F.obj j) n m).app j ≫ colimit.ι (F ⋙ eval C c m) j = colimit.ι (F ⋙ eval C c n) j ≫ 0
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
|
dsimp
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.131_0.gJN7GlsIU4rmUTz
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case w
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.45485, u_1} C
inst✝² : Category.{?u.45489, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasColimit (F ⋙ eval C c n)
n m : ι
h : ¬ComplexShape.Rel c n m
j : J
⊢ d (F.obj j) n m ≫ colimit.ι (F ⋙ eval C c m) j = colimit.ι (F ⋙ eval C c n) j ≫ 0
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
|
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero]
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.131_0.gJN7GlsIU4rmUTz
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.45485, u_1} C
inst✝² : Category.{?u.45489, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasColimit (F ⋙ eval C c n)
i j : J
φ : i ⟶ j
⊢ F.map φ ≫ (fun j => Hom.mk fun n => colimit.ι (F ⋙ eval C c n) j) j =
(fun j => Hom.mk fun n => colimit.ι (F ⋙ eval C c n) j) i ≫
((Functor.const J).obj
(mk (fun n => colimit (F ⋙ eval C c n)) fun n m => colimMap (NatTrans.mk fun j => d (F.obj j) n m))).map
φ
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
|
ext n
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.131_0.gJN7GlsIU4rmUTz
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.45485, u_1} C
inst✝² : Category.{?u.45489, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasColimit (F ⋙ eval C c n)
i j : J
φ : i ⟶ j
n : ι
⊢ Hom.f (F.map φ ≫ (fun j => Hom.mk fun n => colimit.ι (F ⋙ eval C c n) j) j) n =
Hom.f
((fun j => Hom.mk fun n => colimit.ι (F ⋙ eval C c n) j) i ≫
((Functor.const J).obj
(mk (fun n => colimit (F ⋙ eval C c n)) fun n m => colimMap (NatTrans.mk fun j => d (F.obj j) n m))).map
φ)
n
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
ext n
|
dsimp
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
ext n
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.131_0.gJN7GlsIU4rmUTz
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
case h
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝³ : Category.{?u.45485, u_1} C
inst✝² : Category.{?u.45489, u_3} J
c : ComplexShape ι
inst✝¹ : HasZeroMorphisms C
F : J ⥤ HomologicalComplex C c
inst✝ : ∀ (n : ι), HasColimit (F ⋙ eval C c n)
i j : J
φ : i ⟶ j
n : ι
⊢ Hom.f (F.map φ) n ≫ colimit.ι (F ⋙ eval C c n) j = colimit.ι (F ⋙ eval C c n) i ≫ 𝟙 (colimit (F ⋙ eval C c n))
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
ext n
dsimp
|
erw [colimit.w (F ⋙ eval C c n) φ, comp_id]
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
ext n
dsimp
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.131_0.gJN7GlsIU4rmUTz
|
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝⁴ : Category.{?u.75003, u_1} C
inst✝³ : Category.{?u.75007, u_3} J
c : ComplexShape ι
inst✝² : HasZeroMorphisms C
inst✝¹ : HasFiniteColimits C
K L : HomologicalComplex C c
φ : K ⟶ L
inst✝ : Epi φ
n : ι
⊢ Epi (Hom.f φ n)
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
ext n
dsimp
erw [colimit.w (F ⋙ eval C c n) φ, comp_id] }
/-- The cocone `coconeOfHasLimitEval F` is colimit. -/
noncomputable def isColimitCoconeOfHasColimitEval : IsColimit (coconeOfHasColimitEval F) :=
isColimitOfEval _ _ (fun _ => colimit.isColimit _)
instance : HasColimit F := ⟨⟨⟨_, isColimitCoconeOfHasColimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesColimit F (eval C c n) :=
preservesColimitOfPreservesColimitCocone (isColimitCoconeOfHasColimitEval F)
(colimit.isColimit _)
end
instance [HasColimitsOfShape J C] : HasColimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasColimitsOfShape J C] (n : ι) :
PreservesColimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteColimits C] : HasFiniteColimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteColimits C] (n : ι) :
PreservesFiniteColimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteColimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Epi φ] (n : ι) :
Epi (φ.f n) := by
|
change Epi ((HomologicalComplex.eval C c n).map φ)
|
instance [HasFiniteColimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Epi φ] (n : ι) :
Epi (φ.f n) := by
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.173_0.gJN7GlsIU4rmUTz
|
instance [HasFiniteColimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Epi φ] (n : ι) :
Epi (φ.f n)
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
C : Type u_1
ι : Type u_2
J : Type u_3
inst✝⁴ : Category.{?u.75003, u_1} C
inst✝³ : Category.{?u.75007, u_3} J
c : ComplexShape ι
inst✝² : HasZeroMorphisms C
inst✝¹ : HasFiniteColimits C
K L : HomologicalComplex C c
φ : K ⟶ L
inst✝ : Epi φ
n : ι
⊢ Epi ((eval C c n).map φ)
|
/-
Copyright (c) 2023 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.Algebra.Homology.HomologicalComplex
import Mathlib.CategoryTheory.Limits.Shapes.FiniteLimits
import Mathlib.CategoryTheory.Limits.Preserves.Finite
/-!
# Limits and colimits in the category of homological complexes
In this file, it is shown that if a category `C` has (co)limits of shape `J`,
then it is also the case of the categories `HomologicalComplex C c`,
and the evaluation functors `eval C c i : HomologicalComplex C c ⥤ C`
commute to these.
-/
open CategoryTheory Category Limits
namespace HomologicalComplex
variable {C ι J : Type*} [Category C] [Category J] {c : ComplexShape ι} [HasZeroMorphisms C]
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cone in `HomologicalComplex C c` is limit if the induced cones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are limit. -/
def isLimitOfEval (s : Cone F)
(hs : ∀ (i : ι), IsLimit ((eval C c i).mapCone s)) : IsLimit s where
lift t :=
{ f := fun i => (hs i).lift ((eval C c i).mapCone t)
comm' := fun i i' _ => by
apply IsLimit.hom_ext (hs i')
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCone t)
simp only [Functor.mapCone_π_app, eval_map] at eq
simp only [Functor.mapCone_π_app, eval_map, assoc]
rw [eq i', ← Hom.comm, reassoc_of% (eq i), Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasLimit (F ⋙ eval C c n)]
/-- A cone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the limit `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coneOfHasLimitEval : Cone F where
pt :=
{ X := fun n => limit (F ⋙ eval C c n)
d := fun n m => limMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [limMap_π]
dsimp
rw [(F.obj j).shape _ _ h, comp_zero, zero_comp] }
π :=
{ app := fun j => { f := fun n => limit.π _ j }
naturality := fun i j φ => by
ext n
dsimp
erw [limit.w, id_comp] }
/-- The cone `coneOfHasLimitEval F` is limit. -/
noncomputable def isLimitConeOfHasLimitEval : IsLimit (coneOfHasLimitEval F) :=
isLimitOfEval _ _ (fun _ => limit.isLimit _)
instance : HasLimit F := ⟨⟨⟨_, isLimitConeOfHasLimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesLimit F (eval C c n) :=
preservesLimitOfPreservesLimitCone (isLimitConeOfHasLimitEval F) (limit.isLimit _)
end
instance [HasLimitsOfShape J C] : HasLimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasLimitsOfShape J C] (n : ι) :
PreservesLimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteLimits C] : HasFiniteLimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteLimits C] (n : ι) :
PreservesFiniteLimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteLimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Mono φ] (n : ι) :
Mono (φ.f n) := by
change Mono ((HomologicalComplex.eval C c n).map φ)
infer_instance
section
variable (F : J ⥤ HomologicalComplex C c)
/-- A cocone in `HomologicalComplex C c` is colimit if the induced cocones obtained
by applying `eval C c i : HomologicalComplex C c ⥤ C` for all `i` are colimit. -/
def isColimitOfEval (s : Cocone F)
(hs : ∀ (i : ι), IsColimit ((eval C c i).mapCocone s)) : IsColimit s where
desc t :=
{ f := fun i => (hs i).desc ((eval C c i).mapCocone t)
comm' := fun i i' _ => by
apply IsColimit.hom_ext (hs i)
intro j
have eq := fun k => (hs k).fac ((eval C c k).mapCocone t)
simp only [Functor.mapCocone_ι_app, eval_map] at eq
simp only [Functor.mapCocone_ι_app, eval_map, assoc]
rw [reassoc_of% (eq i), Hom.comm_assoc, eq i', Hom.comm] }
fac t j := by
ext i
apply (hs i).fac
uniq t m hm := by
ext i
apply (hs i).uniq ((eval C c i).mapCocone t)
intro j
dsimp
simp only [← comp_f, hm]
variable [∀ (n : ι), HasColimit (F ⋙ HomologicalComplex.eval C c n)]
/-- A cocone for a functor `F : J ⥤ HomologicalComplex C c` which is given in degree `n` by
the colimit of `F ⋙ eval C c n`. -/
@[simps]
noncomputable def coconeOfHasColimitEval : Cocone F where
pt :=
{ X := fun n => colimit (F ⋙ eval C c n)
d := fun n m => colimMap { app := fun j => (F.obj j).d n m }
shape := fun {n m} h => by
ext j
rw [ι_colimMap]
dsimp
rw [(F.obj j).shape _ _ h, zero_comp, comp_zero] }
ι :=
{ app := fun j => { f := fun n => colimit.ι (F ⋙ eval C c n) j }
naturality := fun i j φ => by
ext n
dsimp
erw [colimit.w (F ⋙ eval C c n) φ, comp_id] }
/-- The cocone `coconeOfHasLimitEval F` is colimit. -/
noncomputable def isColimitCoconeOfHasColimitEval : IsColimit (coconeOfHasColimitEval F) :=
isColimitOfEval _ _ (fun _ => colimit.isColimit _)
instance : HasColimit F := ⟨⟨⟨_, isColimitCoconeOfHasColimitEval F⟩⟩⟩
noncomputable instance (n : ι) : PreservesColimit F (eval C c n) :=
preservesColimitOfPreservesColimitCocone (isColimitCoconeOfHasColimitEval F)
(colimit.isColimit _)
end
instance [HasColimitsOfShape J C] : HasColimitsOfShape J (HomologicalComplex C c) := ⟨inferInstance⟩
noncomputable instance [HasColimitsOfShape J C] (n : ι) :
PreservesColimitsOfShape J (eval C c n) := ⟨inferInstance⟩
instance [HasFiniteColimits C] : HasFiniteColimits (HomologicalComplex C c) :=
⟨fun _ _ => inferInstance⟩
noncomputable instance [HasFiniteColimits C] (n : ι) :
PreservesFiniteColimits (eval C c n) := ⟨fun _ _ _ => inferInstance⟩
instance [HasFiniteColimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Epi φ] (n : ι) :
Epi (φ.f n) := by
change Epi ((HomologicalComplex.eval C c n).map φ)
|
infer_instance
|
instance [HasFiniteColimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Epi φ] (n : ι) :
Epi (φ.f n) := by
change Epi ((HomologicalComplex.eval C c n).map φ)
|
Mathlib.Algebra.Homology.HomologicalComplexLimits.173_0.gJN7GlsIU4rmUTz
|
instance [HasFiniteColimits C] {K L : HomologicalComplex C c} (φ : K ⟶ L) [Epi φ] (n : ι) :
Epi (φ.f n)
|
Mathlib_Algebra_Homology_HomologicalComplexLimits
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝¹⁰ : Ring 𝕜
inst✝⁹ : AddCommGroup E
inst✝⁸ : AddCommGroup F
inst✝⁷ : Module 𝕜 E
inst✝⁶ : Module 𝕜 F
inst✝⁵ : TopologicalSpace E
inst✝⁴ : TopologicalSpace F
inst✝³ : TopologicalAddGroup E
inst✝² : TopologicalAddGroup F
inst✝¹ : ContinuousConstSMul 𝕜 E
inst✝ : ContinuousConstSMul 𝕜 F
p : FormalMultilinearSeries 𝕜 E F
n : ℕ
⊢ Continuous (partialSum p n)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
|
unfold partialSum
|
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
|
Mathlib.Analysis.Analytic.Basic.103_0.jQw1fRSE1vGpOll
|
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝¹⁰ : Ring 𝕜
inst✝⁹ : AddCommGroup E
inst✝⁸ : AddCommGroup F
inst✝⁷ : Module 𝕜 E
inst✝⁶ : Module 𝕜 F
inst✝⁵ : TopologicalSpace E
inst✝⁴ : TopologicalSpace F
inst✝³ : TopologicalAddGroup E
inst✝² : TopologicalAddGroup F
inst✝¹ : ContinuousConstSMul 𝕜 E
inst✝ : ContinuousConstSMul 𝕜 F
p : FormalMultilinearSeries 𝕜 E F
n : ℕ
⊢ Continuous fun x => ∑ k in Finset.range n, (p k) fun x_1 => x
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
|
continuity
|
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
|
Mathlib.Analysis.Analytic.Basic.103_0.jQw1fRSE1vGpOll
|
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
C : ℝ
h : ∀ᶠ (n : ℕ) in atTop, ‖p n‖ * ↑r ^ n ≤ C
n : ℕ
hn : ‖p n‖ * ↑r ^ n ≤ C
⊢ ‖‖p n‖ * ↑r ^ n‖ ≤ C * ‖1‖
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by
|
simpa
|
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by
|
Mathlib.Analysis.Analytic.Basic.148_0.jQw1fRSE1vGpOll
|
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : Summable fun n => ‖p n‖ * ↑r ^ n
⊢ Summable fun n => ‖p n‖₊ * r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
|
simp only [← coe_nnnorm] at h
|
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
|
Mathlib.Analysis.Analytic.Basic.157_0.jQw1fRSE1vGpOll
|
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : Summable fun n => ↑‖p n‖₊ * ↑r ^ n
⊢ Summable fun n => ‖p n‖₊ * r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
|
exact mod_cast h
|
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
|
Mathlib.Analysis.Analytic.Basic.157_0.jQw1fRSE1vGpOll
|
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
h : ∀ᶠ (n : ℕ) in atTop, p n = 0
r : ℝ≥0
n : ℕ
hn : p n = 0
⊢ (fun _x => 0) n = (fun n => ‖p n‖ * ↑r ^ n) n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by
|
simp [hn]
|
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by
|
Mathlib.Analysis.Analytic.Basic.169_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
v : F
⊢ ∀ (m : ℕ), constFormalMultilinearSeries 𝕜 E v (m + 1) = 0
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by
|
simp [constFormalMultilinearSeries]
|
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by
|
Mathlib.Analysis.Analytic.Basic.180_0.jQw1fRSE1vGpOll
|
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
⊢ ∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
|
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
this :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
⊢ ∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
|
rw [this]
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
this :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
⊢ ∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
|
simp only [radius, lt_iSup_iff] at h
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
h : ∃ i i_1, ∃ (_ : ∀ (n : ℕ), ‖p n‖ * ↑i ^ n ≤ i_1), ↑r < ↑i
⊢ ∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
|
rcases h with ⟨t, C, hC, rt⟩
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r < ↑t
⊢ ∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
|
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r < ↑t
⊢ ∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
|
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this✝ :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r < ↑t
this : 0 < ↑t
⊢ ∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
|
rw [← div_lt_one this] at rt
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this✝ :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r / ↑t < 1
this : 0 < ↑t
⊢ ∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
|
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this✝ :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r / ↑t < 1
this : 0 < ↑t
n : ℕ
⊢ |‖p n‖ * ↑r ^ n| ≤ C * (↑r / ↑t) ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
|
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this✝ :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r / ↑t < 1
this : 0 < ↑t
n : ℕ
⊢ |‖p n‖ * ↑r ^ n| = ‖p n‖ * ↑t ^ n * (↑r / ↑t) ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
|
field_simp [mul_right_comm, abs_mul]
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this✝ :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r / ↑t < 1
this : 0 < ↑t
n : ℕ
⊢ ‖p n‖ * ↑t ^ n * (↑r / ↑t) ^ n ≤ C * (↑r / ↑t) ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by
|
gcongr
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
case h
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
this✝ :
(∃ a ∈ Ioo 0 1, (fun n => ‖p n‖ * ↑r ^ n) =o[atTop] fun x => a ^ x) ↔
∃ a < 1, ∃ C, (0 < C ∨ 0 < 1) ∧ ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
t : ℝ≥0
C : ℝ
hC : ∀ (n : ℕ), ‖p n‖ * ↑t ^ n ≤ C
rt : ↑r / ↑t < 1
this : 0 < ↑t
n : ℕ
⊢ ‖p n‖ * ↑t ^ n ≤ C
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr;
|
apply hC
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr;
|
Mathlib.Analysis.Analytic.Basic.187_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·)
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
⊢ ∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), ‖p n‖ * ↑r ^ n ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
|
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
|
Mathlib.Analysis.Analytic.Basic.214_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
this : ∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
⊢ ∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), ‖p n‖ * ↑r ^ n ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
|
rcases this with ⟨a, ha, C, hC, H⟩
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
|
Mathlib.Analysis.Analytic.Basic.214_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
a : ℝ
ha : a ∈ Ioo 0 1
C : ℝ
hC : C > 0
H : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
⊢ ∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), ‖p n‖ * ↑r ^ n ≤ C * a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
|
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
|
Mathlib.Analysis.Analytic.Basic.214_0.jQw1fRSE1vGpOll
|
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : r ≠ 0
a : ℝ
ha : a ∈ Ioo (-1) 1
hp : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
|
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : r ≠ 0
a : ℝ
ha : a ∈ Ioo (-1) 1
hp : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x
this :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
|
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : r ≠ 0
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
a : ℝ
ha : a ∈ Ioo 0 1
C : ℝ
hC : C > 0
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
|
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
a : ℝ
ha : a ∈ Ioo 0 1
C : ℝ
hC : C > 0
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
|
lift a to ℝ≥0 using ha.1.le
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
C : ℝ
hC : C > 0
a : ℝ≥0
ha : ↑a ∈ Ioo 0 1
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * ↑a ^ n
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
|
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
C : ℝ
hC : C > 0
a : ℝ≥0
ha : ↑a ∈ Ioo 0 1
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * ↑a ^ n
⊢ ↑r < ↑r / ↑a
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
|
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this✝ :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
C : ℝ
hC : C > 0
a : ℝ≥0
ha : ↑a ∈ Ioo 0 1
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * ↑a ^ n
this : ↑r < ↑r / ↑a
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
|
norm_cast at this
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this✝ :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
C : ℝ
hC : C > 0
a : ℝ≥0
ha : ↑a ∈ Ioo 0 1
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * ↑a ^ n
this : r < r / a
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
|
rw [← ENNReal.coe_lt_coe] at this
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this✝ :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
C : ℝ
hC : C > 0
a : ℝ≥0
ha : ↑a ∈ Ioo 0 1
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * ↑a ^ n
this : ↑r < ↑(r / a)
⊢ ↑r < radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
|
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this✝ :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
C : ℝ
hC : C > 0
a : ℝ≥0
ha : ↑a ∈ Ioo 0 1
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * ↑a ^ n
this : ↑r < ↑(r / a)
n : ℕ
⊢ ‖p n‖ * ↑(r / a) ^ n ≤ C
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
|
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h₀ : 0 < ↑r
a✝ : ℝ
ha✝ : a✝ ∈ Ioo (-1) 1
hp✝ : (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a✝ ^ x
this✝ :
(∃ a ∈ Ioo (-1) 1, (fun n => ‖p n‖ * ↑r ^ n) =O[atTop] fun x => a ^ x) ↔
∃ a ∈ Ioo 0 1, ∃ C > 0, ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * a ^ n
C : ℝ
hC : C > 0
a : ℝ≥0
ha : ↑a ∈ Ioo 0 1
hp : ∀ (n : ℕ), |‖p n‖ * ↑r ^ n| ≤ C * ↑a ^ n
this : ↑r < ↑(r / a)
n : ℕ
⊢ ‖p n‖ * ↑r ^ n ≤ C * ↑a ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
|
exact (le_abs_self _).trans (hp n)
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
|
Mathlib.Analysis.Analytic.Basic.225_0.jQw1fRSE1vGpOll
|
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
⊢ Summable fun n => ‖p n‖ * ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
|
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
|
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
|
Mathlib.Analysis.Analytic.Basic.279_0.jQw1fRSE1vGpOll
|
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
a : ℝ
ha : a ∈ Ioo 0 1
C : ℝ
hp : ∀ (n : ℕ), ‖p n‖ * ↑r ^ n ≤ C * a ^ n
⊢ Summable fun n => ‖p n‖ * ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
|
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
|
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
|
Mathlib.Analysis.Analytic.Basic.279_0.jQw1fRSE1vGpOll
|
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
x : E
hx : x ∈ EMetric.ball 0 (radius p)
⊢ Summable fun n => ‖(p n) fun x_1 => x‖
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
|
rw [mem_emetric_ball_zero_iff] at hx
|
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
|
Mathlib.Analysis.Analytic.Basic.286_0.jQw1fRSE1vGpOll
|
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
x : E
hx : ↑‖x‖₊ < radius p
⊢ Summable fun n => ‖(p n) fun x_1 => x‖
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
|
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
|
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
|
Mathlib.Analysis.Analytic.Basic.286_0.jQw1fRSE1vGpOll
|
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
x : E
hx : ↑‖x‖₊ < radius p
n : ℕ
⊢ ‖p n‖ * ∏ i : Fin n, ‖x‖ = ‖p n‖ * ↑‖x‖₊ ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
|
simp
|
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
|
Mathlib.Analysis.Analytic.Basic.286_0.jQw1fRSE1vGpOll
|
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
⊢ Summable fun n => ‖p n‖₊ * r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
|
rw [← NNReal.summable_coe]
|
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
|
Mathlib.Analysis.Analytic.Basic.294_0.jQw1fRSE1vGpOll
|
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
⊢ Summable fun a => ↑(‖p a‖₊ * r ^ a)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
|
push_cast
|
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
|
Mathlib.Analysis.Analytic.Basic.294_0.jQw1fRSE1vGpOll
|
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
h : ↑r < radius p
⊢ Summable fun a => ‖p a‖ * ↑r ^ a
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
|
exact p.summable_norm_mul_pow h
|
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
|
Mathlib.Analysis.Analytic.Basic.294_0.jQw1fRSE1vGpOll
|
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
⊢ radius p = ⊤ ↔ ∀ (r : ℝ≥0), Summable fun n => ‖p n‖ * ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
|
constructor
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
|
Mathlib.Analysis.Analytic.Basic.311_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case mp
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
⊢ radius p = ⊤ → ∀ (r : ℝ≥0), Summable fun n => ‖p n‖ * ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
·
|
intro h r
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
·
|
Mathlib.Analysis.Analytic.Basic.311_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case mp
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : radius p = ⊤
r : ℝ≥0
⊢ Summable fun n => ‖p n‖ * ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
|
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
|
Mathlib.Analysis.Analytic.Basic.311_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case mp.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : radius p = ⊤
r : ℝ≥0
a : ℝ
ha : a ∈ Ioo 0 1
C : ℝ
hp : ∀ (n : ℕ), ‖p n‖ * ↑r ^ n ≤ C * a ^ n
⊢ Summable fun n => ‖p n‖ * ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
|
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
|
Mathlib.Analysis.Analytic.Basic.311_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case mp.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : radius p = ⊤
r : ℝ≥0
a : ℝ
ha : a ∈ Ioo 0 1
C : ℝ
hp : ∀ (n : ℕ), ‖p n‖ * ↑r ^ n ≤ C * a ^ n
n : ℕ
⊢ ‖‖p n‖ * ↑r ^ n‖ ≤ (fun n => C * a ^ n) n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
|
specialize hp n
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
|
Mathlib.Analysis.Analytic.Basic.311_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case mp.intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : radius p = ⊤
r : ℝ≥0
a : ℝ
ha : a ∈ Ioo 0 1
C : ℝ
n : ℕ
hp : ‖p n‖ * ↑r ^ n ≤ C * a ^ n
⊢ ‖‖p n‖ * ↑r ^ n‖ ≤ (fun n => C * a ^ n) n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
|
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
|
Mathlib.Analysis.Analytic.Basic.311_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case mpr
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
⊢ (∀ (r : ℝ≥0), Summable fun n => ‖p n‖ * ↑r ^ n) → radius p = ⊤
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
·
|
exact p.radius_eq_top_of_summable_norm
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
·
|
Mathlib.Analysis.Analytic.Basic.311_0.jQw1fRSE1vGpOll
|
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
⊢ ∃ C r, ∃ (_ : 0 < C) (_ : 0 < r), ∀ (n : ℕ), ‖p n‖ ≤ C * r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
|
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
r : ℝ≥0
r0 : 0 < ↑r
rlt : ↑r < radius p
⊢ ∃ C r, ∃ (_ : 0 < C) (_ : 0 < r), ∀ (n : ℕ), ‖p n‖ ≤ C * r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
|
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
r : ℝ≥0
r0 : 0 < ↑r
rlt : ↑r < radius p
⊢ 0 < ↑r
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by
|
simp [ENNReal.coe_pos.1 r0]
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
r : ℝ≥0
r0 : 0 < ↑r
rlt : ↑r < radius p
rpos : 0 < ↑r
⊢ ∃ C r, ∃ (_ : 0 < C) (_ : 0 < r), ∀ (n : ℕ), ‖p n‖ ≤ C * r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
|
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
r : ℝ≥0
r0 : 0 < ↑r
rlt : ↑r < radius p
rpos : 0 < ↑r
C : ℝ
Cpos : C > 0
hCp : ∀ (n : ℕ), ‖p n‖ ≤ C / ↑r ^ n
⊢ ∃ C r, ∃ (_ : 0 < C) (_ : 0 < r), ∀ (n : ℕ), ‖p n‖ ≤ C * r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
|
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
r : ℝ≥0
r0 : 0 < ↑r
rlt : ↑r < radius p
rpos : 0 < ↑r
C : ℝ
Cpos : C > 0
hCp : ∀ (n : ℕ), ‖p n‖ ≤ C / ↑r ^ n
⊢ 0 < (↑r)⁻¹
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by
|
simp only [inv_pos, rpos]
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
r : ℝ≥0
r0 : 0 < ↑r
rlt : ↑r < radius p
rpos : 0 < ↑r
C : ℝ
Cpos : C > 0
hCp : ∀ (n : ℕ), ‖p n‖ ≤ C / ↑r ^ n
n : ℕ
⊢ ‖p n‖ ≤ C * (↑r)⁻¹ ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
|
rw [inv_pow, ← div_eq_mul_inv]
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
case intro.intro.intro.intro
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
h : 0 < radius p
r : ℝ≥0
r0 : 0 < ↑r
rlt : ↑r < radius p
rpos : 0 < ↑r
C : ℝ
Cpos : C > 0
hCp : ∀ (n : ℕ), ‖p n‖ ≤ C / ↑r ^ n
n : ℕ
⊢ ‖p n‖ ≤ C / ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
|
exact hCp n
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
|
Mathlib.Analysis.Analytic.Basic.324_0.jQw1fRSE1vGpOll
|
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p q : FormalMultilinearSeries 𝕜 E F
⊢ min (radius p) (radius q) ≤ radius (p + q)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
|
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
|
Mathlib.Analysis.Analytic.Basic.336_0.jQw1fRSE1vGpOll
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p q : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
hr : ↑r < min (radius p) (radius q)
⊢ ↑r ≤ radius (p + q)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
|
rw [lt_min_iff] at hr
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
|
Mathlib.Analysis.Analytic.Basic.336_0.jQw1fRSE1vGpOll
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p q : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
hr : ↑r < radius p ∧ ↑r < radius q
⊢ ↑r ≤ radius (p + q)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
|
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
|
Mathlib.Analysis.Analytic.Basic.336_0.jQw1fRSE1vGpOll
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p q : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
hr : ↑r < radius p ∧ ↑r < radius q
this : (fun x => ‖p x‖ * ↑r ^ x + ‖q x‖ * ↑r ^ x) =O[atTop] fun x => 1
⊢ ↑r ≤ radius (p + q)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
|
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
|
Mathlib.Analysis.Analytic.Basic.336_0.jQw1fRSE1vGpOll
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p q : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
hr : ↑r < radius p ∧ ↑r < radius q
this : (fun x => ‖p x‖ * ↑r ^ x + ‖q x‖ * ↑r ^ x) =O[atTop] fun x => 1
n : ℕ
⊢ ‖‖(p + q) n‖ * ↑r ^ n‖ ≤ ‖‖p n‖ * ↑r ^ n + ‖q n‖ * ↑r ^ n‖
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
|
rw [← add_mul, norm_mul, norm_mul, norm_norm]
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
|
Mathlib.Analysis.Analytic.Basic.336_0.jQw1fRSE1vGpOll
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p q : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
hr : ↑r < radius p ∧ ↑r < radius q
this : (fun x => ‖p x‖ * ↑r ^ x + ‖q x‖ * ↑r ^ x) =O[atTop] fun x => 1
n : ℕ
⊢ ‖(p + q) n‖ * ‖↑r ^ n‖ ≤ ‖‖p n‖ + ‖q n‖‖ * ‖↑r ^ n‖
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
|
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
|
Mathlib.Analysis.Analytic.Basic.336_0.jQw1fRSE1vGpOll
|
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
⊢ radius (-p) = radius p
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
|
simp only [radius, neg_apply, norm_neg]
|
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
|
Mathlib.Analysis.Analytic.Basic.347_0.jQw1fRSE1vGpOll
|
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
f : F →L[𝕜] G
⊢ radius p ≤ radius (ContinuousLinearMap.compFormalMultilinearSeries f p)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
|
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
|
Mathlib.Analysis.Analytic.Basic.357_0.jQw1fRSE1vGpOll
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
f : F →L[𝕜] G
r : ℝ≥0
hr : ↑r < radius p
⊢ ↑r ≤ radius (ContinuousLinearMap.compFormalMultilinearSeries f p)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
|
apply le_radius_of_isBigO
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
|
Mathlib.Analysis.Analytic.Basic.357_0.jQw1fRSE1vGpOll
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius
|
Mathlib_Analysis_Analytic_Basic
|
case h
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
f : F →L[𝕜] G
r : ℝ≥0
hr : ↑r < radius p
⊢ (fun n => ‖ContinuousLinearMap.compFormalMultilinearSeries f p n‖ * ↑r ^ n) =O[atTop] fun x => 1
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
|
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
|
Mathlib.Analysis.Analytic.Basic.357_0.jQw1fRSE1vGpOll
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
f : F →L[𝕜] G
r : ℝ≥0
hr : ↑r < radius p
⊢ (fun n => ‖ContinuousLinearMap.compFormalMultilinearSeries f p n‖ * ↑r ^ n) =O[atTop] fun n => ‖p n‖ * ↑r ^ n
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
|
refine' IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ _) (isBigO_refl _ _)
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
|
Mathlib.Analysis.Analytic.Basic.357_0.jQw1fRSE1vGpOll
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
f : F →L[𝕜] G
r : ℝ≥0
hr : ↑r < radius p
⊢ IsBigOWith ‖f‖ atTop (fun n => ‖ContinuousLinearMap.compFormalMultilinearSeries f p n‖) fun n => ‖p n‖
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
refine' IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ _) (isBigO_refl _ _)
|
refine IsBigOWith.of_bound (eventually_of_forall fun n => ?_)
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
refine' IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ _) (isBigO_refl _ _)
|
Mathlib.Analysis.Analytic.Basic.357_0.jQw1fRSE1vGpOll
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
p✝ : FormalMultilinearSeries 𝕜 E F
r✝ : ℝ≥0
p : FormalMultilinearSeries 𝕜 E F
f : F →L[𝕜] G
r : ℝ≥0
hr : ↑r < radius p
n : ℕ
⊢ ‖‖ContinuousLinearMap.compFormalMultilinearSeries f p n‖‖ ≤ ‖f‖ * ‖‖p n‖‖
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
refine' IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ _) (isBigO_refl _ _)
refine IsBigOWith.of_bound (eventually_of_forall fun n => ?_)
|
simpa only [norm_norm] using f.norm_compContinuousMultilinearMap_le (p n)
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
refine' IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ _) (isBigO_refl _ _)
refine IsBigOWith.of_bound (eventually_of_forall fun n => ?_)
|
Mathlib.Analysis.Analytic.Basic.357_0.jQw1fRSE1vGpOll
|
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius
|
Mathlib_Analysis_Analytic_Basic
|
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
f g : E → F
p pf pg : FormalMultilinearSeries 𝕜 E F
x : E
r r' : ℝ≥0∞
hf : HasFPowerSeriesOnBall f p x r
hg : EqOn f g (EMetric.ball x r)
y : E
hy : y ∈ EMetric.ball 0 r
⊢ HasSum (fun n => (p n) fun x => y) (g (x + y))
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
refine' IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ _) (isBigO_refl _ _)
refine IsBigOWith.of_bound (eventually_of_forall fun n => ?_)
simpa only [norm_norm] using f.norm_compContinuousMultilinearMap_le (p n)
#align formal_multilinear_series.radius_le_radius_continuous_linear_map_comp FormalMultilinearSeries.radius_le_radius_continuousLinearMap_comp
end FormalMultilinearSeries
/-! ### Expanding a function as a power series -/
section
variable {f g : E → F} {p pf pg : FormalMultilinearSeries 𝕜 E F} {x : E} {r r' : ℝ≥0∞}
/-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as
a power series on the ball of radius `r > 0` around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `‖y‖ < r`.
-/
structure HasFPowerSeriesOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) (r : ℝ≥0∞) :
Prop where
r_le : r ≤ p.radius
r_pos : 0 < r
hasSum :
∀ {y}, y ∈ EMetric.ball (0 : E) r → HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y))
#align has_fpower_series_on_ball HasFPowerSeriesOnBall
/-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as
a power series around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `y` in a neighborhood of `0`. -/
def HasFPowerSeriesAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) :=
∃ r, HasFPowerSeriesOnBall f p x r
#align has_fpower_series_at HasFPowerSeriesAt
variable (𝕜)
/-- Given a function `f : E → F`, we say that `f` is analytic at `x` if it admits a convergent power
series expansion around `x`. -/
def AnalyticAt (f : E → F) (x : E) :=
∃ p : FormalMultilinearSeries 𝕜 E F, HasFPowerSeriesAt f p x
#align analytic_at AnalyticAt
/-- Given a function `f : E → F`, we say that `f` is analytic on a set `s` if it is analytic around
every point of `s`. -/
def AnalyticOn (f : E → F) (s : Set E) :=
∀ x, x ∈ s → AnalyticAt 𝕜 f x
#align analytic_on AnalyticOn
variable {𝕜}
theorem HasFPowerSeriesOnBall.hasFPowerSeriesAt (hf : HasFPowerSeriesOnBall f p x r) :
HasFPowerSeriesAt f p x :=
⟨r, hf⟩
#align has_fpower_series_on_ball.has_fpower_series_at HasFPowerSeriesOnBall.hasFPowerSeriesAt
theorem HasFPowerSeriesAt.analyticAt (hf : HasFPowerSeriesAt f p x) : AnalyticAt 𝕜 f x :=
⟨p, hf⟩
#align has_fpower_series_at.analytic_at HasFPowerSeriesAt.analyticAt
theorem HasFPowerSeriesOnBall.analyticAt (hf : HasFPowerSeriesOnBall f p x r) : AnalyticAt 𝕜 f x :=
hf.hasFPowerSeriesAt.analyticAt
#align has_fpower_series_on_ball.analytic_at HasFPowerSeriesOnBall.analyticAt
theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r)
(hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r :=
{ r_le := hf.r_le
r_pos := hf.r_pos
hasSum := fun {y} hy => by
|
convert hf.hasSum hy using 1
|
theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r)
(hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r :=
{ r_le := hf.r_le
r_pos := hf.r_pos
hasSum := fun {y} hy => by
|
Mathlib.Analysis.Analytic.Basic.422_0.jQw1fRSE1vGpOll
|
theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r)
(hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r
|
Mathlib_Analysis_Analytic_Basic
|
case h.e'_6
𝕜 : Type u_1
E : Type u_2
F : Type u_3
G : Type u_4
inst✝⁶ : NontriviallyNormedField 𝕜
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
inst✝¹ : NormedAddCommGroup G
inst✝ : NormedSpace 𝕜 G
f g : E → F
p pf pg : FormalMultilinearSeries 𝕜 E F
x : E
r r' : ℝ≥0∞
hf : HasFPowerSeriesOnBall f p x r
hg : EqOn f g (EMetric.ball x r)
y : E
hy : y ∈ EMetric.ball 0 r
⊢ g (x + y) = f (x + y)
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
import Mathlib.Analysis.SpecificLimits.Normed
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.Algebra.InfiniteSum.Module
#align_import analysis.analytic.basic from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Analytic functions
A function is analytic in one dimension around `0` if it can be written as a converging power series
`Σ pₙ zⁿ`. This definition can be extended to any dimension (even in infinite dimension) by
requiring that `pₙ` is a continuous `n`-multilinear map. In general, `pₙ` is not unique (in two
dimensions, taking `p₂ (x, y) (x', y') = x y'` or `y x'` gives the same map when applied to a
vector `(x, y) (x, y)`). A way to guarantee uniqueness is to take a symmetric `pₙ`, but this is not
always possible in nonzero characteristic (in characteristic 2, the previous example has no
symmetric representative). Therefore, we do not insist on symmetry or uniqueness in the definition,
and we only require the existence of a converging series.
The general framework is important to say that the exponential map on bounded operators on a Banach
space is analytic, as well as the inverse on invertible operators.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`.
* `p.radius`: the largest `r : ℝ≥0∞` such that `‖p n‖ * r^n` grows subexponentially.
* `p.le_radius_of_bound`, `p.le_radius_of_bound_nnreal`, `p.le_radius_of_isBigO`: if `‖p n‖ * r ^ n`
is bounded above, then `r ≤ p.radius`;
* `p.isLittleO_of_lt_radius`, `p.norm_mul_pow_le_mul_pow_of_lt_radius`,
`p.isLittleO_one_of_lt_radius`,
`p.norm_mul_pow_le_of_lt_radius`, `p.nnnorm_mul_pow_le_of_lt_radius`: if `r < p.radius`, then
`‖p n‖ * r ^ n` tends to zero exponentially;
* `p.lt_radius_of_isBigO`: if `r ≠ 0` and `‖p n‖ * r ^ n = O(a ^ n)` for some `-1 < a < 1`, then
`r < p.radius`;
* `p.partialSum n x`: the sum `∑_{i = 0}^{n-1} pᵢ xⁱ`.
* `p.sum x`: the sum `∑'_{i = 0}^{∞} pᵢ xⁱ`.
Additionally, let `f` be a function from `E` to `F`.
* `HasFPowerSeriesOnBall f p x r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₙ yⁿ`.
* `HasFPowerSeriesAt f p x`: on some ball of center `x` with positive radius, holds
`HasFPowerSeriesOnBall f p x r`.
* `AnalyticAt 𝕜 f x`: there exists a power series `p` such that holds `HasFPowerSeriesAt f p x`.
* `AnalyticOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function admits a power series, it is continuous (see
`HasFPowerSeriesOnBall.continuousOn` and `HasFPowerSeriesAt.continuousAt` and
`AnalyticAt.continuousAt`).
* In a complete space, the sum of a formal power series with positive radius is well defined on the
disk of convergence, see `FormalMultilinearSeries.hasFPowerSeriesOnBall`.
* If a function admits a power series in a ball, then it is analytic at any point `y` of this ball,
and the power series there can be expressed in terms of the initial power series `p` as
`p.changeOrigin y`. See `HasFPowerSeriesOnBall.changeOrigin`. It follows in particular that
the set of points at which a given function is analytic is open, see `isOpen_analyticAt`.
## Implementation details
We only introduce the radius of convergence of a power series, as `p.radius`.
For a power series in finitely many dimensions, there is a finer (directional, coordinate-dependent)
notion, describing the polydisk of convergence. This notion is more specific, and not necessary to
build the general theory. We do not define it here.
-/
noncomputable section
variable {𝕜 E F G : Type*}
open Topology Classical BigOperators NNReal Filter ENNReal
open Set Filter Asymptotics
namespace FormalMultilinearSeries
variable [Ring 𝕜] [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F]
variable [TopologicalSpace E] [TopologicalSpace F]
variable [TopologicalAddGroup E] [TopologicalAddGroup F]
variable [ContinuousConstSMul 𝕜 E] [ContinuousConstSMul 𝕜 F]
/-- Given a formal multilinear series `p` and a vector `x`, then `p.sum x` is the sum `Σ pₙ xⁿ`. A
priori, it only behaves well when `‖x‖ < p.radius`. -/
protected def sum (p : FormalMultilinearSeries 𝕜 E F) (x : E) : F :=
∑' n : ℕ, p n fun _ => x
#align formal_multilinear_series.sum FormalMultilinearSeries.sum
/-- Given a formal multilinear series `p` and a vector `x`, then `p.partialSum n x` is the sum
`Σ pₖ xᵏ` for `k ∈ {0,..., n-1}`. -/
def partialSum (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) (x : E) : F :=
∑ k in Finset.range n, p k fun _ : Fin k => x
#align formal_multilinear_series.partial_sum FormalMultilinearSeries.partialSum
/-- The partial sums of a formal multilinear series are continuous. -/
theorem partialSum_continuous (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
Continuous (p.partialSum n) := by
unfold partialSum -- Porting note: added
continuity
#align formal_multilinear_series.partial_sum_continuous FormalMultilinearSeries.partialSum_continuous
end FormalMultilinearSeries
/-! ### The radius of a formal multilinear series -/
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
namespace FormalMultilinearSeries
variable (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
/-- The radius of a formal multilinear series is the largest `r` such that the sum `Σ ‖pₙ‖ ‖y‖ⁿ`
converges for all `‖y‖ < r`. This implies that `Σ pₙ yⁿ` converges for all `‖y‖ < r`, but these
definitions are *not* equivalent in general. -/
def radius (p : FormalMultilinearSeries 𝕜 E F) : ℝ≥0∞ :=
⨆ (r : ℝ≥0) (C : ℝ) (_ : ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C), (r : ℝ≥0∞)
#align formal_multilinear_series.radius FormalMultilinearSeries.radius
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound (C : ℝ) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
le_iSup_of_le r <| le_iSup_of_le C <| le_iSup (fun _ => (r : ℝ≥0∞)) h
#align formal_multilinear_series.le_radius_of_bound FormalMultilinearSeries.le_radius_of_bound
/-- If `‖pₙ‖ rⁿ` is bounded in `n`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_bound_nnreal (C : ℝ≥0) {r : ℝ≥0} (h : ∀ n : ℕ, ‖p n‖₊ * r ^ n ≤ C) :
(r : ℝ≥0∞) ≤ p.radius :=
p.le_radius_of_bound C fun n => mod_cast h n
#align formal_multilinear_series.le_radius_of_bound_nnreal FormalMultilinearSeries.le_radius_of_bound_nnreal
/-- If `‖pₙ‖ rⁿ = O(1)`, as `n → ∞`, then the radius of `p` is at least `r`. -/
theorem le_radius_of_isBigO (h : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) :
↑r ≤ p.radius :=
Exists.elim (isBigO_one_nat_atTop_iff.1 h) fun C hC =>
p.le_radius_of_bound C fun n => (le_abs_self _).trans (hC n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.le_radius_of_is_O FormalMultilinearSeries.le_radius_of_isBigO
theorem le_radius_of_eventually_le (C) (h : ∀ᶠ n in atTop, ‖p n‖ * (r : ℝ) ^ n ≤ C) :
↑r ≤ p.radius :=
p.le_radius_of_isBigO <| IsBigO.of_bound C <| h.mono fun n hn => by simpa
#align formal_multilinear_series.le_radius_of_eventually_le FormalMultilinearSeries.le_radius_of_eventually_le
theorem le_radius_of_summable_nnnorm (h : Summable fun n => ‖p n‖₊ * r ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_bound_nnreal (∑' n, ‖p n‖₊ * r ^ n) fun _ => le_tsum' h _
#align formal_multilinear_series.le_radius_of_summable_nnnorm FormalMultilinearSeries.le_radius_of_summable_nnnorm
theorem le_radius_of_summable (h : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_summable_nnnorm <| by
simp only [← coe_nnnorm] at h
exact mod_cast h
#align formal_multilinear_series.le_radius_of_summable FormalMultilinearSeries.le_radius_of_summable
theorem radius_eq_top_of_forall_nnreal_isBigO
(h : ∀ r : ℝ≥0, (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] fun _ => (1 : ℝ)) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_isBigO (h r)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.radius_eq_top_of_forall_nnreal_is_O FormalMultilinearSeries.radius_eq_top_of_forall_nnreal_isBigO
theorem radius_eq_top_of_eventually_eq_zero (h : ∀ᶠ n in atTop, p n = 0) : p.radius = ∞ :=
p.radius_eq_top_of_forall_nnreal_isBigO fun r =>
(isBigO_zero _ _).congr' (h.mono fun n hn => by simp [hn]) EventuallyEq.rfl
#align formal_multilinear_series.radius_eq_top_of_eventually_eq_zero FormalMultilinearSeries.radius_eq_top_of_eventually_eq_zero
theorem radius_eq_top_of_forall_image_add_eq_zero (n : ℕ) (hn : ∀ m, p (m + n) = 0) :
p.radius = ∞ :=
p.radius_eq_top_of_eventually_eq_zero <|
mem_atTop_sets.2 ⟨n, fun _ hk => tsub_add_cancel_of_le hk ▸ hn _⟩
#align formal_multilinear_series.radius_eq_top_of_forall_image_add_eq_zero FormalMultilinearSeries.radius_eq_top_of_forall_image_add_eq_zero
@[simp]
theorem constFormalMultilinearSeries_radius {v : F} :
(constFormalMultilinearSeries 𝕜 E v).radius = ⊤ :=
(constFormalMultilinearSeries 𝕜 E v).radius_eq_top_of_forall_image_add_eq_zero 1
(by simp [constFormalMultilinearSeries])
#align formal_multilinear_series.const_formal_multilinear_series_radius FormalMultilinearSeries.constFormalMultilinearSeries_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1`, `‖p n‖ rⁿ = o(aⁿ)`. -/
theorem isLittleO_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, (fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (a ^ ·) := by
have := (TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4
rw [this]
-- Porting note: was
-- rw [(TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 4]
simp only [radius, lt_iSup_iff] at h
rcases h with ⟨t, C, hC, rt⟩
rw [ENNReal.coe_lt_coe, ← NNReal.coe_lt_coe] at rt
have : 0 < (t : ℝ) := r.coe_nonneg.trans_lt rt
rw [← div_lt_one this] at rt
refine' ⟨_, rt, C, Or.inr zero_lt_one, fun n => _⟩
calc
|‖p n‖ * (r : ℝ) ^ n| = ‖p n‖ * (t : ℝ) ^ n * (r / t : ℝ) ^ n := by
field_simp [mul_right_comm, abs_mul]
_ ≤ C * (r / t : ℝ) ^ n := by gcongr; apply hC
#align formal_multilinear_series.is_o_of_lt_radius FormalMultilinearSeries.isLittleO_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ = o(1)`. -/
theorem isLittleO_one_of_lt_radius (h : ↑r < p.radius) :
(fun n => ‖p n‖ * (r : ℝ) ^ n) =o[atTop] (fun _ => 1 : ℕ → ℝ) :=
let ⟨_, ha, hp⟩ := p.isLittleO_of_lt_radius h
hp.trans <| (isLittleO_pow_pow_of_lt_left ha.1.le ha.2).congr (fun _ => rfl) one_pow
#align formal_multilinear_series.is_o_one_of_lt_radius FormalMultilinearSeries.isLittleO_one_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` tends to zero exponentially:
for some `0 < a < 1` and `C > 0`, `‖p n‖ * r ^ n ≤ C * a ^ n`. -/
theorem norm_mul_pow_le_mul_pow_of_lt_radius (h : ↑r < p.radius) :
∃ a ∈ Ioo (0 : ℝ) 1, ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C * a ^ n := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 1 5).mp
(p.isLittleO_of_lt_radius h)
rcases this with ⟨a, ha, C, hC, H⟩
exact ⟨a, ha, C, hC, fun n => (le_abs_self _).trans (H n)⟩
#align formal_multilinear_series.norm_mul_pow_le_mul_pow_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_mul_pow_of_lt_radius
/-- If `r ≠ 0` and `‖pₙ‖ rⁿ = O(aⁿ)` for some `-1 < a < 1`, then `r < p.radius`. -/
theorem lt_radius_of_isBigO (h₀ : r ≠ 0) {a : ℝ} (ha : a ∈ Ioo (-1 : ℝ) 1)
(hp : (fun n => ‖p n‖ * (r : ℝ) ^ n) =O[atTop] (a ^ ·)) : ↑r < p.radius := by
-- Porting note: moved out of `rcases`
have := ((TFAE_exists_lt_isLittleO_pow (fun n => ‖p n‖ * (r : ℝ) ^ n) 1).out 2 5)
rcases this.mp ⟨a, ha, hp⟩ with ⟨a, ha, C, hC, hp⟩
rw [← pos_iff_ne_zero, ← NNReal.coe_pos] at h₀
lift a to ℝ≥0 using ha.1.le
have : (r : ℝ) < r / a := by
simpa only [div_one] using (div_lt_div_left h₀ zero_lt_one ha.1).2 ha.2
norm_cast at this
rw [← ENNReal.coe_lt_coe] at this
refine' this.trans_le (p.le_radius_of_bound C fun n => _)
rw [NNReal.coe_div, div_pow, ← mul_div_assoc, div_le_iff (pow_pos ha.1 n)]
exact (le_abs_self _).trans (hp n)
set_option linter.uppercaseLean3 false in
#align formal_multilinear_series.lt_radius_of_is_O FormalMultilinearSeries.lt_radius_of_isBigO
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ * (r : ℝ) ^ n ≤ C :=
let ⟨_, ha, C, hC, h⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
⟨C, hC, fun n => (h n).trans <| mul_le_of_le_one_right hC.lt.le (pow_le_one _ ha.1.le ha.2.le)⟩
#align formal_multilinear_series.norm_mul_pow_le_of_lt_radius FormalMultilinearSeries.norm_mul_pow_le_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem norm_le_div_pow_of_pos_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h0 : 0 < r) (h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖ ≤ C / (r : ℝ) ^ n :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨C, hC, fun n => Iff.mpr (le_div_iff (pow_pos h0 _)) (hp n)⟩
#align formal_multilinear_series.norm_le_div_pow_of_pos_of_lt_radius FormalMultilinearSeries.norm_le_div_pow_of_pos_of_lt_radius
/-- For `r` strictly smaller than the radius of `p`, then `‖pₙ‖ rⁿ` is bounded. -/
theorem nnnorm_mul_pow_le_of_lt_radius (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0}
(h : (r : ℝ≥0∞) < p.radius) : ∃ C > 0, ∀ n, ‖p n‖₊ * r ^ n ≤ C :=
let ⟨C, hC, hp⟩ := p.norm_mul_pow_le_of_lt_radius h
⟨⟨C, hC.lt.le⟩, hC, mod_cast hp⟩
#align formal_multilinear_series.nnnorm_mul_pow_le_of_lt_radius FormalMultilinearSeries.nnnorm_mul_pow_le_of_lt_radius
theorem le_radius_of_tendsto (p : FormalMultilinearSeries 𝕜 E F) {l : ℝ}
(h : Tendsto (fun n => ‖p n‖ * (r : ℝ) ^ n) atTop (𝓝 l)) : ↑r ≤ p.radius :=
p.le_radius_of_isBigO (h.isBigO_one _)
#align formal_multilinear_series.le_radius_of_tendsto FormalMultilinearSeries.le_radius_of_tendsto
theorem le_radius_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : ↑r ≤ p.radius :=
p.le_radius_of_tendsto hs.tendsto_atTop_zero
#align formal_multilinear_series.le_radius_of_summable_norm FormalMultilinearSeries.le_radius_of_summable_norm
theorem not_summable_norm_of_radius_lt_nnnorm (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(h : p.radius < ‖x‖₊) : ¬Summable fun n => ‖p n‖ * ‖x‖ ^ n :=
fun hs => not_le_of_lt h (p.le_radius_of_summable_norm hs)
#align formal_multilinear_series.not_summable_norm_of_radius_lt_nnnorm FormalMultilinearSeries.not_summable_norm_of_radius_lt_nnnorm
theorem summable_norm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖ * (r : ℝ) ^ n := by
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius h
exact .of_nonneg_of_le (fun n => mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg _))
hp ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _)
#align formal_multilinear_series.summable_norm_mul_pow FormalMultilinearSeries.summable_norm_mul_pow
theorem summable_norm_apply (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => ‖p n fun _ => x‖ := by
rw [mem_emetric_ball_zero_iff] at hx
refine' .of_nonneg_of_le
(fun _ => norm_nonneg _) (fun n => ((p n).le_op_norm _).trans_eq _) (p.summable_norm_mul_pow hx)
simp
#align formal_multilinear_series.summable_norm_apply FormalMultilinearSeries.summable_norm_apply
theorem summable_nnnorm_mul_pow (p : FormalMultilinearSeries 𝕜 E F) {r : ℝ≥0} (h : ↑r < p.radius) :
Summable fun n : ℕ => ‖p n‖₊ * r ^ n := by
rw [← NNReal.summable_coe]
push_cast
exact p.summable_norm_mul_pow h
#align formal_multilinear_series.summable_nnnorm_mul_pow FormalMultilinearSeries.summable_nnnorm_mul_pow
protected theorem summable [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : Summable fun n : ℕ => p n fun _ => x :=
(p.summable_norm_apply hx).of_norm
#align formal_multilinear_series.summable FormalMultilinearSeries.summable
theorem radius_eq_top_of_summable_norm (p : FormalMultilinearSeries 𝕜 E F)
(hs : ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n) : p.radius = ∞ :=
ENNReal.eq_top_of_forall_nnreal_le fun r => p.le_radius_of_summable_norm (hs r)
#align formal_multilinear_series.radius_eq_top_of_summable_norm FormalMultilinearSeries.radius_eq_top_of_summable_norm
theorem radius_eq_top_iff_summable_norm (p : FormalMultilinearSeries 𝕜 E F) :
p.radius = ∞ ↔ ∀ r : ℝ≥0, Summable fun n => ‖p n‖ * (r : ℝ) ^ n := by
constructor
· intro h r
obtain ⟨a, ha : a ∈ Ioo (0 : ℝ) 1, C, - : 0 < C, hp⟩ := p.norm_mul_pow_le_mul_pow_of_lt_radius
(show (r : ℝ≥0∞) < p.radius from h.symm ▸ ENNReal.coe_lt_top)
refine' .of_norm_bounded
(fun n => (C : ℝ) * a ^ n) ((summable_geometric_of_lt_1 ha.1.le ha.2).mul_left _) fun n => _
specialize hp n
rwa [Real.norm_of_nonneg (mul_nonneg (norm_nonneg _) (pow_nonneg r.coe_nonneg n))]
· exact p.radius_eq_top_of_summable_norm
#align formal_multilinear_series.radius_eq_top_iff_summable_norm FormalMultilinearSeries.radius_eq_top_iff_summable_norm
/-- If the radius of `p` is positive, then `‖pₙ‖` grows at most geometrically. -/
theorem le_mul_pow_of_radius_pos (p : FormalMultilinearSeries 𝕜 E F) (h : 0 < p.radius) :
∃ (C r : _) (hC : 0 < C) (_ : 0 < r), ∀ n, ‖p n‖ ≤ C * r ^ n := by
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 h with ⟨r, r0, rlt⟩
have rpos : 0 < (r : ℝ) := by simp [ENNReal.coe_pos.1 r0]
rcases norm_le_div_pow_of_pos_of_lt_radius p rpos rlt with ⟨C, Cpos, hCp⟩
refine' ⟨C, r⁻¹, Cpos, by simp only [inv_pos, rpos], fun n => _⟩
-- Porting note: was `convert`
rw [inv_pow, ← div_eq_mul_inv]
exact hCp n
#align formal_multilinear_series.le_mul_pow_of_radius_pos FormalMultilinearSeries.le_mul_pow_of_radius_pos
/-- The radius of the sum of two formal series is at least the minimum of their two radii. -/
theorem min_radius_le_radius_add (p q : FormalMultilinearSeries 𝕜 E F) :
min p.radius q.radius ≤ (p + q).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
rw [lt_min_iff] at hr
have := ((p.isLittleO_one_of_lt_radius hr.1).add (q.isLittleO_one_of_lt_radius hr.2)).isBigO
refine' (p + q).le_radius_of_isBigO ((isBigO_of_le _ fun n => _).trans this)
rw [← add_mul, norm_mul, norm_mul, norm_norm]
exact mul_le_mul_of_nonneg_right ((norm_add_le _ _).trans (le_abs_self _)) (norm_nonneg _)
#align formal_multilinear_series.min_radius_le_radius_add FormalMultilinearSeries.min_radius_le_radius_add
@[simp]
theorem radius_neg (p : FormalMultilinearSeries 𝕜 E F) : (-p).radius = p.radius := by
simp only [radius, neg_apply, norm_neg]
#align formal_multilinear_series.radius_neg FormalMultilinearSeries.radius_neg
protected theorem hasSum [CompleteSpace F] (p : FormalMultilinearSeries 𝕜 E F) {x : E}
(hx : x ∈ EMetric.ball (0 : E) p.radius) : HasSum (fun n : ℕ => p n fun _ => x) (p.sum x) :=
(p.summable hx).hasSum
#align formal_multilinear_series.has_sum FormalMultilinearSeries.hasSum
theorem radius_le_radius_continuousLinearMap_comp (p : FormalMultilinearSeries 𝕜 E F)
(f : F →L[𝕜] G) : p.radius ≤ (f.compFormalMultilinearSeries p).radius := by
refine' ENNReal.le_of_forall_nnreal_lt fun r hr => _
apply le_radius_of_isBigO
apply (IsBigO.trans_isLittleO _ (p.isLittleO_one_of_lt_radius hr)).isBigO
refine' IsBigO.mul (@IsBigOWith.isBigO _ _ _ _ _ ‖f‖ _ _ _ _) (isBigO_refl _ _)
refine IsBigOWith.of_bound (eventually_of_forall fun n => ?_)
simpa only [norm_norm] using f.norm_compContinuousMultilinearMap_le (p n)
#align formal_multilinear_series.radius_le_radius_continuous_linear_map_comp FormalMultilinearSeries.radius_le_radius_continuousLinearMap_comp
end FormalMultilinearSeries
/-! ### Expanding a function as a power series -/
section
variable {f g : E → F} {p pf pg : FormalMultilinearSeries 𝕜 E F} {x : E} {r r' : ℝ≥0∞}
/-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as
a power series on the ball of radius `r > 0` around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `‖y‖ < r`.
-/
structure HasFPowerSeriesOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) (r : ℝ≥0∞) :
Prop where
r_le : r ≤ p.radius
r_pos : 0 < r
hasSum :
∀ {y}, y ∈ EMetric.ball (0 : E) r → HasSum (fun n : ℕ => p n fun _ : Fin n => y) (f (x + y))
#align has_fpower_series_on_ball HasFPowerSeriesOnBall
/-- Given a function `f : E → F` and a formal multilinear series `p`, we say that `f` has `p` as
a power series around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `y` in a neighborhood of `0`. -/
def HasFPowerSeriesAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) :=
∃ r, HasFPowerSeriesOnBall f p x r
#align has_fpower_series_at HasFPowerSeriesAt
variable (𝕜)
/-- Given a function `f : E → F`, we say that `f` is analytic at `x` if it admits a convergent power
series expansion around `x`. -/
def AnalyticAt (f : E → F) (x : E) :=
∃ p : FormalMultilinearSeries 𝕜 E F, HasFPowerSeriesAt f p x
#align analytic_at AnalyticAt
/-- Given a function `f : E → F`, we say that `f` is analytic on a set `s` if it is analytic around
every point of `s`. -/
def AnalyticOn (f : E → F) (s : Set E) :=
∀ x, x ∈ s → AnalyticAt 𝕜 f x
#align analytic_on AnalyticOn
variable {𝕜}
theorem HasFPowerSeriesOnBall.hasFPowerSeriesAt (hf : HasFPowerSeriesOnBall f p x r) :
HasFPowerSeriesAt f p x :=
⟨r, hf⟩
#align has_fpower_series_on_ball.has_fpower_series_at HasFPowerSeriesOnBall.hasFPowerSeriesAt
theorem HasFPowerSeriesAt.analyticAt (hf : HasFPowerSeriesAt f p x) : AnalyticAt 𝕜 f x :=
⟨p, hf⟩
#align has_fpower_series_at.analytic_at HasFPowerSeriesAt.analyticAt
theorem HasFPowerSeriesOnBall.analyticAt (hf : HasFPowerSeriesOnBall f p x r) : AnalyticAt 𝕜 f x :=
hf.hasFPowerSeriesAt.analyticAt
#align has_fpower_series_on_ball.analytic_at HasFPowerSeriesOnBall.analyticAt
theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r)
(hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r :=
{ r_le := hf.r_le
r_pos := hf.r_pos
hasSum := fun {y} hy => by
convert hf.hasSum hy using 1
|
apply hg.symm
|
theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r)
(hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r :=
{ r_le := hf.r_le
r_pos := hf.r_pos
hasSum := fun {y} hy => by
convert hf.hasSum hy using 1
|
Mathlib.Analysis.Analytic.Basic.422_0.jQw1fRSE1vGpOll
|
theorem HasFPowerSeriesOnBall.congr (hf : HasFPowerSeriesOnBall f p x r)
(hg : EqOn f g (EMetric.ball x r)) : HasFPowerSeriesOnBall g p x r
|
Mathlib_Analysis_Analytic_Basic
|
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