cover......Page 1
Elementary Geometry of Algebraic Curves: an Undergraduate Introduction......Page 4
Contents......Page 8
List of Illustrations......Page 11
Preface......Page 14
1 Real Algebraic Curves......Page 18
2 General Ground Fields......Page 37
3 Polynomial Algebra......Page 50
4 Affine Equivalence......Page 64
5 Affine Conics......Page 77
6 Singularities of Affine Curves......Page 88
7 Tangents to Affine Curves......Page 102
8 Rational Affine Curves......Page 112
9 Projective Algebraic Curves......Page 125
10 Singularities of Projective Curves......Page 142
11 Projective Equivalence......Page 154
12 Projective Tangents......Page 165
13 Flexes......Page 179
14 Intersections of Projective Curves......Page 190
15 Projective Cubics......Page 207
16 Linear Systems......Page 218
17 The Group Strueture on a euhie......Page 234
18 Rational Projective Curves......Page 251
Index......Page 264

##### Citation preview

Elementary Geometry of Algebraic Curves: an Undergraduate Introduction This is a genuine introduction to plane algebraic curves from a geometric viewpoint, designed as a first text for undergraduates in mathematics, or for postgraduate and research workers in the engineering and physical sciences. It is well illustrated, and contains several hundred worked examples and exercises, making it suitable for adoption as a course text. From the familiar lines and conics of elementary geometry the reader proceeds to general curves in the real affine plane, with excursions to more general fields to illustrate applications, such as number theory. By adding points at infinity the affine plane is extended to the projective plane, yielding a natural setting for curves and providing a flood of illumination into the underlying geometry. A minimal amount of algebra leads to the famous theorem of Bezout, whilst the ideas of linear systems are used to discuss the classical group structure on the cubic.

c. G. Gibson is Senior Fellow in Mathematical Sciences, University of Liverpool.

Elementary Geometry of Algebraic Curves: an Undergraduate Introduction c.

G. Gibson

!~'N CAMBRIDGE ~~~

UNIVERSITY PRESS

The Pitt Building, Trumpington Street, Cambridge CB2 1RP, United Kingdom CAMBRIDGE UNIVERSITY PRESS

The Edinburgh Building, Cambridge CB2 2RU, UK http://www.cup.cam.ac.uk 40 West 20th Street, New York, NY 10011-4211, USA http://www.cup.org 10 Stamford Road, Oakleigh, Melbourne 3166, Australia

Cambridge University Press 1998

This book is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press First published 1998 Printed in the United Kingdom at the University Press, Cambridge Typeset in Times 10/ 13pt, in Jb.TEX A catalogue record for this book is available from the British Library Library of Congress Cataloguing in Publication data

Gibson, Christopher G., 1940- . Elementary geometry of algebraic curves / C. G. Gibson. p. cm. ISBN 0 521 64140 3 (hardbound) 1. Curves, Algebraic. I. Title. QA565.G5 1998 516.3'52-dc21 98-36910 CIP ISBN 0 521 64140 3 hardback ISBN 0 521 64641 3 paperback

To Dorle

Contents

page x xii xiii

List of Illustrations List of Tables Preface

1 1.1 1.2 1.3 2 2.1 2.2 2.3 2.4 3 3.1 3.2 3.3

3.4 3.5 4 4.1 4.2

4.3 4.4 5 5.1 5.2 5.3

Real Algebraic Curves Parametrized and Implicit Curves Introductory Examples Curves in Planar Kinematics General Ground Fields Two Motivating Examples Groups, Rings and Fields General Affine Planes and Curves Zero Sets of Algebraic Curves Polynomial Algebra Factorization in Domains Polynomials in One Variable Polynomials in Several Variables Homogeneous Polynomials Formal Differentiation Affine Equivalence Affine Maps Affine Equivalent Curves Degree as an Affine Invariant Centres as Affine Invariants Affine Conics Affine Classification The Delta Invariants Uniqueness of Equations VB

1 1

3 12 20 20 22 25 28

33 33 35 38 42 44

47 48 49 51 53

60 61 64 68

vIn 6 6.1

6.2 6.3 7 7.1 7.2 7.3 7.4

8 8.1 8.2 8.3 9 9.1 9.2 9.3 9.4 9.5 10 10.1 10.2 10.3 10.4

11 11.1 11.2 11.3 11.4

12 12.1 12.2 12.3 12.4 12.5 12.6

13 13.1

13.2

Contents

Singularities of Affine Curves Intersection Numbers Multiplicity of a Point on a Curve Singular Points Tangents to Affine Curves Generalities about Tangents Tangents at Simple Points Tangents at Double Points Tangents at Points of Higher Multiplicity Rational Affine Curves Rational Curves Diophantine Equations Conics and Integrals Projective Algebraic Curves The Projective Plane Projective Lines Affine Planes in the Projective Plane Projective Curves Affine Views of Projective Curves Singularities of Projective Curves Intersection Numbers Multiplicity of a Point on a Curve Singular Points Delta Invariants viewed Projectively Projective Equivalence Projective Maps Projective Equivalence Projective Conics Affine and Projective Equivalence Projective Tangents Tangents to Projective Curves Tangents at Simple Points Centres viewed Projectively Foci viewed Projectively Tangents at Singular Points Asymptotes Flexes Hessian Curves Configurations of Flexes

71 71 77 80

85 85 86 88 91 95 96 101 106 108 108 110 115 117 118

125 125 129 130 134

137 137 140 142 144 148 148 149 150 152 156 159

162 163 169

Contents

14 14.1 14.2 14.3 14.4 14.5 14.6 15 15.1 15.2 15.3 15.4 16 16.1 16.2 16.3 16.4 16.5 16.6

17 17.1 17.2 17.3 17.4 17.5 18 18.1 18.2 18.3 18.4 18.5 Index

Intersections of Projective Curves The Geometric Idea Resultants in One Variable Resultants in Several Variables Bezout's Theorem The Multiplicity Inequality Invariance of the Intersection Number Projective Cubics Geometric Types of Cubics Cubics of General Type Singular Irreducible Cubics Reducible Cubics Linear Systems Projective Spaces of Curves Pencils of Curves Solving Quartic Equations Subspaces of Projective Spaces Linear Systems of Curves Dual Curves The Group Structure on a Cubic The Nine Associated Points The Star Operation Cubics as Groups Group Computations Determination of the Groups Rational Projective Curves The Projective Concept Quartics with Three Double Points The Deficiency of a Curve Some Rational Curves Some Non-Rational Curves

IX

173 173 175 177 179 184 187

190 190 194 196 198

201 201 203 207 208 210 213

217 217 221 222

226 229

234 234 236 240 242 245 247

List of Illustrations

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.10 1.11 2.1 2.2 2.3 2.4 4.1 4.2 4.3 4.4 6.1 6.2 6.3 6.4

Constructions of standard conics Construction of pedal curves Pedals of a parabola Bezier curve with control points bo, bl , b2 , b3 The three forms of a limacon Watt four bar linkage Planar motion with one dof The double slider motion The fixed and moving coordinate systems The Newton motion Four bar linkage coupler curve Horizontal line meeting a circle The affine plane over Z3 Agnesi's versiera and the Serpentine The curves y2 = x 3 - 3x + A Superimposing two curves Affine equivalent curves The concept of a centre Diameters of an ellipse Coalescence of intersections Lines intersecting the eight-curve The boomerang Triple point on the three-leaved clover 6.5 The astroid 6.6 The Maltese cross 6.7 An invisible singular point 7.1 Inscribing an ellipse in a parallelogram 7.2 Types of real double point 7.3 Double points in a family of cubics 7.4 The four-leaved clover

x

5 6 7 8 10 13 14 15 15 17 18 21 27 28 30 48 50 55 58 72 74 76 78 79 81 82 87 89 90

92

List of Illustrations

8.1 8.2 8.3 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8 9.9 10.1 11.1 12.1 12.2 12.3 12.4 13.1 14.1 14.2 14.3 15.1 16.1 16.2 16.3 16.4 16.5 17.1 17.2 17.3 17.4 17.5 17.6 17.7 17.8 18.1

Rationality of circle and hyperbola Rationality of the folium of Descartes Rationality of xy + (x 2 + y2)2 Affine plane in 3-space Real projective line as a circle Complex projective line as a sphere The projective plane over Z2 Hemisphere model of p]R2 Projective curve in the spherical model Three affine views of a cubic curve Three hemispherical views of a cubic curve Two affine views of the eight-curve Simple, double and triple points Root patterns of cubics in one variable Centres viewed projectively Focus of a parabola Foci of ellipses and hyperbolas Asymptotes of the cross curve Two flexes of the Fermat cubic Projection from a point to a line Projecting intersections onto a line Intersection patterns of two conics Deforming a cuspidal cubic The real projective line Pencil of lines through a point Three line-pairs in a pencil of conics Dual concepts of collinearity and concurrency The concept of the dual curve Nine associated points: the general case Pascal's Mystic Hexagon The star operation Properties of the star operation Configuration of flexes on a general cubic Group operations on a Weierstrass normal form A lattice in ee 2 Deforming a triangle to obtain a torus The quadratic transformation

Xl

96 99 99 109 112 113 114 116 118 119 120 121 129 147 151 154 155 160 170 174 174 182 198 202 204

206 214 214 218 220 221 222 225 227 232 233 237

List of Tables

5.1 5.2 5.3 5.4 11.1 11.2 11.3 11.4 15.1 16.1

The nine types of real affine conic The five types of complex affine conics Invariants for complex affine conics Invariants for real affine conics The three types of complex projective conic The five types of real projective conic Complex affine conics viewed projectively Real affine conics viewed projectively Geometric types of cubics Projective subspaces

XlI

62 63 65 66 142 143 145 145 192 209

Preface

For some time I have felt there is a good case for raising the profile of undergraduate geometry. The case can be argued on academic grounds alone. Geometry represents a way of thinking within mathematics, quite distinct from algebra and analysis, and so offers a fresh perspective on the subject. It can also be argued on purely practical grounds. My experience is that there is a measure of concern in various practical disciplines where geometry plays a substantial role (engineering science for instance) that their students no longer receive a basic geometric training. And thirdly, it can be argued on psychological grounds. Few would deny that substantial areas of mathematics fail to excite student interest: yet there are many students attracted to geometry by its sheer visual content. The decline in undergraduate geometry is a bit of a mystery. It probably has something to do with the fashion for formalism which seemed to permeate mathematics some decades ago. But things are changing. The enormous progress made in studying non-linear phenomena by geometrical methods has certainly revived interest in geometry. And for material reasons, tertiary institutions are ever more conscious of the need to offer their students more attractive courses.

0.1 General Background I first became involved in the teaching of geometry about twenty years ago, when my department introduced an optional second year course on the geometry of plane curves, partly to redress the imbalance in the teaching of the subject. It was mildly revolutionary, since it went back to an earlier set of precepts where the differential and algebraic geometry of curves were pursued simultaneously, to their mutual advantage. In the final year of study, students could pursue this kind of geometry Xl11

xiv

Preface

by following traditional courses on the differential geometry of curves and surfaces. But in the area of algebraic geometry, matters were more problematic. A course on the geometry of algebraic curves seemed to me to be the obvious kind of development. The problem was a dearth of suitable texts. Some had developed from courses lasting for a whole session, where it was possible to attain some distance. By contrast, I was faced with a single semester course, offered over a period which saw a decline in the technical accomplishments of our students. I simply could not hope to be so ambitious. Also I find myself out of sympathy with colleagues who fret that they fail to reach significant results. I belong firmly to the school of thought which believes that it is far better to obtain a thorough appreciation of the basics than to reach some technical pinnacle. Elementary facts (for instance, the fact that the centre of a circle can be defined projectively, rather than metrically) can have a stunning impact on students. My view is that the few who wish to pursue more advanced aspects of the subject can always proceed to higher degrees where their needs will be met. This book arose from my lecture notes after several years of experimentation. It has gained enormously from the reaction of my students over the years; they have proved to be my harshest critics, and my most helpful advisers, and I owe them a great deal.

0.2 Required Mathematical Knowledge

The intending reader will probably want to know how much mathematical knowledge is assumed of him. Let me first state quite clearly that one of my objectives was to make this book as accessible as possible. I am well aware of the needs of workers in other fields who do not have a substantial mathematical background: and I feel strongly that it is the very beginnings of the subject which need proper exposition. The more experienced reader will find that this book can be viewed as a stepping stone to many excellent texts which assume a higher level of mathematical preparation. In the area of algebra, the most basic requirement is a good understanding of the elements of linear algebra. The abstract concepts of group, domain and field do occur, and are recalled in Section 2.2: but they only occur in a fairly marginal way - you certainly should not be put off just because you are not familiar with these ideas. More substantially, much of the material rests on the unique factorization of polynomials in several variables: however, all the necessary definitions are given, the result itself is carefully stated, and references are given

0.3 Concerning the Structure

xv

to the proof for those who wish to see it. In the area of analysis, I do assume the elements of calculus in several variables; basically, you need to be able to work out partial derivatives. The reader should be fluent in handling complex numbers, particularly complex roots of unity which appear in many of the calculations. Beyond that I only assume that the reader has come across the Fundamental Theorem of Algebra, i.e. the statement that every polynomial of positive degree in a single variable has at least one complex zero, but you only need the statement of the result. As to geometry, it would certainly help to have a little background (some familiarity with lines and conics for instance) but effectively the book is quite self-contained. I made a conscious decision to make the material independent of virtually any knowledge of topology. In practice that means that a small number of statements are made without proof. More regrettably, that decision precluded the possibility of developing one of the great historical ideas of the subject, that complex curves can be viewed as real surfaces.

0.3 Concerning the Structure

Concerning the structure of the book, I should say that roughly the first half is devoted to curves in the (familiar) affine plane, and the second to curves in the (less familiar) projective plane. I wanted my reader to feel quite comfortable with the mechanics of handling affine curves before making the conceptually difficult transition to the projective plane. One of the main functions of this book is to place algebraic curves in their natural setting (the complex projective plane) where their structure is more transparent. For some readers, particularly those whose background is not in mathematics, this may prove to be a psychological barrier. I can only assure such readers that the reward is much greater than the mental effort involved. History has shown that placing algebraic curves in a natural setting provides a flood of illumination, enabling one much better to comprehend the features one meets in everyday applications. I made a deliberate effort to keep the individual chapters fairly short, adopting the theory that each chapter revolves around one new idea; likewise the sections are brief, and punctuated by a series of 'examples' illustrating the concepts. I have included a collection of exercises, designed to illustrate (and even amplify) the small amount of theory. Each chapter contains sets of exercises, each appearing immediately after the relevant section. I felt it was a service to the mathematics community to gather

xvi

Preface

together a coherent set of exercises for the benefit of teachers; many have been culled from the older literature.

0.4 Concerning the Content

The content of the book is largely classical. There is a tendency in the subject to overemphasize examples of curves drawn from the distant past. I wanted to make the point that the resurgence of geometry is based on the role it plays in the increasing mathematization of the physical sciences. Thus I have indulged my own passion for the curves which arise in engineering kinematics, a sadly neglected subject (the real beginnings of theoretical robotics) which deserves to be better known both for its intrinsic interest and its considerable mathematical potential. I make no apologies for the fact that conics occupy a substantial part of the text; they playa significant role in geometry at this level, and my view is that their intrinsic importance should be reflected in the space devoted to them. On the same basis, cubics receive an extended discussion. In particular, I regard the group structure on the cubic as one of the most attractive topics of elementary geometry within the reach of a mathematics undergraduate; for me, it is the mathematical equivalent of a treasured holiday snapshot. So far as objectives are concerned, I felt it was sensible to get as far as Bezout's Theorem, to justify in some measure the assertion that algebraic curves live naturally in the complex projective plane. Some topics are conspicuous by their absence. For instance, I have great affection for the lost art of tracing algebraic curves, to which Frost's classic text on 'Curve Tracing' is a fitting memorial. Like archery, it is a satisfying pursuit, of little relevance to the world we live in. But just as the machine gun has rendered the bow obsolete, so the computer has proved itself a superbly efficient tool for tracing curves at phenomenal speeds. In this connexion, I am particularly grateful to Wendy Hawes, who constructed a picturebook of algebraic curves using the graphics facilities of the Pure Mathematics Department in The University of Liverpool, and kindly allowed me to include her pictures. Finally, I offer my warmest thanks to my friend and colleague Bill Bruce who read a working draft, and produced a wealth of valuable comment.

1 Real Algebraic Curves

Plane curves arise naturally in numerous areas of the physical sciences (such as particle physics, engineering robotics and geometric optics) and within areas of pure mathematics itself (such as number theory, complex analysis and differential equations). In this introductory chapter, we will motivate some of the basic ideas and set up the underlying language of affine algebraic curves. That will also give us the opportunity to preview some of the material you will meet in the later chapters.

1.1 Parametrized and Implicit Curves At root there are two ways in which a curve in the real plane described. The distinction is quite fundamental.

]R2

may be

• A curve may be defined param,etrically, in the form x == x(t), y == y(t). The parametrization gives this image a dynamic structure: indeed at any parameter value t we have a tangent vector (x'(t), y'(t)) whose length is the speed of the curve at the parameter t. An example is the line parametrized by x == t, Y == t, with constant speed another parametrization such as x == 2t, Y == 2t yields the same image, but at twice the speed • A curve may be defined implicitly, as the set of points (x, y) in the plane satisfying an equation f(x,y) == 0, where f(x,y) is some reasonable function of x, y. For instance the line parametrized by x == t, Y == t arises from the function f(x, y) == y - x. Such a curve has no associated dynamic structure - it is simply a set of points in the plane.

J2,

2J2.

Broadly speaking, the study of parametrized curves represents the beginnings of a major area of mathematics called d~fferential geometry, whilst the study of curves defined implicitly represents the beginnings 1

Real Algebraic Curves

2

of another major area, algebraic geometry. It is the latter study which provides the material for this book, though at various junctures we will have something to say about the question of parametrization. The common feature of many curves which appear in practice is that they are defined implicitly by equations of the form f(x, y) = 0 where f(x,y) is a real polynomial in the variables x, y, i.e. given by a formula of the shape f(x,y) = Laijxiyj i,j

where the sum is finite and the coefficients aij are real numbers. There is much to gain in restricting attention to such curves, since they enjoy a number of important 'finiteness' properties. Moreover, it will be both profitable and illuminating to extend the concepts to situations where the coefficients aij lie in a more general 'ground field'. In some sense the complexity of a polynomial f(x,y) is measured by its degree, i.e. the maximal value of i + j over the indices i, j with aij =!= O. Given a polynomial f(x,y) we define its zero set to be Vf

= {(x,y)

E

ffi.2 : f(x,y)

= O}.

Instead of saying that a point (x, y) lies in the zero set of a curve f we may, for linguistic variety, say that (x, y) lies on the curve f, or that f passes through (x,y). Note that the zero set (and the degree) are unchanged when we multiply f by a non-zero scalar. It is for that reason that we introduce the following formal definition. A real algebraic curve is a non-zero real polynomial f, up to rnultiplication by a non-zero scalar. The more formally inclined reader may prefer to phrase this in terms of 'equivalence relations'. Two polynomials f, g are equivalent, written f g, when there exists a non-zero scalar A for which g = Af. It is then trivially verified that has the defining properties of an equivalence relation: it is reflexive (f f), it is symmetric (if f g then g f), and it is transitive (if f g and g h then f h). A real algebraic curve is then formally defined to be an equivalence class of polynomials under the So strictly speaking, a real algebraic curve is an equivalence relation set of all polynomials Af(x,y) with A =!= 0, and any polynomial in this set is a representative for the curve. In this book we will usually abbreviate the term 'algebraic curve' to 'curve'. Curves of degree 1, 2, 3, 4, ... are called lines, conics, cubics, quartics, .... It is a long established convention that the curve with representative polynomial f(x, y) is referred to as the 'curve' f(x,y) = O. There is no harm in this provided you remember that I"V

I"V

I"V

I"V

I"V.

I"V

I"V

I"V

I"V

1.2 Introductory Examples

3

it is a convention, and not a shorthand for the zero set. Thus y = x and 2y = 2x represent the same curve of degree 1. It is an unfortunate fact of life that when dealing with the simplest possible curves of elementary geometry (such as the lines and standard conics discussed in the next section) the distinction between curves and their zero sets can be blurred without undue consequences. However, as one proceeds into algebraic geometry the relation between the two concepts becomes crucial, and leads to some of the most fundamental results in the subject. The reader is warned, even at this very early stage, to make a crystal clear mental distinction between the concept of a curve, and that of its zero set.

1.2 Introductory Examples In this section we present a small selection of curves, illustrating some of the general concepts which will occur later. For reasons of space, it is simply not feasible to give an account of even the more significant situations (in the physical sciences, and within pure mathematics itself) where curves arise, as each such situation would demand at least some of the pertinent underlying mathematics to be developed. However, the impatient reader, wishing to see 'real' curves (in the sense of 'real' ale), might like to jump to Section 1.3 which presents some of the curves arising in planar kinematics. A good guiding philosophy is to begin at the beginning (though we will not end at the end) and work with increasing degree. Curves of degree 1 are lines, and playa fundamental role in understanding the geometry of general curves. We will recall their most important attributes via a series of examples. According to the above definition a line has the form ax + by + c with at least one of a, b non-zero.

Example 1.1 Given any two distinct points p = (Pl, P2), q = (ql, q2) in ffi.2 there is a unique line ax + by + c passing through P, q. We seek scalars a, b, c (not all zero) for which

aql

+ bq2 + c = o.

Since P, q are distinct, the 2 x 3 coefficient matrix of these two linear equations in a, b, c has rank 2. By linear algebra it has kernel rank 1, so there is a non-trivial solution (a, b, c), and any other solution is a non-zero scalar multiple of this one. Explicitly, the line joining P, q is

4

Real Algebraic Curves

given by

Note this point well: the equation of a line is determined up to scalar multiples by its zero set. For higher degree curves that can fail.

Example 1.2 Consider two lines alX + bly + Cl, a2X + b2y + C2 in ~2. The intersection points (x, y) are those points which satisfy the linear equations

By linear algebra, when the determinant b = a 1b2 - a2bI =1= 0 these equations have a unique solution (x, y). Otherwise, there is no solution (parallel lines) or a line of solutions (coincident lines).

Example 1.3 Let 1 be a line, and let p be a point not on 1. Then there is a unique line m through p parallel to 1. Suppose that 1 has equation ax + by + c = O. It follows from the previous example that the lines m parallel to 1 are those of the form ax + by + d = 0, with d arbitrary. The condition for m to pass through p then determines d uniquely. Example 1.4 Lines can be parametrized in a natural way. Consider a line ax + by + c, and distinct points p = (PI, P2), q = (ql' q2) on the line. Then a brief calculation verifies that any point P + 2(q - p) = (1 - 2)p + 2q also lies on the line. Conversely, we claim that any point r = (rl, r2) on the line has the form r = (1 - 2)p + 2q for some scalar 2. Since p, q, r all lie on the line we have api + bp2 + c aqi + bq2 + c { arl + br2 + c

= 0 =

0

=

o.

That is a linear system of three equations in a, b, c. Since at least one of a, b is non-zero, the system has a non-trivial solution. By linear algebra, the 3 x 3 matrix of coefficients is singular, so the rows (PI,P2, 1), (ql,q2, 1), (rl, r2, 1) are linearly dependent. However, the first two rows are linearly independent (as P, q are distinct) so the third row is a linear combination of the first two, i.e. (rl,r2, 1) = K(PI,P2, 1) + 2(ql,q2, 1) for some scalars K, 2. That means r = Kp + 2q and 1 = K + 2, so r = (1 - 2)p + 2q, as required.

1.2 Introductory Examples

5

o

L

Fig. 1.1. Constructions of standard conics

Note that the parametrization of a line depends on the choice of points p, q. Given two distinct points p = (PI, P2), q = (ql, q2), the parametrized line through p, q is the specific parametric curve given by the above example, namely x = (1 - A)PI + Aql, Y = (1 - A)P2 + Aq2. Example 1.5 Conics will be a recurrent theme in this text. The most familiar conic by far is the circle, defined metrically as the locus of points (x, y) whose distance from a fixed point (a, b) in the plane (the centre) takes a constant value r > 0 (the radius). A circle is thus the zero set of a polynomial (x - a)2 + (y - b)2 = r2. The 'standard' parametrization of the circle is x = a + r cos t, y = b + r sin t, but we will meet other parametrizations later. Example 1.6 The reader has probably met the 'standard conics' of elementary geometry via a metrical construction going back to the classical Greeks. One is given a line L (the directrix), a point F (the focus) not on L, and a variable point P whose distance from F is proportional to its distance from L. 0 denotes the unique point on L for which L is perpendicular to the line through 0, F. (See Figure 1.1.) The locus of P is known as a 'parabola', an 'ellipse', or a 'hyperbola' according as the constant of proportionality e (the eccentricity) is = 1, < 1 or > 1. The fact that P lies on a conic is demonstrated by taking 0 to be the origin, L to be the y-axis, and the line OF to be the x-axis (with F on the positive axis). Then, setting F = (2a, 0) with a > 0, the condition on P = (x,y) is (x-2a)2+ y2 = e2x 2, which is indeed a conic. For instance in the case e = 1 of a parabola this becomes 4a(a - x) + y2 = 0: the translation x = X +a, y = Y then yields the standard parabola y 2 = 4aX

6

Real Algebraic Curves

Fig. 1.2. Construction of pedal curves

with focus F = (a,O) and directrix X = -a. In Chapter 4 we will have more to say about the process of reducing polynomials to such 'normal' forms by applying translations, and more generally 'affine mappings'.

Example 1.7 A regular parameter of a parametrized curve x = x(t), y = y(t) is a parameter t for which the tangent vector (x'(t), y'(t)) is non-zero. The unique line through P = (x(t), y(t)) in the direction of the tangent vector is the tangent line to the parametrized curve at t, given parametrically as x = x(t) + AX'(t), y = y(t) + Ay'(t). It is the line y'(t)x - x'(t)y

+ {x'(t)y(t) -

x(t)y'(t)} = O.

Tangent lines playa fundamental role in studying parametrized curves. We will discuss tangent lines to algebraic curves in Chapter 7 and relate them to the concept just introduced for parametrized curves. Numerous interesting constructions are based on the tangent lines to parametrized curves, and give rise to a zoo of interesting curves. One such construction is that of the 'pedal', of considerable importance in geometric optics and kinematics. Suppose we are given a regular parametrized curve x = x(t), y = y(t), i.e. one for which every parameter t is regular, and a fixed point P = (ri, f3), the pedal point. Then the pedal curve of the curve with respect to P is the parametrized curve obtained by associating to the parameter t the projection P(t) of P onto the tangent line at t. (Figure 1.2.) In practice, given the tangent line, you can write down the line perpendicular to it through P and find the intersection P(t) of the two lines. (Recall from elementary geometry that the lines perpendicular to a given line ax + by + c = 0 are the lines of the form -bx + ay + d = 0.) Here is a deceptively simple example giving rise to a number of interesting cubics.

1.2 Introductory Examples

7

Fig. 1.3. Pedals of a parabola

Example 1.8 Consider the standard parabola y2 = 4ax with a > 0, parametrized as x = at 2, y = 2at. We will show that the pedal curve with respect to the point P = (a,O) satisfies the equation of a cubic. The tangent line at t is x - ty + at 2 = 0, and the perpendicular line through P is tx + Y - at = O. The parametrized pedal is obtained by setting these expressions equal to zero, and then solving for x, y in terms of t, to obtain (a - a)t 2 t(a + at 2) X= y = 1 + t2 . 1 + t2 '

To obtain a polynomial satisfied by the points on the pedal we eliminate t instead, to obtain the cubic x(x - a)2 + y2(a - ct + x) = O. More precisely we have obtained a family of cubics, depending on ct. The zero set of some of the pedal curves are illustrated in Figure 1.3. The first thing to notice is that P always lies on the pedal, and is in some visual sense 'singular'. Thus for a < 0 the curve has a loop, which crosses itself at P, for ct = 0 the loop contracts down to a point, giving a 'cusp' at P, and for a > 0 the curve has an isolated point at P. Such 'singular' points play a very basic role in understanding the geometry of a curve, and will be studied in some detail in Chapter 6. The cubic x 3 + y2(x + a) = 0 obtained when ct = 0 is called the cissoid of Diocles after the classical Greek mathematician Diocles, who derived its equation when solving the problem of 'doubling the cube'; Newton discovered a mechanical construction for the cissoid, which we will meet in Section 1.3. a = 0 is not the only exceptional value of a. When a = a,

8

Real Algebraic Curves

Fig. 1.4. Bezier curve with control points bo, bI , b2 , b3

i.e. the pedal point is the focus F of the parabola, the equation factorizes as x{(x - a)2 + y2} = 0, whose zero set is simply the y-axis together with the point F. Another exceptional value is ti = -a, i.e. the pedal point is the point of intersection of the axis and directrix of the parabola: the pedal curve is then known as the right strophoid, and is characterized geometrically within the family by the fact that the tangents to the pedal curve at P are perpendicular. Cubic curves play important roles in numerous areas of mathematics and the physical sciences. An interesting class of naturally parametrized cubics arises in Computer Aided Design (CAD). The idea is as follows. One is given a plane 'curve', for instance part of an artist's visualization of an industrial product, and one seeks a useful mathematical model for this curve which can be handled on a computer. The underlying idea was developed in the late 1950s by two design engineers working for rival French car companies, namely Bezier (working for Renault) and de Casteljau (working for Citroen). A first crude step is to take a sequence of points b o, b 2 , ..., b 2n on the curve and interpolate a polynomially parametrized curve. However, this process is intrinsically unsatisfactory: as n increases, so the degrees of the polynomials increase, and the interpolating curve may oscillate wildly. The idea is to control this oscillation by specifying the tangent direction at each point. One way of doing this is to associate to each point b 2k another point b2k+l and stipulate that the tangent direction of the interpolating curve at b2k should be the direction of the line segment joining b2k , b2k +1. Let us illustrate this for the case of two points bo, b2 . In that case there are four

1.2 Introductory Examples: Exercises

9

control points bo, bl , b2, b3 to which is associated the Bezier curve defined by B(t) == (1 - t)3b o + 3t(1 - t)2b l + 3t2(1 - t)b 3 + t 3b2.

Note that B(O) == bo, B(l) == b2, B'(O) == 3(b l - bo), B'(l) == 3(b 2 - b3) so the curve passes through the points bo, b2 and has tangent directions hl - bo, b2 - b3 at those points. (Figure 1.4.) What is not obvious is that Bezier curves are algebraic. For the moment we will content ourselves with a numerical example. Later (Example 14.4) when we have a little more algebra available, we will be able to prove this in full generality. Example 1.9 In the above discussion take bo == (0,0), bi == (1/3,0), b2 == (2,2), b3 == (1,1/3) so B(t) == (t+t 2,t2 +t 3). Write x == t+t 2, Y == [2 + t 3. Note that y == tx. Eliminating t we see that each point (x, y) on the Bezier cubic lies on the cubic curve x 3 == y(x + y). Conversely, we will show that any point (x, y) satisfying the equation x 3 == y(x + y) necessarily has the form x == t + t 2, Y == t 2 + t 3 == tx for some real number t. Indeed if x =1= 0 define t by the relation y == tx; then, substituting for y we obtain x == t + t 2 , and hence y == tx == t 2 + t 3 . Finally, if x == 0 then y == 0 and we can choose either t == 0 or t == 1. Numerous examples of quartic curves arise in the physical sciences. For the moment we will content ourselves with a particularly interesting family of quartics. Example 1.10 The unit circle x 2 + y2 == 1 is parametrized as x == cos t, Y == sin t. We will find the pedal curve with respect to a point p == (ct,O) on the x-axis with Cl > O. The tangent line at tis (cost)x+(sint)y-1 = 0, and the perpendicular line through p is sin t( x - Cl) - (cos [) y = O. An equation for the pedal can be found by solving these relations for sin t, cos t, and then substituting in the identity cos 2 t + sin 2 t = O. The result is the quartic curve

known as a limacon. The zero set of the limacon (Figure 1.5) depends on the value of Cl. The point p always lies on the pedal, and is in some sense 'singular'. (Compare with the pedals of the parabola.) For Cl > 1 the curve has two loops, whilst for Cl < 1 it has just one. The intermediate case ct = 1 gives rise to a curve with a 'cusp', known as a cardioid.

10

Real Algebraic Curves

Fig. 1.5. The three forms of a limacon

Exercises

1.2.1

Show that the Bezier curve defined by the points bo = (-9,0), b i = (-27,-3), b2 = (-6,-2), b3 = (-24,-6) is given parametrically by x = 3(t 2 - 3), Y = t(t 2 - 3). By eliminating t from these relations, show that every point lies on the zero set of Tschirnhausen's cubic 27y 2 = x 2 (x + 9).

1.2.2

A parametrized curve is defined by x(t) = t 2 + t 3 , y(t) = t 3 + t4 . Find a polynomial f(x,y) of degree 4 such that f(x(t),y(t)) = 0 for all t. (It helps to observe that y = tx.) Conversely, show that for any point (x,y) with f(x,y) = 0 there exists a real number t with x = x(t), y = y(t). (Again, it helps to observe that you seek a t for which y = tx.) Show that there exists a cubic curve f(x,y) such that every point on the parametrized curve x( t) = 1 + t 2 , y(t) = t + t 3 satisfies the equation f(x(t), y(t)) = O. Conversely, show that for any point (x,y) with f(x,y) = 0, with one exception, there exists a real number t with x = x(t), y = y(t). Let a > 0, let C be the circle of radius a with centre (a,O) and let D be the line x = 2a. For each line L through the origin 0 (except the y-axis) let C L , D L denote the points where L meets C, D respectively, and let B L denote the point on the line segment joining 0, DL for which OB L = CLD L . Taking t to be the angle between L and the x-axis, find the coordinates of C L , DL in terms of t, and hence show that the locus of B L has the parametric form x(t) = 2asin2 t, y(t) = 2asin 2 ttant with -n12 < t < n12. Verify that every point on this parametrized curve lies on the zero set of the cubic x 3 = (2a - x)y2. Conversely, show that any

1.2.3

1.2.4

1.2 Introductory Examples: Exercises

1.2.5

1.2.6

1.2.7

point (x, y) on this cubic curve satisfies the relation 0 S x < 2a, and deduce that it has the form x = x(t), y = y(t) for some t with -n /2 < t < n /2. (The cubic in this question is the cissoid of Diocles, obtained via its original construction.) Show that there exists a cubic curve f(x,y) such that every point on the parametrized curve x(t) = sin 2t, y(t) = sin 2t tan t satisfies f(x(t),y(t)) = O. Conversely, show that for every point (x,y) with (x,y) = 0 there exists a t for which x = x(t), y = y(t). Let a > O. A parametrized curve is defined by x(t) = 2a tan t, y(t) = 2acos2 t where -n/2 < t < n/2. Show that there exists a cubic curve f(x, y) such that f(x(t), y(t)) = 0 for all parameters t. Let (x,y) be a point with f(x,y) = O. Show that 0 < y s 2a. Use this fact to show that there exists a parameter t for which x = x(t) and y = y(t). Sketch the zero set of f. (f is the curve known as Agnesi's versiera.) Let a > O. A parametrized curve is defined by the formulas _ 2a cos t 1 . , + slnt

x (t ) -

1.2.8

1.2.9

11

y(t)

= a(1 + sin t)

where -n/2 < t < n/2. Show that there exists a cubic curve f(x,y) such that f(x(t),y(t)) = 0 for all t. Let (x,y) be a point with f(x,y) = O. Show that 0 < y s 2a. Use this fact to show that there exists a t for which x = x(t) and y = y(t). Sketch the zero set of f. (f is identical to the curve in Exercise 1.2.6.) Let a > O. A parametrized curve is defined by x(t) = a cos t, y(t) = a sin t cos t. Show that there exists a quartic curve f(x, y) such that f(x(t),y(t)) = 0 for all values oft. Let (x,y) be a point in the plane with f(x,y) = O. Show that -a s x s a. Use this fact to show that there exists a real number t for which x = x(t) and y = y(t). Sketch the zero set of f. (f is the eight-curve.) Let a, b > O. Every line L through (0,0) in ~2, except the line x = 0, meets the line x = b in a unique point QL: and there are two points on L distance a from QL. K is the set of all such points. (At this point it helps to draw a sketch to understand the question.) Show that K is parametrized as x( t) = b + a cos t, y(t) = b tan t + a sin t with -n/2 < t < n/2 or n/2 < t < 3n/2, explaining what these intervals correspond to. (Take t to be the angle between the line L and the x-axis, and use a little trigonometry.) Find a quartic curve f(x,y) such that every point in K satisfies the equation f(x, y) = O. Conversely, show that

Real Algebraic Curves

12

any point (x,y) =1= (0,0) on this quartic has the form x == x(t), y == y(t) for some t in one of the given intervals. Show that (0,0) lies on K if and only if b s a. (f is the curve known as the 1.2.10

1.2.11

conchoid of Nicomedes.) Let a, b > O. A parametrized curve is defined by x(t) == a(l +cos t), y(t) == b sin t(l + cos t). Find a quartic curve f of the form f(x,y) == y2_¢(x) where ¢(x) is a quartic in x, with the property that f(x(t), y(t)) == 0 for all t. Let (x, y) be a point with f(x, y) == o. Show that 0 s x S 2a. Use this fact to show that there exists a t with x == x(t) and y == y(t). Give a rough sketch of the zero set

of f. Show that there exists a quartic curve f(x,y) such that every point on the three-leaved clover given by x(t) == cos 3t cos t, y(t) == cos 3t sin t satisfies f(x(t), y(t)) == o. Conversely, show that for every point (x,y) with f(x,y) == 0 there exists a t for which x

1.2.12

== x(t), y == y(t).

A parametrized curve in the real plane ]R2 is given by the following formulas, where a, b are positive real numbers, and t is such that cos t =1= 0, sin t =1= O. x(t)

a

== - ,

cost

y(t)

b

== - . - . SIn

t

By eliminating t from these relations, show that there exists a quartic curve f(x, y) such that f(x(t), y(t)) == 0 for all values of t. Let (x, y) be any point in the plane with f(x, y) == 0; show that either (x,y) == (0,0) or la/xl < 1 and Ib/YI < 1. Deduce that for any point (x, y) with f(x, y) == 0, with one exception, there exists a real number t for which x == x(t) and y == y(t). Sketch the zero set of the curve f(x, y).

1.3 Curves in Planar Kinematics

It is not possible (and probably not desirable) in a book of this length to describe the numerous areas of the physical sciences which contribute to the genesis of curve theory. A compromise is to mention one area of particular historical significance, namely planar kinematics. During the Industrial Revolution, mechanisms for converting rotary into linear motion were widely adopted in industrial and mining machinery, locomotives and metering devices. Such devices had to combine engineering simplicity with a high degree of accuracy, and the ability to operate at

1.3 Curves in Planar Kinematics

13

Fig. 1.6. Watt four bar linkage

speed for lengthy periods. For many purposes approximate linear motion is an acceptable substitute for exact linear motion. Perhaps the best known example is the Watt four bar linkage, discovered by the Scottish engineer James Watt in 1784. (Figure 1.6.) The device is made up of three smoothly jointed bars moving with one degree of freedom, the mid-point of the middle (or coupler) bar describing the Watt curve. The curve has a self-crossing with two 'branches' through it, one of which gives an excellent approximation to a straight line: it is a particularly good example of the 'flex' concept of Chapter 13. It was the detailed investigation of the fascinating curves traced by mechanisms such as the Watt four bar which gave rise to the (sadly neglected) body of knowledge known as planar kinematics. The underlying idea can be abstracted as follows. Suppose that a copy of the plane (the moving plane, in the language of that subject) moves with one degree of freedom (dof) over the given plane (the fixed plane). Any choice of tracing point P in the moving plane will then trace a trajectory curve on the fixed plane, yielding a 2-parameter family of trajectories, one for each point P. The idea is illustrated in Figure 1.7. It is worthwhile thinking a little bit about how such motions can

14

Real Algebraic Curves

fixed plane Fig. 1.7. Planar motion with one dof

be generated. The unconstrained moving plane moves with three dof, represented by one rotational dof, and two translational dof. In principle, the movement will be restricted to one dof when the moving plane is subject to two constraints. One way of constraining the motion is to insist that a given point in the moving plane must lie on a given curve in the fixed plane; or dually, one can insist that a given point in the fixed plane must lie on a given curve in the moving plane. Motions with one dof can be constructed by imposing two such constraints, of the same or different types. • Construction 1. Choose points B, C in the moving plane, and curves L, M in the fixed plane, and insist that B lies on L, and that C lies on

M. • Construction 2. In the moving plane take a point B and a curve M, in the fixed plane take a point C and a curve L, and insist that B lies on L, and C lies on M.

By making explicit choices of curves L, M one obtains a wide range of planar motions of considerable practical and theoretical interest. Here are some examples. Example 1.11 The simplest example of a planar motion generated according to Construction 1 is obtained when the two given curves in

1.3 Curves in Planar Kinematics

15

L

M

Fig. 1.8. The double slider motion

x

x

Fig. 1.9. The fixed and moving coordinate systems

the fixed plane are lines L, M, intersecting at a single point A, this is the double slider motion of engineering kinematics, illustrated in Figure 1.8. We will show that the trajectories of the double slider motion are conics. For simplicity we assume L, M are perpendicular. In the fixed plane we take the X-, y-axes to be the lines L, M, with A the origin, and in the moving plane we take the X -, Y -axes to be the line L' joining B, C and the line M' obtained by rotating L' through a right angle about C. (Figure 1.9.) Since B, C are fixed in the moving plane they have to remain a constant distance d > 0 apart. It is convenient to parametrize points on L, M as B = (ds,O), C = (0, dt) so the constant distance condition is s2 + t 2 = 1.

The coordinate systems in the fixed and moving planes are then related by x=sX+tY, y=sY+t(d-X). (*)

16

Real Algebraic Curves

Choose a fixed tracing point P = (X, Y) in the moving plane. Provided the matrix of coefficients is invertible, we can solve these equations for s, t in terms of x, y and then substitute in s2 + t 2 = 1 to obtain a polynomial of degree 2 in x, y defining the trajectory of P. In fact the matrix of coefficients has determinant F(X, Y) = X 2 + y 2 - dX, so is invertible if and only if F = 0, representing the circle in the moving plane centred at the mid-point of BC, and passing through B, C. Eliminating s, t from (*) via Cramer's Rule we obtain the conic in the (x,y)-plane given by ((d - X)x - Yy)2

+ (-Yx + Xy)2 = F 2.

More precisely, we have a family of conics, depending on the choice of tracing point P = (X, Y). The nature of the conic depends on this choice. For instance, the conic is an ellipse if and only if P does not lie on the circle F = O. (Exercise 5.2.8.) However, when P does lie on the circle F = 0 the equation degenerates to a perfect square (Y x - Xy)2 = 0, representing a 'repeated line', in fact the line through P and the origin. Incidentally, the double slider is the basis of the mechanical construction of an ellipse by the draughtsman's instrument known as the ellipsograph. It illustrates a significant general point in curve theory, namely that in naturally occurring families of curves we should expect degenerations to occur, corresponding to factorization of the defining polynomial. That is one reason why it is important to understand how polynomials factorize, a topic we pursue in Chapter 3.

Example 1.12 The simplest instance of a planar motion constructed according to Construction 2 is when both the curves L, M are straight lines. We will call it a Newton motion, since it was Newton who realized that the cissoid of Diocles could be constructed as a trajectory of such a motion. Write B' for the point on M with the property that the line BB' is perpendicular to M: and likewise write C' for the point on L with the property that the line CC' is perpendicular to L. For simplicity we suppose the tracing point P = (x, y) is the Inid-point of the line segment joining B, B', and we suppose that the distances from B to M, and from C to L, take the fixed value 2a > o. (Figure 1.10.) It will be no restriction to assume that C = (-a, 0) and thatL is the line x = a. Since B lies on L we can write B = (a, A) for some A. In order to obtain the equation of the curve traced by P, we will show that x, Y, A satisfy two polynomial relations, namely x 2 + y2 = Ay,

2x(a - x) = (2y - A)(Y - A).

17

1.3 Curves in Planar Kinematics

Y

L

x

Fig. 1.10. The Newton motion

To this end write P = (h, k); clearly h = 2x - a, k = 2y - A. By symmetry, the distance from B to C' coincides with the distance from B' to C, producing the first displayed relation. Also, the lines BB', B' C must be perpendicular; equivalently, the product of their slopes is -1; but BB' has slope (k - A)j(h - a), and Be' has slope (h + a)jk so the condition is h2 + k 2 = a2 + Ak, reducing to the second displayed relation when we write h = 2x - a, k = 2y - A. Eliminating A between the two displayed relations gives x(2a - x )y2 = x 4 . The possibility x = 0 only gives rise to the case when P is the origin, so we conclude that P must lie on the cubic curve (2a - x)y2 = x 3 which is indeed a cissoid of Diocles when we replace x in the formula of Example 1.8 by -x. The cissoid can be physically traced by taking two sheets of wood (the fixed and moving planes) on each of which is a groove (the lines Land M) and a small fixed peg (the points C and B) designed to slide in the groove on the other sheet. The distances from peg to groove must be the same. The sheet with groove L and peg C is fixed on a work surface; the second sheet can then slide with the peg B in the groove L, and the peg C in the groove M. The cissoid is traced by the point P halfway between Band M. More complex trajectories, of considerable geometric interest, can be generated via both constructions by allowing L, M to be more compli-

18

Real Algebraic Curves

Fig. 1.11. Four bar linkage coupler curve

cated curves. In the next (and final) example B, C move along circles, and the trajectories turn out to be sextic curves. Example 1.13 In mechanical engineering, the general four bar linkage is obtained by taking a quadrilateral ABCD hinged at the points A, B, C, D with sides AB, BC, CD, DA of fixed lengths. Fixing one of the sides (AD for instance) we see that the point B moves round a circle centred at A, the point C moves round a circle centred at D, and the coupler bar BC moves with one dof. (The reader is urged to construct a linkage using cardboard pinned to a flat surface.) A tracing point P in the moving plane carried by BC then describes a trajectory, known as a coupler curve; given the simplicity of the construction, the complexity of this curve can be quite surprising. This example includes the Watt curve, which is a trajectory arising from a special type of four bar, with tracing point the mid-point of the coupler bar. A typical example is illustrated in Figure 1.11.

One can pursue the line of thought underlying this section much further. There is a fascinating zoo of 'mechanisms', mechanical linkages moving with one dof, which can generate trajectories of seemingly infinite complexity. Indeed there is a remarkable result (proved by a London solicitor Kempe in 1876) which says that any real algebraic curve can be mechanically generated. Very little is known about such

1.3 Curves in Planar Kinematics

19

curves, and much remains to be discovered. It is the starting point for the much wider study of spatial kinematics, likely to be of considerable practical relevance as robotics assumes an ever increasing role in our lives.

2 General Ground Fields

The purpose of this chapter is to widen the scope of our enquiry by moving from real algebraic curves defined by finite sums f(x,y)

=

2:

a ijX

i

yj

i,j

with coefficients aij in the real number field lR, to curves for which the coefficients lie in an arbitrary 'ground field' IK. There are two compelling reasons for such an extension. The first is that it will lead to a better understanding of the geometry of curves, even in the real case. And the second is that the powerful visual ideas arising from real algebraic curves can be applied to other areas of mathematics (such as number theory) to considerable effect.

2.1 Two Motivating Examples

In numerous situations one needs to count the intersections of two algebraic curves. This raises a fundamental question. How many points of intersection are there? Example 2.1 How many times does the unit circle f(x,y) = x 2 + y2_ 1 intersect the line y = c? For a fixed value of the constant c, the intersections are given by x 2 = 1 - c2 . The solutions of this equation depend critically on the value of c. For -1 < c < 1 there are two real solutions, for c = ±1 there is just one real solution, and for c < -1 and c > 1 there are none. (Figure 2.1.) The answer admits a more natural phrasing were we to allow the possibility of x, y assuming complex values. In that case we would be able to say that for c =1= ±1 there are two points of intersection, and that for c = ± 1 there is just one. Better still, we could 20

2.1 Two Motivating Examples

leI1

Fig. 2.1. Horizontal line meeting a circle

say that there are always two points of intersection, which coincide when c = ±1! Such examples lead us in a significant direction. Instead of restricting our attention to points (x, y) in the real affine plane lR 2 satisfying an equation f(x, y) = 0 we might broaden our viewpoint to consider points (x, y) in the set C 2 = {(x, y) : x, y E C} with this property. Thus we could define a 'complex' algebraic curve in exactly the same way that we defined a 'real' algebraic curve in Section 1.1, save that the coefficients aij in the defining polynomial f would be allowed to be complex numbers. In the language of algebra, we are replacing the real number field lR by the complex number field C. The complex environment is both natural and fruitful, lending considerable insight into real phenomena. For instance, it will give us a simple geometric insight into the concept of a centre for a circle. The next example opens up a rather different direction in which we might proceed, namely thinking about problems in number theory in the context of curves. Example 2.2 A classical problem of Greek mathematics was to find all right-angled triangles with integer sides, i.e. all positive integers X, Y, Z with X 2 + y 2 = Z2. Equivalently one seeks positive rational solutions x = X /Z, y = Y /Z of the equation x 2 + y2 = 1. In other words, we seek all points (x,y) in the set Q2 = {(x,y) : x,y E Q} with x 2 + y2 = 1. (In Example 8.8 we will obtain a complete solution to this problem, via the idea of 'rational' parametrization.) This example suggests it might be profitable to proceed by analogy and define a 'curve' in Q2 just as we did in the real case, save that the coefficients aij in the defining polynomial f would be allowed to

22

General Ground Fields

be rational numbers. This time we would be replacing the real number field IR by the rational number field Q. On this basis, there is nothing to stop one going all the way and replacing the real field IR by an abstract 'ground field' IK. The advantage of such a move is that one widens the scope of the subject to include interesting problems in number theory, such as that in the above example. Do not worry if you have not met the idea of an abstract number field before; we will give a formal definition in the next section. In any case, we will not work at this level of generality. The convention in this book is that the underlying ground field is either the real field IR, or the complex field C. Once in a while (just for the fun of it) we may allow IK to be some other field, but at each such juncture we will explain what the field is.

Exercises 2.1.1

A piriform is a quartic curve in IR2 defined by a formula of the form a4 y 2 = b2x 3 (2a - x) where a, b are positive real numbers. Determine the number of real points of intersection of the piriform with the circle (x - a)2 + y2 = a2 in terms of a, b.

2.2 Groups, Rings and Fields In this section we present a very brief review of the basic algebraic concepts underlying the material treated in this book. (Virtually any elementary algebra text will tell you much more.) Three algebraic structures playa significant role, namely the ideas of group, domain and field. It is natural to consider them in turn. The most basic structure is that of a 'group'. Examples of groups appear at several points in the development. For instance, the 'affine' maps' of Chapter 4 form a group under the operation of composition; and we will see in Chapter 17 that certain cubic curves have a natural group structure, the source of much interesting geometry. Here is a brief reminder of the definitions. A group is a set X, together with an 'operation' ., which satisfies the following group axioms (Gl), (G2), (G3), (G4). • (01) . is a binary operation on X, i.e. there is a rule whereby to each pair of elements x, y in X we associate another element x . y in X. (Closure.) • (02) For any elements x, y, z in X we have x . (y . z) = (x . y) . z. (Associative Law.)

23

2.2 Groups, Rings and Fields

• (03) There exists an element 1 in X (the identity) with the property that for any x in X we have 1 . x = x = x· 1. (Existence of an Identity.) • (04) For any element x in X there exists an element x-I in X with the property that x . x-I = 1 = X-I. x. (Existence of Inverses.) A binary operation . on X is commutative when x . y = y . x for all choices of x, y in X. A group X whose binary operation· is commutative is said to be Abelian. It is a convention in group theory to use 'additive' notation when dealing with Abelian groups; thus the operation is written +, the identity is written 0, and the inverse of x is written -x. (We will use this notation when dealing with the Abelian group structure on cubic curves.) For an element x in X, and a positive integer n we define x n = x· x· .... x (n times); additively, we write nx = x + x + ... + x. An element x is said to be of finite order when there exists a positive integer n with x n = 1 (additively, with nx = 0), and in that case the least such n is the order of x. The most familiar examples of groups are the sets Z of integers, Q of rational numbers, JR of real numbers, and CC of complex numbers, all with the usual definitions of addition +, and with identity element O. Likewise, the sets Q*, ~*, CC* of non-zero elements in Q, ~, CC are Abelian groups under the usual definitions of multiplication ., with identity element 1. A more exotic example is the group Zp of residue classes of integers modulo p, obtained as follows. Example 2.3 Let p be a fixed positive integer, and let Z be the set of integers. Recall that two integers a, b are said to be congruent modulo p, and we write a == b mod p, when a - b is divisible by p. This defines an equivalence relation partitioning Z into disjoint equivalence classes, known as residue classes of integers. The residue class a containing a comprises all integers congruent to a mod p: thus there are p residue classes 0, I, ... , (p - 1) modulo p, forming the set Zp of all residue classes modulo p. Addition of residue classes is defined by a + b = a + b. It should be clear from the definitions that Zp is an Abelian group under the operation + with identity element 0, and with inverses defined by -a = (-a). Example 2.4 Write Z; for the set of non-zero elements in Zp. Here we need to proceed more carefully. Multiplication of residue classes is defined is an Abelian group by a· b = a . b. We claim that provided p is prime, under multiplication with identity element I. It will not be too confusing

Z;

24

General Ground Fields

simply to write a for the residue class a. Note first that if a . b = 0 then either a = 0 or b = 0, for if a . b = 0 then p is a factor of ab, so p is a factor of a or a factor of b (that is the point where we use the assumption that p is prime) and hence a = 0 or b = O. It follows that is closed under multiplication. It remains to establish the existence of inverses. We have to show that if a =1= 0 then there exists an element b such that a . b = 1. To this end, note that the (p - 1) elements a . 1, ... , a . (p - 1) are non-zero and distinct: for if we had an equality a . j = a . k with j =1= k then a . (j - k) = 0, and hence j = k, a contradiction. However, there are exactly (p - 1) elements in so they must be a . 1, ... , a . (p - 1). In particular, the element 1 must be in the sequence, i.e. a . b = 1 for some

Z;

Z;,

b =1=

o.

For the purposes of this book a commutative ring will mean a set R with distinct elements 0, 1 and commutative operations + (addition) and . (multiplication) satisfying the following 'axioms', of which (3) is the Distributive Law. (1) (2) (3)

R is a group under the operation + with identity O. Multiplication' is associative with identity 1. x . (y + z) = x . y + x . z for all x, y, z in R.

A commutative ring R is a domain when in addition we have no divisors of zero, i.e. for any choices of a, b the relation ab = 0 implies that a = 0 or b = O. Cancellation is possible in domains, meaning that if ab = ac and a =1= 0 then b = c; just observe that ab = ac is equivalent to a(b - c) = O. An element u in R is a unit when it has a multiplicative inverse, i.e. an element u- 1 (necessarily unique) with u'u- 1 = u-1·u = 1. A commutative ring R is a field when every element a =1= 0 has a multiplicative inverse; thus a field is automatically a domain. Important examples of domains for us are Z, (Q, IR. and C, all with the usual definitions of addition and multiplication; of these (Q, IR. and C are fields. But for fun purposes we will add the set Zp of residue classes of integers modulo a prime number p. The first case of interest is then the field Z3, comprising the residue classes 0, 1, 2 with addition and multiplication tables as below.

+ o 1 2

0

1

2

0 1 2

1 2 0

2 0 1

012 000 101 202

0 2 1

2.3 General Affine Planes and Curves

25

The number field Zp is distinguished from the number fields Q, lR and C by the fact that it has 'finite characteristic'. Generally, a domain lIJ) has finite characteristic when there exists a positive integer p for which o = I + I + ... + I (p times); and in that case the least positive integer p for which this holds is the characteristic of llJ). If no such integer exists then lIJ) is said to have characteristic zero. Thus Zp has characteristic p, whilst Q, lR and C have characteristic zero.

Example 2.5 The process whereby the field of rationals Q is obtained from the domain Z of integers by forming 'fractions' can be extended to any domain lIJ). Consider the set of pairs (a, b) with a, b E llJ) and b =1= o. On this set we introduce an equivalence relation '" by agreeing that (a, b) '" (c, d) if and only if ad = bc. Equivalence classes are called fractions, and we denote the class containing the pair (a,b) by a/b. Addition + and multiplication . of fractions are then defined by a

c

b+ d =

a

c

b.d =

ac bd·

With these definitions it is easily verified that the fractions form a field, the field offractions over the domain lIJ). And by identifying the element a E llJ) with the fraction all, we identify llJ) with a subset of the field of fractions.

2.3 General Affine Planes and Curves At this point it may be helpful to embark on a little harmless abstraction, just to clarify the foundations of what we are doing. Consider a set X, whose elements we will call points, together with a collection of nonempty subsets of X called lines. We say that a point p lies on a line I, or that I passes through p, when p is an element of the subset 1. We refer to X as a plane when points and lines satisfy the following axioms. • There are at least three points which do not lie on anyone line. • Through any two points p, q there passes exactly one line 1. Let X be a plane, let I be a line in X, and let p be a point in X. Two lines are said to be parallel when they are disjoint subsets of X. In principle we have three posssibilities. (i) There are no lines through p parallel to 1. (ii) There is exactly one line through p parallel to 1. (iii) There is more than one line through p parallel to I.

26

General Ground Fields

The most familiar situation is when X is an affine plane, meaning that (ii) holds for all choices of line 1, and point p not on 1. Later in this book we will meet projective planes, where (i) holds for all choices of line 1, and point p not on 1: in other words, a projective plane is one in which any two lines intersect in at least one point. The next example constructs a wide range of affine planes, sufficient for all our purposes. (The reader is warned that not all affine planes arise in this way.) Example 2.6 Let l[{ be a field, and let l[{2 = {(x,y) : x,y E l[{}. By a line in l[{2 we mean a subset of the form {(x,y) E l[{2 : ax+by+c = O} where a, b, c are elements of l[{ with at least one of a, b =1= 0. With this definition l[{2 is a plane. Clearly, there is no line through the three points (0, 0), (1,0), (0, 1): and the argument in Example 1.1, establishing that there is a unique line through any two distinct points in ~2, works over any field. Indeed l[{2 is an affine plane; the argument in Example 1.3 also works over any field. With this concept of 'line', we call l[{2 the affine plane over the ground field l[{. The plane ~2 is known as the real affine plane, and C 2 as the complex affine plane.

The main point to make is that it is only the affine plane structure of which plays a role in this book. For instance, the metric structure on the real affine plane ~2 given by the concepts of distance and angle is irrelevant. (Very occasionally we use the metric structure on ~2, but only as a convenient device to define interesting examples of real algebraic curves.) Here is a rather odd example of an affine plane. Although it is really a 'fun' example, we will meet it later in an unexpected context, namely the geometry of cubic curves.

l[{2

Example 2.7 Consider the plane l[{2, where l[{ is the finite field Z,3 with elements 0, 1, 2. There are nine points in l[{2, namely (0,0), (0, 1), (0,2), (1,0), (1,1), (1,2), (2,0), (2,1) and (2,2). It is convenient to picture them as the nine points in ~2 with the same coordinates. (Figure 2.2.) There are twelve lines: three 'vertical' lines x = 0, x = 1, x = 2, three 'horizontal' lines y = 0, y = 1, y = 2, two 'diagonal' lines y = x, y = -x + 2, and four more y = x + 1, y = -x, y = x-I, y = -x + 1. Thus for instance the zero set of the line y = x + 1 comprises the points (0, 1), (1,2) and (2,0).

We can define 'curves' in general affine planes l[{2 just as we did in the real affine plane ~2. A polynomial f(x, y) in the variables x, y over the

2.3 General Affine Planes and Curves

Fig. 2.2. The affine plane over

27

Z,3

field OC is defined to be a formula of the shape f(x,y)

=

L aijXiyj i,j

where the sum is finite and the coefficients aij lie in oc. An algebraic curve over OC is a non-zero polynomial f(x, y) over OC, up to multiplication by a non-zero scalar. Henceforth, we will abbreviate the term 'algebraic curve' to 'curve'. The degree of a curve is the common degree of its defining polynomials. Curves of degree 1, 2, 3, 4, ... are called lines, conics, cubics, quartics, .... Roughly speaking, the higher the degree of a curve the more complicated it may become, so there is a lot to be said for understanding curves of very low degree in some detail. That is part of our underlying philosophy. Thus in Chapter 5 we will present a thorough discussion of conics. And cubics receive a lot of attention, culminating in the beautiful connexion between cubic curves and groups in Chapter 17.

General Ground Fields

28 y

y

x

x

Fig. 2.3. Agnesi's versiera and the Serpentine

2.4 Zero Sets of Algebraic Curves As in Section 1.1, we define the zero set of a polynomial f(x,y) over the field JK to be the set Vf

= {(x,y)

E

JK2 : f(x,y) = O}.

The zero set is unchanged when we multiply f by a non-zero scalar, so is defined not just for polynomials, but for the associated curves. Consider first the case of the real field ffi.. In Chapter 1, we sketched a number of zero sets of real algebraic curves. Generally speaking, it can be quite difficult to do this by hand, indeed there was a time (not so long ago) when mathematical texts were devoted to this art. However, life has moved on; in principle zero sets can be traced by computer within a fraction of a second. All the same, there is much to be said for being able to sketch simple examples. Curves which can be put in the form y = ¢(x) for some (not necessarily polynomial) function ¢(x) are an obvious starting point. Example 2.8 The zero set of a curve x 2 y = 4a 2 (2a - y) with a > 0 (this is Agnesi's versiera of Exercise 1.2.6) is rather easy to sketch, because it is the graph of the function y = 8a 3 j(x 2 + 4a 2 ) depicted in Figure 2.3. Likewise the zero set of the serpentine x 2 y + a2 y - b2 x with a, b > 0 is the graph of the function y = b2 xj(x 2 + a2 ). The point of the next example is that it provides you with another useful class of curves to which elementary sketching techniques apply.

2.4 Zero Sets of Algebraic Curves

29

Example 2.9 Consider curves of the form y2 = 4J(x), with 4J(x) a (not necessarily polynomial) function. The method is first to sketch the graph of 4J(x), and then to 'take square roots'. A concrete example is provided by the family of curves y2 = x 3 - 3x + A, where A is a real parameter. Here 4J(x) = x 3 - 3x + A. Think of this as the function y = x 3 - 3x translated upwards (or downwards) by A. The polynomial y = x 3 - 3x is a cubic with three real roots having a local maximum at x = -1 with value y = 2, and a local minimum at x = 1 with value y = -2. Figure 2.4 shows how the graph of 4J(x) varies as A varies. In each picture we now 'take square roots', to obtain the series of pictures of the curve y2 = 4J( x) as A varies. We will return to this class of examples later. One of the psychological difficulties of working over general ground fields (as opposed to the real field) is that there may be no way of visualizing the zero set. However, one can soon adjust to that. The main point to make is that the analogy with the real case is a powerful tool for understanding a diversity of mathematical problems. Example 2.10 We will determine the zero set of the conic x 2 - y2 = 1, over the field Z3. There are only three possible values for y, namely y = 0, y = 1, y = 2. When y = 0 we have x 2 = 1, and hence x = 1 or x = 2, and when y = 1, y = 2 we have x 2 = 2, with no solutions. Thus the zero set comprises the points (1,0), (2,0). In this book we adopt a rather geometric viewpoint, by which we mean that our intuitions are based on the visual properties of zero sets for real algebraic curves. However, we have to bear in mind that the underlying object is the polynomial since, although the curve determines the zero set, the converse may not hold. Here is a salutary example. Example 2.11 The conics x 2 + y2 + 1, x 2 + y2 + 2 in }R2 are distinct (clearly, neither is a scalar multiple of the other) but have the same zero set, namely the empty set. The trouble here is that we are working over the real field. Over the complex field the zero sets are distinct; for instance, the point (i,O) lies on the first curve but not on the second. A different phenomenon is illustrated by the cubic curves x 2y, xy2 which are distinct, but have identical zero sets; this time the trouble is that the equations factorize. In Chapter 14, we will return to the question of the relation between curves and their zero sets, and show that in the complex case the zero set determines the curve, provided the equation does not factorize. Until then

30

General Ground Fields

A< -2

A= -2

-2 < A < 2

A=2

Fig. 2.4. The curves y2 = x 3

-

3x + A

the reader is advised to heed the warning given in Chapter 1, namely that one needs to maintain a very clear distinction between the two concepts. Example 2.11 makes the point that real algebraic curves may have empty zero sets. By contrast, zero sets of complex algebraic curves always have lots of points!

31

2.4 Zero Sets of Algebraic Curves

Lemma 2.1 The zero set of any curve f of degree d ~ 1 in C 2 is infinite. Proof The idea is to show that infinitely many lines Y = constant meet the curve at least once. The proof depends on the fact that any polynomial d . ¢(x) = 2:i=O ai x1 of degree d ~ 1 has at least one zero, i.e. a complex number x which satisfies the equation ¢(x) = o. (That is the Fundamental Theorem of Algebra: see Lemma 3.7.) Write f(x,y) = 2:~=Oai(y)xi where the coefficients ai(Y) are polynomials in y. We can suppose at least one polynomial ai(Y) with i ~ 1 is non-zero; otherwise f(x, y) = ao(Y), and the zero set is a union of lines y = constant, so infinite. For fixed y the equation f(x, y) = 0 is polynomial in x with complex coefficients, and has a zero x, provided it has degree ~ 1. That only fails when o = al (y) = ... = ad(Y). But a non-zero polynomial has at most finitely many zeros, so there are only finitely many 'exceptional' values Y for which these conditions can hold. There are therefore infinitely many Y for which the conditions fail, and hence for which the equation f(x, y) = 0 has at least one solution (x, y). D

Example 2.12 Consider the conic f(x, y) = xy-1 in C 2 . With the notation of the above lemma ao(Y) = -1, al(Y) = y. The only 'exceptional' value of y is given by 0 = al (y) = y: indeed, the line y = 0 does not meet the zero set, whereas any line y = c with c =1= 0 does.

It is interesting to take the very simplest algebraic curves in C2 and determine their zero sets explicitly. Example 2.13 The zero set of a line ax + by + c in C 2 is a real plane! Identifying a point x = Xl + iX2 in C with a point (Xl, X2) in ffi.2, and likewise a point y = Yl + iY2 in C with a point (Yl, Y2) in ffi.2, we identify a point (x,y) in C 2 with a point (Xl,X2,Yl,Y2) in ffi.4. The single complex linear equation ax + by + c = 0 then represents two real linear equations in Xl, X2, Yl, Y2; indeed, if we write a = al + ia2, b = b l + ib 2, C = Cl + iC2 and equate real and imaginary parts we obtain alXl -

a2 x l

a2 X2 + blYl - b2Y2

-Cl

+ alx2 + b2Yl + b 1Y2

-C2·

representing two linear equations in the four unknowns The matrix of this system is -bb 2 1

)

.

Xl,

X2, Yl, Y2.

General Ground Fields

32

Suppose the matrix of coefficients has rank < 2. Then (by linear algebra) all the 2 x 2 minors vanish. In particular, ai + a~ = 0 and bi + b~ = 0, so a1 = a2 = 0, b 1 = b2 = O. But that means a = b = 0, which is impossible, as one of a, b must be non-zero. It follows that the matrix has rank two, and (by linear algebra again) the solution space of the equations is an affine plane in ~4. This is the first instance of a general principle, namely that curves in ee 2 can be considered as real surfaces in ]R4; in the single complex relation f(x,y) = 0 defining an algebraic curve in C 2 we can take real and imaginary parts to produce two polynomials in the variables Xl, X2, Y1, Y2 defining (in principle) a surface in ~4.

Exercises 2.4.1

Use the sketching technique of Example 2.9 to sketch the zero sets of the following real algebraic curves. (i) (ii) (iii) (iv)

2.4.2

2.4.3 2.4.4 2.4.5

2.4.6

f = y2 - x 3 f = y2 + x 2 - x 3 f = y2 - x 2 - x 3 f = y2 + x 2 - x 4

(v) (vi) (vii) (viii)

f = y2 - x 2 + x 4 f = y2 - x 3 + x 4 f = y2 + x 3 - x 4 f = x 2 + y2 - x 2y2.

Sketch the zero set of the real algebraic curve given by the formula f = x(x 2 + y2) - (1 - x)3. Let p(x) be a polynomial over the field JK. Show that the graph of p(x) in OC2 is the zero set of an algebraic curve. Find the zero sets of the conics fa = x 2 + y2, f1 = x 2 + y2 + 1 and f2 = x 2 + y2 + 2 over the field Z3. Find the zero set of the line 2x + 3y + lover the field Zs. Express the line in the form y = ax + /3, and hence check your answer. Let f be a curve of odd degree d in ~2 with f(O,O) =1= O. Show that there are at most finitely many real numbers A for which f fails to intersect the line y = AX, and deduce that the zero set of f is infinite. (You may assume that a real polynomial of odd degree has at least one zero.)

3 Polynomial Algebra

In this chapter, we lay some algebraic foundations for a systematic study of curves, specifically the question of factorizing polynomials in one or more variables. Later, we will return to more special topics in algebra, but till then this material will serve all our needs. We start by discussing the abstract concept of factorization in an arbitrary domain. In the succeeding section, we recall the elementary algebra associated to polynomials in a single variable; that provides a model for the algebra of polynomials in several variables, and is anyway of particular relevance to the geometry of curves. We devote a separate section to the special polynomials known as 'forms', crucial to understanding 'tangents' and 'projective' curves. Finally, we explain how some basic calculus ideas can be introduced for polynomials over arbitrary domains.

3.1 Factorization in Domains

Much of this book will centre around the concept of 'factorizing' polynomials. The domain Z of integers provides the model for the ideas, but we phrase the definitions for any domain ]D). Given elements a, b E ]D) we say that a is a factor of b, or that b is divisible by a, written alb, when there exists an element c E IIJ) with b = ac. (Note that according to this definition the zero element 0 is divisible by any element in IIJ).) A factor is said to be trivial when it is a unit, otherwise it is proper. The associates of an element a are the elements of the form au with u a unit. (Thus in Z the units are ±1.) There are two key ideas in discussing factorization: • An element p E IIJ) is irreducible when p =1= 0, p is not a unit, and p = ab means that one of a, b is a unit. 33

Polynomial Algebra

34

• An element p is prime when p either pia or plb.

=1=

0, p is not a unit, and plab means that

A prime element is necessarily irreducible, though in general irreducibles may fail to be prime. (Exercise 3.1.1.) A unique factorization domain (UFD) is a domain IIJ) with the following properties: • Any element a E JD) can be written as a finite product a = al ... ap where the factors aI, ... , a p are irreducible. • The factorization into irreducibles is unique, in the sense that if a = at ... ap , a = a~ ... a~ are two factorizations into finitely many irreducibles, then p = q, and each ai is associate to exactly one aj. In a unique factorization domain the concepts of prime and irreducible coincide. (Exercise 3.1.1.) The most familiar example is the domain Z of integers where these concepts yield the 'prime numbers' of elementary number theory. One of the central facts we will use in this book is that polynomial domains (to be introduced in the succeeding sections) are likewise unique factorization domains; the next two abstract lemmas will pinpoint the key ingredient in this result. The first provides a sufficient condition for the existence of factorizations into finitely many irreducible elements. First a definition. A degree function on a domain [)) is a function d on IIJ) with non-negative integer values, such that d(a) < d(ab), when b is not a unit. The model for a degree function is the absolute value function on the domain Z of integers. Lemma 3.1 Let JD) be a domain on which there is a degree function. Then any element I can be written as a product I = I I ... Is of irreducibles. Proof If I is irreducible, we are done. Otherwise write f = gh where g, h are proper factors, so d(g) < d(gh) = d(f), d(h) < d(gh) = d(f). Now repeat this process to g and to h; if either fails to be irreducible we factor it into proper factors on which d takes strictly smaller values. The process can be repeated at most finitely many times, since at each stage the degree function drops by at least one. The result follows. D

Here is an equally simple result concerning the uniqueness of polynomial factorizations into prime elements. Lemma 3.2 Let a unit, and let f

JD)

=

°

be a domain, let f =1= be an element which is not fl . .. f p = gi ... gq be factorizations of f into primes.

3.2 Polynomials in One Variable

35

Then p = q, each of the I's is an associate of one of the g's, and conversely each of the g's is an associate of one of the I's. Proof Since It is prime and divides gt ... gq it must be a factor of some gj. We can suppose the g's numbered so that j = 1. Since gt is prime that means It, gt are associates, and gt = ult for some unit u =1= o. Substituting for gt in It ... I p = gt ... gq, and cancelling It, we obtain a relation 12 ... I p = ug2 ... gq. Repeating this argument p times we obtain a relation 1 = gq_p ... gq. That implies that p :::; q since the g's are not

units. Likewise we establish that q :::; p and hence p = q. In the process we have established that each I is an associate of some g, and conversely. D Combining these two results, we obtain the following sufficient condition for a domain to have unique factorization. Lemma 3.3 Let ]I)) be a domain. Assume that ]I)) has a degree function, and that every irreducible is prime. Then ]I)) is a unique factorization domain. In particular, any element I =1= 0 can be written uniquely (up to order and units) in the form I = cI~l .. . I~s where c is a unit, where It, ... ,Is are irreducible, and for i =1= j no Ii is a factor of Ij.

Exercises 3.1.1

Let]I)) be a domain. Show that a prime element in ]I)) is necessarily irreducible. And show that if ]I)) is a unique factorization domain then conversely any irreducible element is prime.

3.2 Polynomials in One Variable It is worth recalling the generalities of factorization for polynomials in a single variable x over a domain ]I)). The case when ]I)) is the domain of real numbers is probably familiar ground for the reader. All we are doing in this section is simultaneously to recall school algebra, and phrase it in more general terms, for reasons which will appear later when we progress to polynomials in several variables. A monomial in x is defined to be a power x k : and a polynomial in x over the domain ]I)) is defined to be a linear combination of monomials in x with coefficients in llJ), so is given by a formula I(x) = ao + atX + ... + adxd, where the coefficients ai E ]I)). The degree of a monomial x k is defined to be k, and that of a

Polynomial Algebra

36

polynomial f(x) is the maximal degree of the monomials x k for which the associated coefficient ak =1= o. Polynomials of the form f(x) = a with a E JI)) are constant with value a. We can add and multiply polynomials in an 'obvious' way. Given two polynomials

we define their sum f given by {

+ g,

and their product f.g to be the polynomials

(f + g)(x) (f.g)(x)

+ CIX + C2 x2 + . + d 1x + d2x 2 + . dl = aOb l + ... + alb o. With these definitions =

Co

=

do

where Ck = ak + bk and of addition and multiplication, it is easily checked that the polynomials in x over a domain JI)) form another domain JI))[x]. The zero element is the constant polynomial with value 0, and the identity element is the constant polynomial with value 1. The units in llJ)[x] are the constant polynomials with value a unit in llJ). In the case when llJ) is a field, the units are the constant polynomials with non-zero values. It is easily checked that the degree of a polynomial is additive, in the sense that for polynomials fl, ... , fp the degree of the product f = fl ... fp is given by degf

= degfl + ... + degfp·

Note that the concept of 'irreducibility' depends on the domain llJ); for instance, the polynomial f(x) = x 2 + 1 is irreducible over the real field, but reducible over the complex field since x 2 + 1 = (x - i)(x + i). The starting point for studying polynomials in one variable is the following result from elementary algebra. d

.

Lemma 3.4 Let f(x) = Li=O aixl be a non-constant polynomial of degree d over a domain llJ), and let c be a scalar. There exists a polynomial q(x) (the quotient) of degree (d - 1), and a scalar r (the remainder) with f(x) = (x - c)q(x) + r. (The Remainder Theorem.) Proof It suffices to show that each monomial Xi can be written in the form Xi = (x - C)qi(X) + ri with q(x) a polynomial of degree (i - 1), and ri a scalar, since then f(x)

=

L

ai xi

=

L ai{(x -

C)qi(X)

+ ri} = (x -

c)q(x)

+r

where q(x) = L aiqi(x) has degree (d - 1), and r = L airi is a scalar. It

3.2 Polynomials in One Variable remains to observe that we can take ri =ci.

qi(X)

= x i-

I

+ x i- 2 C + ... + ci - I

37

and 0

We will use the Remainder Theorem in the special case when c is a zero of f(x), meaning that f(c) = 0; alternatively, we will say that c is a root of the equation f(x) = O. Lemma 3.5 Let c be a zero of the polynomial f(x) over the domain IIJ). Then (x - c) is a factor of f(x), i.e. we can write f(x) = (x - c)q(x) for some polynomial q(x) over IIJ). (The Factor Theorem.) Proof Taking x = c in the Remainder Theorem we see that the remainder r = f(c) = 0, since c is assumed to be a zero. Thus f(x) = (x - c)q(x).

D Lemma 3.6 Any non-constant polynomial f(x) of degree d over a domain II:» has at most d distinct zeros. Proof Let CI, ... , Cd be distinct zeros of f(x). Then the Factor Theorem tells us that f(x) = (x - CI)g(X) for some polynomial g(x) of degree (d - 1). Since C2 is a zero of f(x) we have 0 = f(C2) = (C2 - CI)g(C2), and hence C2 is a zero of g(x). (This uses the fact that there are no divisors of zero in a domain IIJ).) Using the Factor Theorem again we get f(x) = (x - CI)(X - c2)h(x) for some polynomial h(x) of degree (d - 2). Continuing in this way we eventually obtain f(x) = c(x - CI)··· (x - Cd) for some scalar c =!= O. It is then immediate that any zero of f(x) must be one of CI, ... , Cd. D Exercise 3.2.2 shows that Lemma 3.6 fails for a polynomial over a general commutative ring. We can say more about factorization of polynomials in one variable for special types of domain. A classic result from complex analysis is Lemma 3.7 Every non-constant polynomial f(x) over the complex field has at least one zero. (The Fundamental Theorem of Algebra.) Generally speaking, a field 1[( is said to be algebraically closed when any non-constant polynomial f(x) over lK has at least one zero in lK. (So the above result can be paraphrased by saying that the complex field C is algebraically closed.) For such a field we obtain a factorization f(x) = c(x - PI)· .. (x - Pd) where the zeros PI, ... , Pd are not necessarily

Polynomial Algebra

38

distinct, and c =1= O. Let )'1, ... , Ys be the distinct zeros of f occurring respectively rl, ... , rs times. (rl, ... , rs are called the multiplicities of the zeros.) Then we arrive at the following result, which is a special case of the Unique Factorization Theorem for general polynomials, to be discussed in the next section. Lemma 3.8 Any non-constant polynomial f(x) over the complex field can be written uniquely (up to order) in the following form, for some complex number c =1= 0, and distinct complex numbers Yl, ... , Ys. f(x)

=

c(x - YlYl ... (x - Ys)r s •

Example 3.1 Let n ~ 1 be an integer. Then the polynomial f(x) = x n - l has exactly n distinct zeros in C, namely 1, 0), 0)2, ... , O)n-l where 2ni / n . We refer to these zeros as the complex nth roots of unity. 0) = e

Exercises 3.2.1 3.2.2

3.2.3

Show that the units in the domain ]IJ)[x] are precisely the constant polynomials with value a unit in ]IJ). Verify that the quadratic polynomial f(x) = x 2 over 2 9 has three distinct zeros; also, verify that the quadratic polynomial g(x) = 2x(x - 1) over 2 4 has four distinct zeros. Show that an algebraically closed field OC has infinitely many elements. (Hint: assume OC is finite, with elements k 1, ••• , k s , and consider the polynomial f(x) = 1 + (x - k 1 ) ••• (x - ks ).) Deduce that the zero set of an algebraic curve in OC2 is infinite. (This generalizes Lemma 2.1.)

3.3 Polynomials in Several Variables Formally, a polynomial f(Xl, ... , x n ) over the domain ]IJ) in the variables Xl, ... , Xn is an expression given by a formula of the form

where the sum is finite, and the coefficients ail .. .in lie in ]IJ). Polynomials of the form f(Xl, ... , x n ) = a with a E ]IJ) are said to be constant with value a. The polynomials in Xl, ... , Xn form a domain ]IJ)[Xl, ••. , x n ] under the 'obvious' definitions of addition and multiplication, with zero element the constant polynomial taking the value 0, and identity element

3.3 Polynomials in Several Variables

39

the constant polynomial taking the value 1. The units in ]IJ)[X1, ... , X n ] are the constant polynomials whose values are units in ]IJ). In the case when JI]) is afield the units are the constant polynomials with non-zero values, and the associates of a polynomial are its non-zero scalar multiples. Example 3.2 Recall from Example 2.5 that to any given domain is associated a 'field of fractions'. An example is represented by the domain JI])[X1, ... , x n] of polynomials in the variables Xl, ... , Xn over a domain IIJ). In that case the field of fractions is denoted ]IJ)(X1, , x n ), and comprises fractions f / g, where f, g are polynomials in Xl, , Xn with g =1= O. Such fractions are known as rational functions in Xl, ... , Xn. The simplest case is provided by rational functions f(x)/ g(x) in a single variable, with f(x), g(x) polynomials in x. Rational functions in a single variable will play a significant role in discussing the concept of a 'rational' curve in Chapter 8. Note one generality about polynomials in several variables: a polynomial in ]IJ)[X1, ... , x n ] can be viewed as a polynomial in one variable X n (say) with coefficients in the domain ]IJ)[X1, ... , xn-d. That is the main reason we went to the trouble of recalling the theory of polynomials in one variable over a general domain. Here is a useful fact about polynomials in several variables, which illustrates this philosophy well. Lemma 3.9 Let f(X1, ... , x n) be a polynomial over an infinite domain ]IJ) with the property that f(X1, ... ,Xn) = ofor all Xl, ... ,Xn in]IJ). Then f = 0 in ]IJ)[X1, ... ,X n]. Proof The proof proceeds by induction on the number n of variables. When n = 1 the result is immediate from Lemma 3.6. We proceed by induction, assuming the result holds for polynomials in (n -1) variables. Write f = fa + f1 Xn + ... + fsx~, where the coefficients fk lie in the domain ]IJ)[X1, ... , xn-d. If f = 0, there is nothing to prove, so we can suppose f =1= O. Moreover, we can suppose fs =1= 0, else we are back to the case of a polynomial in (n - 1) variables. By the induction hypothesis, there exist a1, ... , an-1 in ]IJ) for which fs(a1, ... , an-1) =1= O. But then Lemma 3.6 tells us there are only finitely many values of X n for which f(a1, ... , an-1, x n) = o. Choosing an E ]IJ) distinct from these values gives f(a1,···, an-1, an) =1= 0, a contradiction. D

The degree of the monomial xii and that of the polynomial f(X1,

x~ is the natural number i1 + ... + in,

, x n) is the maximal degree of those

40

Polynomial Algebra

monomials xiI ... X~l with ail .. .in =1= O. As in the one variable case, it is easily checked that the degree is additive, in the sense that for polynomials 11, ... ,Ip the degree of the product I === 11 ... I p is given by degi

===

degii

+ ... + degI p ·

Clearly, the degree of a polynomial provides a degree function on any polynomial domain. What is not so obvious is that provided the domain is a field irreducible polynomials are prime. We are not going to prove this result, the interested reader will find excellent accounts given in numerous texts in the area of algebraic geometry. (For instance Ideals, Varieties and Algorithms by D. Cox, J. Little and D. O'Shea, Springer Verlag, Undergraduate Texts in Mathematics.) On that assumption Lemma 3.3 yields one of the most basic results used in this text. Theorem 3.10 Any non-constant polynomial I(xl, ... , x n ) over a field II( can be written uniquely (up to order and non-zero scalars) in the form I === cI~1 ... I;s where c is a scalar, where 11, ... ,Is are irreducible, and for i =1= j no Ii is a factor of Ij. (Unique Factorization Theorem.) The polynomials 11, ... , Is are the components of I, and the numbers rl, ... , rs are their multiplicities. Note that if I, 11, ... , Is have degrees d, d 1, .•. , ds then (by additivity of the degree) d == rtdt + ... + rsd s. A component of multiplicity 2 2 is said to be repeated. A general remark is that the zero set of a curve I, with unique factorization I == cI~1 ... I;s, is the union of the zero sets of its components It, ... , Is. Thus in some sense, one is reduced to the irreducible case. In general it is rather difficult to determine whether a given polynomial in two variables is irreducible. Polynomials of degree 1 are certainly irreducible; for those of higher degree one may be able to decide the question by going back to first principles. Example 3.3 Consider the polynomial I === y2 - x. Let us verify from first principles that I is irreducible. Suppose I reduces to two polynomials of degree 1, so we can write y2- x == (atx+btY+Ct)(a2x+b2Y+C2) with one of at, b t non-zero, and one of a2, b2 non-zero. Equating coefficients of x 2, xy, y2, x we get 0 == ata2, 0 === atb2 + a2bt, 1 == b t b2, -1 == atC2 + a2Cl. The first relation tells us that at === 0 or a2 === 0; we claim that both are zero. If al == 0 the second relation yields 0 == a2bl, but the third relation shows that b t =1= 0, so a2 == 0 as well; likewise if a2 == 0 then at == 0 as well. The fourth relation now provides a contradiction, and we conclude that I is irreducible.

3.3 Polynomials in Several Variables: Exercises

41

A few words are in order on the factorization of real and complex polynomials. In many physical problems one starts with a curve f in JR2 , and finds that the geometry is explained by thinking of f as a curve in ee 2 with real coefficients. Thus real and complex curves playa significant role in the applications of the subject. Recall from school mathematics that the factors of a polynomial in one variable with real coefficients are either real, or occur in complex conjugate pairs. This statement extends to general polynomials as follows. A complex polynomial f is said to be real when there exists a polynomial g with real coefficients and a complex scalar A for which f = Ag. In particular, any polynomial f with real coefficients is real. (Beware: according to this definition the complex polynomial ix is real.) An equivalent condition proceeds via the idea of 'complex conjugation'. The complex conjugate of f is defined to be the polynomial 1 obtained from f by replacing all its coefficients by their complex conjugates. (For instance the complex conjugate of x + iy is x - iy.) It is easily verified (Exercise 3.3.4) that f is real if and only if f = AJ for some complex number A =1= O. Note that f is irreducible if and only if 1 is irreducible; it follows immediately that if f has components fl, ... , fs then 1 has components Jl' ... , Js with the same multiplicities. Lemma 3.11 The components of a real polynomial occur in complex conjugate pairs.

f are either real, or

Proof Suppose that f is real, so f = AJ for some complex number A =1= O. Then (by the Unique Factorization Theorem) f, 1 have the same components, and each fj is a complex scalar multiple of some Jk. When j = k that means that fj is real, and when j =1= k it means that lk is the complex conjugate of fj, up to a complex scalar multiple. D

Exercises 3.3.1 3.3.2 3.3.3

3.3.4

3.3.5

Show from first principles that the conic x 2 + y2 -1 is irreducible. Show that deg(f + g) s max(degf,degg). Show that the degrees of polynomials f, g are related to the degree of the polynomial fg by deg(fg) = degf + degg. Now use induction to establish that the degree is additive. Show that a complex polynomial f is real if and only if there exists a complex number A such that f = Al. Show that any non-constant polynomial f(x) over the field JR has a unique factorization into linear factors (x - a) and quadratic

42

3.3.6

3.3.7

Polynomial Algebra

factors x 2 + {Jx + y where Ct, {J, yare real. (Use Lemma 3.11.) Deduce that any non-constant polynomial f(x) over the field ~ of odd degree has at least one real zero. Find the zeros of the complex polynomial f(x) = x 4 + 81. Hence write f(x) as a product of complex linear factors, and as a product of real quadratic factors. Show that x = i - 1 is a zero of the complex polynomial given by f(x) = x 4 + 2x 3 + 3x 2 + 2x + 2. Hence factorize f(x), and find all the zeros.

3.4 Homogeneous Polynomials A polynomial F of degree d in the variables Xl, ... , X n over the domain IT», is homogeneous (or a form) when every monomial has the same degree d. Forms will be denoted by capital letters F, G, H, Forms of degree 1, 2, 3, ... are said to be linear, quadratic, cubic, Collecting together terms of given degree we see that any non-zero polynomial f of degree d can be written uniquely as f = Fo + Fl + ... + Fd where each Fk is a form of degree k. One refers to Fo, Fl, ... , Fd as the constant, linear, quadratic, ... parts of f. We refer to the part Fc of lowest degree as the lowest order terms (abbreviated to LOT), and to the part Fb of highest degree as the highest order terms (abbreviated to HOT) in f. We will be interested mainly in binary forms (the case of two variables) and ternary forms (the case of three variables). Here is an alternative way of viewing forms. In practice we will only use it for the real and complex fields, but it is phrased for general infinite domains IT» simply to clarify the structure of the proof. Lemma 3.12 Let F(Xl, ... , x n ) be a polynomial over an infinite domain IT». Then F is a form if and only if for all t E IT», F(tXl, ... , tx n )

= tdF(Xl, ... , x n ).

(3.1)

Proof Equation 3.1 certainly holds when F is a form of degree d: multiplying all the variables by t means that we multiply each monomial (and hence F) by t d • Conversely, assume Equation 3.1 holds. Write F = Fo + Fl + ... + Fd where each Fk is a form of degree k. Since Equation 3.1 holds for each form Fk it can be rewritten as

3.4 Homogeneous Polynomials

43

This is a polynomial equation in the single variable t with coefficients in the domain II} [Xl , ... , x n ] having infinitely many roots, one for each t E II}. By Lemma 3.6 all the coefficients vanish, so Fo = 0, ... , Fd-l = 0, F = Fd. Thus F is a form of degree d. D Since forms are special types of polynomials, they enjoy the property of unique factorization; what is not immediately clear is that factors of forms are themselves necessarily forms. Lemma 3.13 Any factor of a form F is itself a form.

Proof Suppose F = fg, and that one (say f) of f, g is not a form. Write f = Fa + Fa+ l +... + Fb with the Fi forms of degree i, and Fa =1= 0, Fb =1= o. Also write g = Gc + GC+ I + ... + Gd with the Gj forms of degree j, and Gc =1= 0, Gd =1= O. Then F = FaG c + ... + FbGd with FaG c =1= 0, FbGd =1= O. By supposition a < b so deg(FaG c ) = a + c < b + d = deg(FbGd), and that contradicts the assumption that F is a form. D

Thus, by Unique Factorisation of Polynomials, any form F admits a unique factorization F = CF~l ... F;s with c =1= 0 a scalar, and the Fi irreducible forms such that Fj is not a factor of Fk for j =1= k. We will have a particular interest in binary forms, which have particularly simple factorizations. Lemma 3.14 Any non-zero complex form F(x, y) can be written uniquely (up to order) in the form F(x,y) = (alx+!Jly)'l ... (asx+!Jsy)r s where the ratios (al : !JI), ... , (as: !Js) are uniquely defined.

Proof Let F(x, y) = Ef=o aixiyd-i, and let c be the largest index for which ac =1= O. Then, using the unique factorization of polynomials in a single variable xjy for the second line, we derive the required form

D Finally, here is a useful little proposition, providing us with a sufficient condition for the irreducibilty of many of the curves arising in this book.

44

Polynomial Algebra

Lemma 3.15 Let F, G be non-zero forms of degrees d, d + 1 respectively, having no common factors. Then f = F + G is irreducible. Proof Suppose F + G = ab with a, b non-constant polynomials. Write a = A p + ... + Apt, b = B q + ... + Bqt where the Ai, B j are forms of degrees i, j where p s p', q s q', and where A p, Apt, B q, Bqt are all =!= O. Suppose p < p' and q < q'. Equating terms of equal degree in F + G = ab we get F = ApBq, G = A pBq+ 1 + A p+1 Bq, ... , 0 = AptBqt. The last relation is a contradiction, so we must have p = p' or q = q'. But in either case it is clear that F, G have a non-constant common factor, contradicting the hypothesis. D

Example 3.4 The real polynomial f = (x 2 - y2)2 - y(3x 2 - y2) can be written f = F3 + F4, where F3 = -y(3x 2 - y2) = -y(J3x - y)(J3x + y), F4 = (x 2 _ y2)2 = (x-y)2(x+y)2. Clearly F3, F4 have no common factors, so f is irreducible.

Exercises 3.4.1

3.4.2

Show that the criterion for homogeneity given in Lemma 3.12 may fail over a finite domain J]J) by considering polynomials over the field Z2. In each of the following cases, find the linear components of the given complex binary form F(x,y). (i) F = x 2 + xy + y2 (iv) F = x 3 + x 2y + xy2 + y3 F = x3 F = x3

(ii) (iii)

3.4.3

-

+

y3 y3

(v)

(vi)

F = x4 F = x4

+ y4

+ x 2y2 + y4.

In each of the following cases show that the given polynomial f(x, y) is irreducible. (i)

(ii) (iii) (iv) (v)

f = y2 - xy2 - x 2 - x 3 f = y3 - y2 + x 3 - x 2 + 3xy2 + 3x 2y + 2xy f = x 2y - y3(2x + y) - 2x4 (2 =!= 0) f = (x 2 + y2)2 - y(3x 2 _ y2) f = x 6 - x 2 y 3 _ y5. 3.5 Formal Differentiation

We need to say something (it will be the bare minimum) about differentiating polynomial functions, since many of our results (and compu-

3.5 Formal Differentiation

45

tations) will involve derivatives. The formal derivative of a polynomial f(x) = ao+alx+a2 x2 + ... is defined to be f'(x) = al +2a2x+3a3x2+ .... The point of this definition is that it makes sense over any field, and gives the 'correct' answers (meaning those expected from elementary calculus) over the real (or for that matter, complex) field. In exactly the same way, we define the formal partial derivatives of a polynomial I in several variables, and the formal higher derivatives. We write fx, fy, for the , and first order partial derivatives with respect to the variables x, Y, extend this notation in an obvious way to higher order derivatives. It is an easy matter to check that the resulting process of differentiation has the algebraic properties expected of differentiation. (Exercise 3.5.1.) Here is a typical application of derivatives to the question of when a polynomial f(x) has a repeated factor.

I in a single variable x over a field ]I{ has a repeated irreducible factor g if and only ~r g is a common factor of both I,

Lemma 3.16 A polynomial

f'· Proof Suppose that f has a repeated irreducible factor g, so g21f and we can write f = g2h for some polynomial h. Differentiation yields I' = 2gg' + g2h', so g is a factor of I' as well. Conversely, suppose that g is an irreducible common factor of I, I'. Since glf we can write f = gk for some polynomial k, and differentiation gives I' = g'k+gk'. As glf' we deduce that glg'k. g is irreducible by assumption, hence prime. (Remember, it is a working assumption that in polynomial domains irreducibles are prime.) It follows that gig' or glk; the former case is not possible, since deg g > deg g', so g Ik. Together with f = gk that implies that g21I, so g is a repeated factor of f. 0 The key application of differentiation is the idea of a Taylor expansion. This has two ingredients, namely the Taylor expansion for the special case of polynomials in one variable t, and the Chain Rule. Lemma 3.17 Let ¢(t) be a polynomial of degree d over the field OC, and let

a be a scalar. Then we have the following Taylor expansion of ¢(t) centred at t = a,

46

Polynomial Algebra

Proof Write c/J(t + a) = L:1=o aiti. Differentiating d times with respect to t, and then setting t = 0 in the resulting expressions, we find that ao = ¢(a),

al = ¢'(a),

_ 1 ,

a2 - 2¢ (a),

_ 1

(d)

(a).

The result follows on substituting these expressions for the coefficients ao, ... , ad in the formula for c/J(t + a), and then replacing t by t - a. D The most useful case of the Taylor expansion is the case when a yielding the Maclaurin expansion

=

0,

Lemma 3.18 Let f(Xl, ... , x n) be a polynomial in n variables, and let gl(X), ... , gn(x) be n polynomials in one variable, then we have the Chain Rule

We are now in a position to extend the Maclaurin expansion to any number of variables; effectively, this is an explicit way of writing the polynomial as a sum of forms. Lemma 3.19 Let f(x) be a polynomial in x = (Xl, then we have the Maclaurin expansion at 0 = (0,

f(x)

=

f(O)

+L

X;fXi(O)

1

+ 2! L

,Xn) over the field IK, ,0)

xixjfxiXj(O) + HOT.

Proof For fixed x write ¢(t) = f(tx). Expand ¢(t) by the Maclaurin expansion, as in Lemma 3.17. The Chain Rule gives c/J(O) = f(O), c/J'(O) = L: xifxi(O), .... The result follows on substituting these expressions back in the Maclaurin expansion, and then setting t = 1. D

Exercise

3.5.1

Establish the following properties of differentiation for polynomials over an arbitrary field. (i) (ii) (iii)

(f + g)' = f' + g' (fg)' = f'g + fg' f' = 0 for f constant.

4 Affine Equivalence

In this chapter we will be concerned with the question of when two curves are to be regarded as the 'same'. The first thing to be clear about is that there is no absolute answer - it all depends on which aspects of curves you are studying. We will introduce the group of 'affine mappings', leading to a natural relation of 'affine equivalence' on the curves of given degree d. The remainder of the chapter will be concerned with concepts which are invariant under affine mappings, so can be used in principle to distinguish curves. The first of these is the concept of degree, which has a basic geometrical interpretation, and the second is the interesting concept of a 'centre', inspired by the familiar case of a circle. In order to motivate the definitions of Section 4.1, it may be helpful to start with what is possibly a more familiar notion, at least in the context of studying the standard conics of elementary geometry. We keep to the familiar Euclidean plane ~2. (This is one of the very few points in our development where we will refer to the Euclidean structure on ~2, but only for motivational purposes.) When dealing with standard conics, one thinks of two curves as being 'rigidly' equivalent when the one can be superimposed exactly on the other. You think of the curves as being in different (rectangular) coordinate systems, say one curve in the 'standard' (x, y)-plane, and the other in the (X, Y)-plane. Then the instinct is that if you place the second plane on the first so that the axes coincide, then the two curves will coincide exactly. The idea is illustrated in Figure 4.1. The relation between the two coordinate systems in this situation is that the one can be obtained from the other by a rigid mapping from the (x,y)-plane to the (X, Y)-plane, i.e. a mapping that preserves both distance and orientation. In books on linear algebra, it is shown that rigid maps are precisely those which can be written as composites of otations (about the origin) and translations. Explicitly, they are mappings given 47

48

Affine Equivalence

y,Y

x

superimpose

X,X

Fig. 4.1. Superimposing two curves

by formulas of the following form, where () is the angle of rotation, and (u, v) is the translation vector.

{~

cos () . x - sin () . y sin e. x + cos e. y

+u + v.

The resulting relation of 'rigid' equivalence on curves is too fine, in the sense that it produces far too many types of curves. For instance, two standard parabolas y2 = 4ax, y2 = 4a' x with a, a' > 0 are rigidly equivalent in this sense if and only if a = a'. (Exercise 4.2.2.) Thus we would obtain infinitely many different types of parabola, one for each positive value of the scalar a. However, there is a natural way forward here. The rotational component of the 'rigid' map is a special type of invertible linear map; replacing this by a general invertible linear map we obtain the key concept of an 'affine' map, developed in the remainder of this chapter. This has the extra advantage that it will make sense over a general field JK.

4.1 Affine Maps The first step is to introduce the concept of an 'affine map' of JK2. An affine map (or equivalence, or change of coordinates) of JKn is a mapping ¢ : JK2 ~ JK2 of the form ¢ = T 0 A, where A is an invertible linear map of JK2, and T is a 'translation' defined by a formula T(X) = x + t with t a fixed vector in JI(2. Thus, if we think of A given by a formula A(X) = Lx,

4.2

~ffine

Equivalent Curves

49

with L an invertible 2 x 2 matrix, we see that an affine map has the form ¢(x) == Lx + t. More concretely, an affine mapping has the form ¢(x,y) == (X, Y) where X, Yare given by the formulas below for some scalars p, q, r, S, u, v with ps - qr =1= o.

{~

px +qy +u rx + sy + v.

Example 4.1 Taking the linear map A to be the identity, we see that any translation is an affine map. Likewise, taking the translation r to be zero we see that any invertible linear map is affine. In particular, scalings X == px, Y == sy (with p =1= 0, s =1= 0) are affine maps, as is the coordinate switch X == y, y == x. Rigid mappings of the plane are affine, corresponding to the case when p == cos e, q == - sin e, r == sin e, S == cos e for some angle e; note that ps - qr == 1 =1= o. Recall that translations and invertible linear maps are examples of bijections of the plane. Since the composite of two bijections is another bijection, we deduce that affine maps are automatically bijective, and hence have inverses. One of the basic facts about affine maps of OC2 is that they form a group Aff(2) under the operation of composition. (It is not Abelian.) We need to verify the group axioms of Section 2.2. • G1. Aff(2) is closed under composition. Indeed if ¢1(Z) == L 1z + t1, ¢2(Z) == L 2z + t2 are two affine maps then (by straight computation) their composite is ¢(z) == (¢1 0 ¢2)(Z) == Lz + t, where L == L 1L2 and t == L1t2 + t1, which is again an affine map. (Recall from linear algebra that the product of t\VO invertible 2 x 2 matrices is again invertible.) • G2. Composition of maps is known to be an associative operation on the set of all maps from a given set to itself. • G 3. The identity map of 1[(2 is the affine map ¢(z) == Lx + t with L == I, t == 0 where I is the identity 2 x 2 matrix. • G4. Aff(2) is closed under inversion. The inverse of the affine map ¢(z) == Lz + t is ¢-1(z) == L'z + t' where L' == L -1 and t' == -L-1 t, which is again affine.

4.2 Affine Equivalent Curves Two affine curves f, g in 1[(2 are affinely equivalent when there exists an affine map ¢ and a scalar A =1= 0 with g(x,y) == Af(¢(x,y)). Since Aff(2) is a group, affine equivalence defines an equivalence relation on

50

Affine Equivalence y

y

affine x

x

map

Fig. 4.2. Affine equivalent curves

the curves in OC2. One pictures the situation as in Figure 4.2; two curves as the 'same' when the one can be superimposed upon the other by an affine map. More concretely, that means that there exist scalars p, q, r, S with ps - qr =1= 0 and a relation of the form g(x, y) = Af(px + qy

+

(l,

rx + sy + f3).

Example 4.2 Any two lines in II(2 are affinely equivalent. Since the affine equivalences form a group, it is sufficient to show that any line is affinely equivalent to the line x = O. Suppose the line is ax + by + c = 0, with one of a, b non-zero. We can suppose a =1= 0, otherwise we just switch the coordinates x, y to obtain an affine equivalent line with a =1= o. Then X = ax + by + c, Y = y is an affine equivalence, with inverse x = (X - bY - c)ja, y = Y, taking ax + by + c to X.

Example 4.3 In}R2 the standard parabola y2 = 4ax with a > 0 is affine equivalent to the parabola y 2 = X via the scaling x = aX, y = 2aY; the standard ellipse x 2 j a 2 + y2 jb 2 = 1 with 0 < a < b is affinely equivalent to the circle X 2 + Y 2 = 1 via the scaling x = aX, y = bY; and the standard hyperbola x 2j a 2 - y2 j b2 = 1 is affine equivalent to the rectangular hyperbola X 2 - y2 = 1. Generally, a parabola in ]R2 is a conic affine equivalent to Y2 = X: an ellipse is a conic affine equivalent to X 2 + Y 2 = 1; and a hyperbola is a conic affine equivalent to X 2 - y2 = 1. We will have rather more to say about the affine types of conics in Chapter 5.

4.3 Degree as an Affine Invariant

51

Exercises 4.2.1 4.2.2

Show that the rigid mappings of ]R2 form a subgroup of the affine group Aff(2). Two affine curves f, g in ]R2 are rigidly equivalent when there exists a rigid map ¢ and a scalar A =1= 0 with g(x,y) = Af(¢(x,y)). Show that the parabolas y2 = 4ax, y2 = 4a' x in ]R2 with a, a' > 0 are rigidly equivalent if and only if a = a'.

4.3 Degree as an Affine Invariant In this section, we will establish that the algebraic concept of the degree of a curve is an affine invariant, and that it admits an important geometric interpretation. Lemma 4.1 The degree of a curve is an affine invariant, i.e. two affine equivalent curves have the same degree. Thus affine maps take lines to lines, conics to conics, and so on. Proof Let f, g be affine equivalent curves, so there exists an affine map ¢(x, y) = (px + qy + ct, rx + sy + 13) and a scalar A =1= 0 such that g(x, y) = Af(¢(x,y)) = Af(px + qy + ct, rx + sy + 13). Assume f(x,y) = L aijxiyj, so g(x, y) = A

L aij(px + qy + ct)i(rx + sy + f3)j.

Each expression px + qy + ct, rx + sy + 13 in parentheses is a polynomial of degree 1. (They cannot be constant, else the condition ps - qr =1= 0 fails.) By additivity of the degree, (px + qy + ct)i(rx + sy + f3)j has degree i + j. It follows immediately that deg f ~ deg g: since affine equivalence is a symmetric relation deg g ~ deg f, yielding the result. D Lemma 4.2 Let f, g be affine equivalent curves in JI(2. Suppose that f has components f 1, ... , f s with multiplicities rl, ... , rs and degrees d 1, ... , ds . Then g has components gl, , gs where fk, gk are affinely equivalent, with the same multiplicities rl, , rs and the same degrees d 1, ... , ds . In particular, f is irreducible (reducible) if and only if g is irreducible (reducible ). Proof Since f, g are affinely equivalent there exists an affine map ¢ and a scalar A =1= 0 with g(x,y) = Af(¢(x,y)). The curve f has a unique

Affine Equivalence

52

factorization f =

Cf~l

... f~s with c

g(x,y)

=1=

O. Then

Af(cjJ(x, y)) (Acf~l

... f;s)(cjJ(x,y))

Acf~l (cjJ(x,

Acg~l (x,

y)) ... f;s( ¢(x, y))

y) ... g;s (x, y)

where gk(X,y) = fk(cjJ(X,y)) is affinely equivalent to fk, and hence has the same degree dk • In particular, the argument shows that f is irreducible (reducible) if and only if g is irreducible (reducible). It follows that gl, ... , gs are the components of g. D Our object now is to show that the algebraic concept of degree has a purely geometric interpretation in terms of the zero set of the curve, providing a powerful way of thinking about curves. The proof depends on a useful technical lemma, which gives you some idea of the 'flexibility' of affine maps. A set of points in OC2 is collinear when there exists a line passing through every point in the set. And a set of lines in OC2 is concurrent when there exists a point through which every line in the set passes. Lemma 4.3 Let A, B, C and A', B', C' be triples of non-collinear points. There exists a unique affine map ¢ which takes A, B, C respectively to A', B', C'. (The Three Point Lemma.)

Proof Since the affine maps form a group, it is enough to prove the result when A = (1,0), B = (0, 1), C = (0,0). We seek an affine map ¢(X, Y) = (x,y), say x = pX +qY + ex, y = rX +sY +fJ with ps-qr =1= 0 for which cjJ(I,O) = (p + rt, r + fJ) = A', cjJ(O, 1) = (q + rt, S + fJ) = B', cjJ(O,O) = (rt, fJ) = C'. It is clear these relations determine ex, fJ, p, q, r, s (and hence the map cjJ) uniquely. If ps - qr = 0, the vectors (p, r), (q, s) would be linearly dependent, so (p, r), (q, s), (0,0), and hence their translates A', B', C', would be collinear, a contradiction: thus ps - qr =1= o.

D Here is an application of the Three Point Lemma. It is one of the guiding intuitions of the subject, and will play a very basic role in the remainder of this book. Lemma 4.4 Let f be an affine curve of degree d 2 1 in OC2 , and let I be a line. Then either I meets f in s d points, or I is a component of f. Thus

4.4 Centres as Affine Invariants

53

for a curve f with no line components the degree d is an upper bound for the number of intersections of f with any line 1. Proof Let 1 be the line through a = (aI, a2) and b = (b l , b2). Then 1 is parametrized as x(t) = (l-t)al +tb l , y(t) = (l-t)a2+tb2 with t E OC. The where ¢(t) = f(x(t), y(t)) intersections of f and 1 are given by ¢(t) = is a polynomial in t of degree :::; d (possibly < d). Assume ¢ is not identically zero, then the equation ¢(t) = 0 has:::; d roots, and there are :::; d points of intersection. If on the other hand ¢ is identically zero, then f vanishes at every point on 1. By the Three Point Lemma we can assume a = (0,0), b = (1,0), then 1 is given by y = 0, and f vanishes on 1 if and only if f(x, 0) = for all x E oc. Set f(x,y) = yg(x,y) + h(x) with g, h polynomials, then h(x) = for all x E OC; that means h = 0, so y is a factor of f(x,y), i.e. 1 is a component of f. D

°

°

°

In particular, a line is either a component of an algebraic curve or meets it in finitely many points. (This is one of the 'finiteness' properties of algebraic curves mentioned in Section 1.1. It allows us to give simple examples of curves which fail to be algebraic. For instance the graph of the sine function y = sin x is not algebraic, since the line y = 0 intersects it in infinitely many points, but is not a component.)

Exercises

4.3.1

Show that the polynomial f = 3xy+x 3+y3 is irreducible. Deduce that g = x 3 + y3 - 3x 2 - 3y2 + 3xy + 1 is also irreducible. (Hint: it suffices to show that f, g are affine equivalent.)

4.4 Centres as Affine Invariants

The idea of a 'centre' of a curve is motivated by the familiar case of a circle in ~2. Any line through the centre meets the circle in two distinct points, and the centre is the mid-point of the resulting line segment. What is interesting is that curves other than the circle can have 'centres' in this sense, and that the idea is invariant under affine mappings. A formal development is based on the following observation, that in a certain sense affine maps preserve parameters on lines. Lemma 4.5 Let a, b be distinct points in OC2 , let t E OC and let c

=

a+t(b-a). Then, for any affine map f, we have f(c) = f(a)+t(f(b)- f(a)).

54

Affine Equivalence

Thus an affine map f maps the parametrized line through a, b to the parametrized line through f(a), f(b), and 'preserves parameters'. Proof For any vector u E JK2 write f(u) = A(U) +k, with A linear, and k a fixed vector in the plane. Then, using linearity of A to get the third line, f(c)

f(a + t(b - a)) A(a + t(b - a)) + k = A(a) + t(A(b) - A(a)) + k = {A(a) + k} + t(A(b) - A(a)) = f(a) + t{(A(b) + k) - (A(a) + k)} = f(a) + t(f(b) - f(a)).

=

=

By definition, the parametrized line through a, b comprises the set of points a+t(b-a), and the parametrized line through f(a), f(b) comprises the set of points f(a) + t(f(b) - f(a)), so (by the above computation) D comprises the image under f of the parametrized line through a, b. Example 4.4 The mid-point of the parametrized line through two points a, b in JK2 is defined to be the point with parameter t = 1/2, i.e. the point c = !(a + b). Then Lemma 4.5 tells us that affine maps preserve mid-points on parametrized lines: under an affine map f the mid-point c of the line-segment joining a, b is mapped to the mid-point f(c) of the line segment joining f(a), f(b). Example 4.5 Affine maps preserve the property of two subsets of the plane intersecting, in the sense that if A, B are subsets of the plane, and f is an affine map, then A, B intersect if and only if f(A), f(B) intersect; indeed this is a property of general bijective maps. In particular, the concept of 'parallelism' for lines is an affine invariant. That brings us to the key definition of this section. Let p = ((I., {3) be a fixed point in JK2. By central reflexion in the point p we mean the affine mapping defined by the formula (x, y) ~ (x', y') where x' = 2a - x, y' = 2[3 - y. (Note that when p is the origin this simply means that x' = -x, y' = -y.) The geometric content is that the mid-point of the line joining a point (x, y) to its central reflexion (x', y') in p is the point p. Now let f be a curve in JK2. We say that p is a centre for f when the curves f(x, y), f(x', y') are the same, i.e. their defining polynomials differ only by a non-zero scalar multiple. We express this by saying that f is invariant under central reflexion in the point p. A curve f is central when it has at least one centre.

4.4 Centres as Affine Invariants

55

Fig. 4.3. The concept of a centre

Example 4.6 Any line ax + by + c is a central curve. Indeed any point p = (a, f3) on the line is a centre, for ax' +by' +c = a(2a-x)+b(2f3-y)+c = 2(aa + bf3 + c) - (ax + by + c) = -(ax + by + c). Example 4.7 Consider a conic which reduces to a pair of lines II, 12 • A point p of intersection is called a vertex of the conic. (Thus when the lines are distinct and parallel there is no vertex, when the lines are distinct and intersect there is a unique vertex, and when the lines coincide there is a line of vertices.) A vertex p is automatically a centre of the conic: by Example 4.6 each line 11, 12 is invariant under central reflexion in p, and hence the product 11 12 is invariant as well. Example 4.8 The conic y2 = 1 defines parallel lines y = ±1. Any point = (a, 0) is a centre for the conic. Indeed for any point (x, y), the central reflexion in the point p is the point (x',y') where x' = 2a - x, y' = -y, and clearly (x, y) lies on the conic if and only if (x', y') does. Thus the line y = 0, parallel to y = ±1 and 'midway' between them, provides a line of centres.

p

Lemma 4.6 Centres of curves are affine invariant, in the following sense. Let p be a centre for a curve j, and let ¢ be an affine mapping, then p' = ¢-I(p) is a centre for j' = jo¢. In particular, if two curves are affine equivalent, and one is central, then the other is central.

56

Affine Equivalence

Proof Write z = (x,y). Then f'(z) = f(¢(z)) = f(2p - ¢(z)) = f(¢(2¢-1(p) - z)) = f'(2¢-1(p) - z) = f'(2p' - z). D In principle, Lemma 4.6 provides a starting point for the process of trying to find all centres p = (rx, [3) of a given curve f; we can translate that point to the origin, and then try to discover whether the origin is a centre for the translated curve. That provides the motivation for the next proposition. Lemma 4.7 The origin is a centre of a curve f if and only if there are no terms of odd degree, or no terms of even degree. Proof

Suppose that the origin is a centre for f. Write f(x,y) =

~i,jaijxiyj, and let f'(x,y) = ~i,j(-1)i+jaijxiyj be the polynomial ob-

tained from it by replacing x, y by -x, -Yo The supposition implies that f' = Af for some scalar A =1= 0, so that aij = A( -1 )i+j aij for all choices of i, j. It follows that 1 = A( -1 )i+j for all choices of i, j with aij =1= 0. Since at least one aij =1= 0, that means that either all the i + j with aij =1= are even (and A = 1), or they are all odd (and A = -1). Conversely, if every term in f is of odd degree then f' = -f, and the origin is a centre; likewise, if every term in f is of even degree then f' = f, and we deduce again that the origin is a centre. D

°

Thus if f has even degree, the origin is a centre if and only if there are no terms of odd degree. The simplest case is provided by conics. In that case the origin is a centre if and only if the terms of degree 1 in x, yare absent. (For instance, the origin is a centre of the circle x 2 + y2 - 1, of the hyperbola x 2 - y2 -1, and of the line-pair x 2 - y2.) This observation provides the basis for a practical method of finding all the centres (rx, [3) of a given conic ax 2 + 2hxy

+ by 2 + 2gx + 2fy + c.

(*)

Translate the centre to the origin by substituting x = X + rx, y = y + f3 and then see if (0,0) is a centre for the translated conic, by setting the coefficients of X, Y equal to zero. That yields two linear equations in rx, {3. coefficient of X coefficient of Y

2(arx + h[3 2(hrx + bf3

+ g) =

°

+ f) = o.

Note that these equations are obtained by differentiating (*) with respect to x, y, writing x = rx, y = {3, and then setting the results equal to

57

4.4 Centres as Affine Invariants

zero. Geometrically, each equation defines a line in the (ct, f3)-plane. We now have the situation of Example 1.2. In general the lines intersect in a unique centre, but exceptionally they could be parallel (in which case there is no centre) or coincide (in which case there is a line of centres). These are the only possibilities. By linear algebra, there is a unique centre if and only if l5 = ab - h 2 =1= O. (l5 is the determinant of the coefficients.) This gives you a simple numerical test for determining whether or not a general conic (*) has a unique centre. Note, however, that when b = 0 it does not distinguish the case when there is no centre from the case when there is a line of centres. Example 4.9 Consider the conic x 2-2xy+5y2+2x-10y+1. Here a = 1, b = 5, h = -1 so b = 1.5 - (-1)2 = 4 =1= 0, and there is a unique centre. We can find it explicitly as follows. Substituting x = X + ct, Y = Y + {3, we need to solve the following equations. These have the solution ct = 0, 13 = 1 yielding the centre (0, 1).

coefficient of X coefficient of Y

2(ct - 13 + 1) 2( -ct + 5{3 - 5)

o O.

Example 4.10 Consider the parabola y2 - x in ]R2. Substitute x = X + ct, Y = Y + 13 to see that the coefficients of X, Yare respectively -1, 213. The condition for (ct, {3) to be a centre is that -1 = 0, 2{3 = o. We cannot satisfy these relations, so the parabola has no centre. It follows from Lemma 4.6 that the parabola cannot be affinely equivalent to a real ellipse, since the latter is central. This is an example where we can use an affine invariant to distinguish two (irreducible) affine curves of the same degree.

Here is a pretty application of the above ideas, making the point that they can readily establish facts which are by no means obvious. We have already seen that the conic x 2 + y2 - 1 in ]R2 has a unique centre (not on the conic), and hence any conic affinely equivalent to it, i.e. any real ellipse, has a unique centre (not on the conic). By a chord of a real ellipse we mean a line which meets the conic in two distinct points, and by a diameter we mean a chord through the centre. Clearly, an affine map between two real ellipses will map any chord (respectively diameter) of the one to a chord (respectively diameter) of the other.

58

Affine Equivalence

f

..

Fig. 4.4. Diameters of an ellipse

Lemma 4.8 If you take all the chords parallel to a given diameter L of an ellipse E then the mid-points lie on another diameter M. (L, M are said to be 'conjugate diameters' of the ellipse.) Proof This follows almost immediately from the facts that parallelism and mid-points are preserved by affine maps. There is an affine map f taking E to the unit circle, and mapping the diameter L to a diameter L' of the circle. Clearly, the mid-points of all the chords parallel to L' lie on a diameter M' of the circle. And under the inverse j-l, the diameter M' is mapped to a diameter M of E with the desired properties. (Figure 4.4.)

D Lemma 4.8 makes a fundamental point, namely that we can deduce affine properties of affine algebraic curves from those of curves affine equivalent to them. That raises the question of classifying curves of given degree d up to affine equivalence. Example 4.2 solves that problem in the simplest case d = 1. In Chapter 5, we will deal with the next simplest case d = 2 of conics in some detail, as they represent a key element in understanding algebraic curves.

Exercises

4.4.1

In each of the following cases decide whether the given conic in ]R2 has a centre, and if so write down the equation of the conic relative to the centre as origin. (i) 25x 2 + 9y 2 - 72y - 81 (ii) 5x 2 + 6xy + 5y 2 - 4x + 4y - 4 (iii) x 2 - 4xy + 4y 2 + lOx - 8y + 13.

4.4 Centres as Affine Invariants: Exercises

4.4.2

59

In each of the following cases decide whether the given conic in has a centre, and if so, write down the equation of the conic relative to the centre as origin.

]R2

(i) (ii)

(iii) (iv)

x 2 + xy - 2y 2 + X - Y x 2 - 4xy + 3y 2 + 2x x 2 - 2xy + y2 + 2x - 4y + 3 9x 2 - 24xy + 16 y 2 + 3x - 4y - 2.

5 Affine Conics

This chapter can be thought of as an extended example. The object is to introduce the reader to the question of listing (and of distinguishing) affine curves of given degree d under the relation of affine equivalence. For general values of d, this is a somewhat hopeless (and ultimately uninteresting) task. The answer in the simplest possible case d = 1 of lines (Example 4.2) is misleading, in the sense that it does not depend on the underlying field IK. The next case d = 2 of conics is more interesting, since part of the listing process applies over virtually any field IK, and beyond that it depends crucially on IK. It is particularly satisfying that we obtain complete answers over the real and the complex fields; in those cases we will manage to reduce an arbitrary conic to one of a finite list of 'normal forms' by affine changes of coordinates. By contrast, it would take a significant amount of number theory to achieve an answer over the rational field. The conic case also forces us to think about the question of distinguishing two types of conic on our list. One basic distinction between lines and conics is that conics may factorize so the multiplicities of the components will provide affine invariants. For instance x 2 - y2 factorizes as (x - y)(x + y); it is an example of a 'line-pair' since its zero set is the union of the zero sets of the lines x - y, x + y. A more degenerate case still is provided by x 2 , a 'repeated line'. However, there are certainly conics which do not reduce, for instance in Example 3.3 we saw that the parabola f = y2 - x is irreducible. In Section 5.2 we will look at more subtle invariants of conics, the so-called 'delta invariants' which enable us to make finer distinctions than those provided by the multiplicities of the components. 60

5.1 Affine Classification

61

5.1 Affine Classification

The first step in the process of listing affine conics is to reduce to a 'prenormal' form, independent of the field JK. The resulting lists will depend on JK. According to the definition, a general conic in JK2 is a polynomial of degree 2. In this chapter we will tacitly assume that the ground field JK has characteristic =1= 2, so any conic can be written in the following form, where the coefficients a, b, c, f, g, h lie in JK, and at least one of a, b, h is non-zero,

ax 2 + 2hxy + by2 + 2gx + 2fy + c.

(*)

Lemma 5.1 Any conic in JK2 is affinely equivalent to a prenormal form y2 = q(x) where q(x) = Ax 2 + 2Bx + C and A, B, C are in JK.

Proof The idea is to view (*) as a quadratic in y, whose coefficients involve x, and then 'complete the square'. For this to work we assume (for a moment) that b =1= 0, then, dividing through by b, we can suppose b = 1. That yields an equation (y + hx + f)2 = q(x), with q(x) having the desired form. Now replace y + hx + f by y, and leave x unchanged (an affine equivalence) to achieve the form y2 = q(x). If b = 0 and a =1= 0 just switch x, y (another affine equivalence) and proceed as before. That leaves us with the case a = b = 0, so h =1= O. The trick is to replace x, y by x + y, x - y (yet another affine equivalence) to get back to the case a =1= 0, b =1= o. D Next, let us see what this gives for the real and complex fields. (For other fields the list may be very difficult to obtain.) Here is the list of normal forms for real conics. Lemma 5.2 In JR2 any conic is affinely equivalent to one of the nine normal forms in Table 5.1.

Proof By Lemma 5.1, we can suppose the conic has the form y2 Ax 2 + 2Bx + C, where A, B, C are real numbers. Assume A =1= 0; scaling x by 2 =1= 0 the coefficient of x 2 becomes A22 , and we can force this to be ±1 by choosing 2 so that A2 2 = ±1. (When A is positive we take +, and when A is negative we take -.) Thus we can suppose A = ±1, so y2 = ±(x - B)2 + (B 2 - C), with possibly different Band C. (When A is negative change B into -B as well.) Replacing x - B by x, the equation assumes the form y2 = ±x2 + D. When D =1= 0 we can scale both x, y by

62

Affine Conics Table 5.1. The nine types of real affine conic normal form y2 y2 y2 y2

=X = -X2 + 1 = -x 2 - 1 = x2 + 1

y2 = x2 y2 = -x2 y2 = 1 y2 =-1 y2 = 0

name parabola real ellipse imaginary ellipse hyperbola real line-pair imaginary line-pair real parallel lines imaginary parallel lines repeated line

/1 =!= 0, and then divide through by /12, to change D to D/ /12; now choose /1 so that D //12 = ±1 to get D = ±1. (When D is positive we take +, and

when D is negative we take -.) Firstly, that yields the two normal forms y2 = -x 2 ± 1 (the real ellipse and the imaginary ellipse). It also yields y2 = x 2 ± 1; note however that these forms are affinely equivalent, we just need to switch x and y, so we only get one normal form y2 = x 2 + 1 representing the hyperbola. When D = 0 we get the real line-pair y2 = x 2 and the imaginary line-pair y2 = -x 2. Now consider the case A = 0, so y2 = 2Bx + C. Suppose B =!= O. Then we can replace 2Bx + C by x to get the parabola y2 = x. When B = 0 our equation is y2 = C. When C =!= 0 we can scale y by v, and then divide through by v2 to replace C by C/v 2 . Choose v so that C/v 2 = ±1. (When C is positive take the + sign, and when C is negative take the - sign.) Our equation is now y2 = ±1, yielding real parallel lines y2 = 1 and imaginary parallel lines y2 = -1. Finally, when C = 0 we obtain the repeated line y2 = O. D Example 5.1 Consider the conic x 2 + 2xy + 5y2- 2x -lOy + 1. Collecting terms in x and 'completing the square' we get (x + y - 1)2 + 4(y2 - 2y), and 'completing the square' again gives (x + y - 1)2 + 4(y - 1)2 - 4. Under the affine equivalence X = !(x + y - 1), Y = y - 1 this becomes 4(X 2 + y2 - 1), which is a real ellipse.

Trivial modifications to the proof of Lemma 5.3 (essentially omitting the various ± possibilities) yields the affine classification of complex conics.

5.1 Affine Classification: Exercises

63

Table 5.2. The five types of complex affine conics normal form

name parabola general conic

y2 = x2 y2 = 1 y2 = 0

line-pair parallel lines repeated line

Lemma 5.3 In C 2 , any conic is affinely equivalent to one of the five normal forms in Table 5.2.

Exercises 5.1.1

In each of the following cases, show (by explicit factorization) that the given conic in ffi.2 is a line-pair, and determine the vertex, i.e. the intersection of the lines. (i) 2x 2 - txy + 3y 2 + 5x - 5y + 2 (ii) y2 - 4xy + 4y - 4x + 3 (iii) 2x 2 + xy - y2 - 2x + y.

5.1.2 5.1.3

Write out a proof of Lemma 5.3 following that of Lemma 5.2. In each of the following cases determine the affine types of the given conic in ]R2, and write down an affine equivalence giving the normal form. (i) x 2 - 2xy + y2 + 2x + 3y + 2 (ii) 3x 2 - 10xy + 3y 2 + 14x - 2y - 8 (iii) 5x 2 + 6xy + 5y 2 - 4x + 4y - 4.

5.1.4

In each of the following cases determine the affine type of the given conic in ee 2 , and write down an affine equivalence giving the normal form. In each case where the conic reduces to two lines, find the equations of the lines.

(i) (ii) (iii) (iv) 5.1.5

x 2 + xy - 2y 2 + X - Y x 2 - 4xy + 3y 2 + 2x x 2 - 2xy + y2 + 2x - 4y + 3 9x 2 - 24xy + 16y 2 + 3x - 4y - 2.

For each real number t let

it

be the conic in ffi.2 defined by the

64

5.1.6

5.1.7

Affine Conics formula it{x, y) = x 2 + t{t + 1)y2 - 2txy + 2x + 2. Determine the affine types of the it for all t. For each real number t let it be the conic in IR 2 defined by the formula it = 2y{x - 1) + 2t{x - y). Determine the affine types of it for all t. For each real number t let it be the conic in IR 2 which is defined by the formula it{x, y) = x 2 - 2x - 2y - 1 + t{x + y)2. Determine the affine type of it for all t.

5.2 The Delta Invariants Although we have lists of affine conics in both the real and the complex cases, we have as yet no way of distinguishing the various types on the lists. This section is devoted to the question of achieving such distinctions using two 'delta invariants' l5 and ~. The starting point is to note that the general conic ax 2 + 2hxy

+ by 2 + 2gx + 2iy + c

(*)

can be written advantageously in matrix form. The symmetric 3 x 3 matrix

A=(~g i~ ~) c

is called the matrix of (*). Write v = (x, y, 1): then (*) can be written vAv T, where v T denotes the transpose of the row vector v. We define ~ = detA, l5 = detB where B denotes the leading 2 x 2 submatrix of A; Ll is a somewhat complex expression in a, b, c, i, g, h, whilst 0 and we obtain just

6.2 Multiplicity of a Point on a Curve

77

two values of t, hence just two points of intersection, with corresponding intersection number 2, hence the required intersection pattern 2 + 2. In the '-' case the equation t 2 = c/2 has no solutions, and there are no intersections, as the picture confirms. It is worth pointing out that the concept of the intersection number of a line I with a curve f in ]K2 depended only on the fact that lines always have parametrizations x = x(t), y = y(t). The concept can be extended from lines I to any curve with this property, by defining the intersection function ¢(t) = f(x(t), y(t)) and proceeding as above. Example 6.6 The parabola y = x 2 in ffi.2 has the parametrization x = t, Y = t 2. To investigate its intersections with the circle f = x 2 + y2 - 2y = of radius 1 centred at (0, 1) we form the intersection function ¢( t) = t 4 - t 2 = t 2 (t - 1)(t + 1) having zeros t = 0, t = 1, t = -1 of respective multiplicities 2, 1, 1. There are therefore three intersections, at the points (0,0), (1,1), (-1,1) to which can be associated 'intersection numbers' 2, 1, 1.

°

It is tempting to think that this idea can be used to define intersection numbers for any two curves in 1[(2. Unfortunately it founders on a very basic fact, namely that very few curves have 'global' parametrizations x = x(t), y = y(t). We will say rather more about this topic in Chapter 8. The introduction of 'intersection numbers' for two general curves requires a new set of ideas, explained in Chapter 14.

6.2 Multiplicity of a Point on a Curve Now specialize the above by taking p = (a,b) to be a fixed point on the curve f, and consider the intersections of f with the 'pencil' of all lines through p. (We will give a formal definition of this term in Section 16.2.) In this situation, I (p, f, I) 2 1 automatically. The multiplicity of p on f is the minimal value m of the intersection number I (p, f, I) taken over all lines I through p, i.e. I (p, f, I) 2 m for every line I through p, and there exist lines I for which I (p, f, I) = m. Since intersection numbers are affine invariants, the multiplicity of a point on a curve is likewise an affine invariant. Points of multiplicity 1, 2, 3, 4, ... are said to be simple, double, triple, quadruple, ... points of f. A crude mental picture for a point p of multiplicity m is that there are m 'branches' of the curve self-intersecting at p. (But beware; as we will see, that is not necessarily the case.) For

78

Singularities of Affine Curves y

x

Fig. 6.4. Triple point on the three-leaved clover

instance the three-leaved clover of Figure 6.4 has a point of multiplicity 3 at the origin. The next result provides a computational technique for determining the multiplicity of a point on a curve. Recall that the 'lowest order terms' (LOT) in a polynomial were defined in Section 3.4. Lemma 6.4 Let p == (a,b) be a point on a curve f in JI(2. Set g(x,y) == f(a + x, b + y). The multiplicity of p on f is the degree of the LOT in g. In particular, the multiplicity of the origin (0,0) on f is the degree of the LO T in f itself. Proof Write g == Gm + Gm+l + ... + Gd where each Gk is a form of degree k, and Gm =1= O. Let (X, Y) be a non-zero vector in JI(2, and let I == Ix,Y be the line joining the points (a, b), (a + X, b + Y), thus I is given parametrically as x( t) == a + tX, y(t) == b + t Y. The associated intersection polynomial is then f(a

+ tX,b + tY)

g(tX, tY) Gm(tX, tY)

+ Gm+ 1(tX, tY) + ...

tmGm(X, Y)

+ tm+1 Gm+ 1(X, Y) + ....

Clearly, t m is a factor of 4Jx,y(t) for all choices of X, Y. However, there exist choices of X, Y for which Gm(X, Y) =1= 0, and hence for which tm+ 1 is not a factor of 4Jx,y(t). (Recall that a binary form has only finitely many zeros.) It follows that p is a point of multiplicity m on f. D

6.2 Multiplicity of a Point on a Curve

79

x

Fig. 6.5. The astroid

Example 6.7 The astroid is the curve in ]R2 given parametrically by x = sin 3 t, y = cos 3 t. By substitution, one can check that every point on the astroid lies on the sextic curve f = (1 - x 2 - y2)3 - 27x 2y2. (In fact the zero set of f coincides with the image of the parametrized curve, but that is harder to check.) The illustration in Figure 6.5 suggests that four points on the curve, namely (1,0), (0, 1), (-1,0), (0, -1) are in some sense exceptional. For instance the point (1,0) has multiplicity 2; using Lemma 6.4 with a = 1, b = 0 we see that g(x,y) = f(x+ 1,y) = _(x 2 +2x+ y2)3 -27(x+ 1)2y2 = -27y2 + HOT. The criterion for a point to be of given multiplicity m on a curve can also be phrased usefully in terms of partial derivatives.

Lemma 6.5 Let p = (a, b) be a point on a curve f in ]K2. Then p has multiplicity m on f if and only if all the partial derivatives of f of order < m vanish at p, and at least one partial derivative of order m is non-zero at p. Proof Set g(x,y) = f(a + x,b + y), and write g = Go + ... + Gd where each Gk is a form of degree k. Then by Lemma 6.4 the point p has multiplicity m on f if and only if Go = ... = Gm-l = 0, Gm =!= o. The Taylor expansion of g(x,y) shows that these conditions hold if and only if all the partial derivatives of g of order < m vanish at the origin, and at least one of order m is non-zero at the origin. The result follows since the partial derivatives of g at the origin coincide with those of f at p. D

Singularities of Affine Curves

80

Exercises 6.2.1

In Example 1.8 it was shown that the pedal curve of the standard parabola y2 -4ax with a > 0, with respect to the pedal point p = (ex, 0) satisfies the equation of the cubic f = x(x-ex)2+ y2(a-ex+x) in ]R2. Show that P is a double point of f.

6.2.2

In Example 1.10 it was shown that the pedal curve of the unit circle x 2 + y2 = 1 with respect to the pedal point p = (ex, 0) satisfies the equation of the quartic in }R2 defined by

Show that p is a double point of f. 6.2.3

In each of the following cases, find the multiplicity of the given point p on the curve f in }R2.

(i) (ii) (iii) (iv) (v)

p = (0,1) p = (0,1) p=(O,l) p=(l,l) p = (0,4)

f = (x 2 - 1)2 - y2(3 - 2y) f = x 2(3y - 2x 2) - y2(1 - y)2 f=x 2y+xy(y-1)+(y-1)2 f=x 3 +y3-3x 2 -3 y2+3xy+1 f = y3(4 - y)3 - 4x 4 (x + 3)2.

6.3 Singular Points Points of multiplicity 2:: 2 on a curve f are singular and play an important role in understanding the geometry of the curve. The curve f is singular when it has a singular point, otherwise it is non-singular. Since multiplicity is invariant under affine mappings, so too is the concept of a singular point. We will see in Chapter 14 that an irreducible curve f has at most finitely many singular points, thus the number of singular points, and the list of their multiplicities, is an affine invariant of f. Lemma 6.5 yields the following criterion for a point to be singular on a curve f. Lemma 6.6 A necessary and sufficient condition .for a point p = (a, b) to be singular on a curve f is that f(p) = 0, fx(p) = 0, fy(p) = 0. One finds the singular points of f by solving the equations displayed in the statement; there is no general technique beyond native ingenuity. Example 6.8 The singular points of a line f = ax + by + c are given by = f, = fx = a, = fy = b. These relations can only be satisfied when a = b = 0, which is impossible. Thus lines are non-singular.

° °

°

6.3 Singular Points

81

y

x

Fig. 6.6. The Maltese cross

Example 6.9 The singular points of a general conic f in OC2 are given by f(x,y) = 0, fx(x,y) = 0, fy(x,y) = 0. The latter relations say that (x,y) is a centre for f. Thus a singular point of a conic is a centre which lies on the conic. Over the complex field the only two normal forms having singular points are the line-pair (the singular point is the point of intersection) and the repeated line (every point on the line is singular); over the real field the outcome is the same, save that we have two types of line-pair, namely real and imaginary. Example 6.10 For the eight-curve f = y2 - x 2 + x 4 , singular points require = f, = fx = 2x(2x 2 - 1), = fy = 2y. Thus there is a unique singular point (0,0), of multiplicity 2. It is no coincidence that this is the only point of the curve where the curve crosses itself.

° °

°

Example 6.11 The Maltese cross is the quartic in ]R2 defined by f = xy(x 2 - y2) - (x 2 + y2) and illustrated in Figure 6.6. Singular points are given by = f, = fx = 3x 2y - y3 - 2x, = fy = x 3 - 3xy 2 - 2y. These relations look unpromising. The magic trick is to notice (using the relation f = 0) that = xfx + yfy = 4xy(x 2 - y2) - 2(x 2 + y2) = 2xy(x 2 - y2) so that x = 0, y = or x 2 - y2 = 0. In each case it is clear that (0,0) is the only solution of f = 0, fx = 0, fy = 0. The magic trick is 'explained' in some measure by Exercise 10.3.9.

° ° °°

°

Example 6.12 Any curve in ]R2 can be viewed as a curve in C 2 ; there may be singular points in C 2 which are not in ]R2. Take for instance f(x,y) = (1 + x 2)2 - xy2. Then fx = 4x(1 + x 2) - y2, fy = -2xy. For

82

Singularities of Affine Curves

y

x

Fig. 6.7. An invisible singular point

singular points we have x = 0 or y = O. x = 0 can't give a singular point as f(O,y) = 1. When y = 0, we have to satisfy (1 + x 2 )2 = 0, 4x(1 + x 2 ) = O. Over the real field these equations have no solution, and there are no singular points in ]R2. But over the complex field we have solutions x = ±i, yielding singular points (±i,O) in C 2 . Example 6.13

The reader is warned that a singular point on a real curve may not be visible on the zero set. An example is provided by the

irreducible quartic f = x 4 - x 2y - y3 in ]R2, having a singular point at the origin. The zero set of f is the image of the parametrized curve x = t + t 3 , Y = t 2 + t 4 . (Exercise 8.1.12.) It follows that given x, the equation f(x, y) = 0 can be solved uniquely for y; indeed t + t 3 is a non-decreasing function of t with image the whole real line, so given, x we determine a unique t with x = t + t 3 , hence a unique y = t 2 + t 4 . And the tangent vector to the parametrization varies smoothly with t, so the zero set is perfectly 'smooth' at the origin, as can be seen in Figure 6.7. One way in which singular points arise is as intersections of components of reducible curves. Lemma 6.7 Let p be a point of multiplicities m, n on the curves f, g in lI(2. Then p has multiplicity m + n on the product h = f g. In particular, any intersection is singular on h.

Since multiplicities are invariant under affine mappings, It IS no restriction to suppose that p = (0,0). By Lemma 6.4, we can write

Proof

6.3 Singular Points: Exercises

83

= Fm + HOT, g = Gn + HOT where Fm , Gn are non-zero forms of respective degrees m and n. Then h = H m+n + HOT, where H m+n = FmG n is a non-zero form of degree m+n. It follows immediately from Lemma 6.4 that p has multiplicity m + n on h. D

f

For the reader with some knowledge of calculus in several variables we point out that the Implicit Function Theorem provides a description of a simple point p = (a,b) on a real algebraic curve f(x,y). By that result, there exist convergent power series x(t), y(t) defined on a neighbourhood of t = 0, with a = x(O), b = y(O) for which f(x(t),y(t)) == 0 identically in t, and for which the parametric curve z(t) = (x(t), y(t)) is regular. In other words, in a neighbourhood of p, the set defined by f(x, y) = 0 is the image of a regular parametrized curve. Although this elegant description fails at singular points, the interested reader will find a natural generalization in more advanced texts using the idea of 'Puiseaux series'. Here is an application. Example 6.14 This is one of the very few points in this text where we will make use of the Euclidean structure on the real affine plane lR2 • The open disc B(p : £5) of radius £5 > 0, centred at the point p E lR2 is defined to be B(p : £5) = {q E

]R2 :

Ip - ql < £5}

where Ip - q I denotes the usual Euclidean distance between the points p, q. A point p on a curve f in ]R2 is isolated when there exists a real number £5 > 0 such that p is the only point in B(p : £5) which lies on f. We claim that an isolated point p on a curve f is necessarily singular. Indeed, were p simple the intersection of the zero set of f with a sufficiently small disc centred at p would be the image of a regular parametrized curve, and (by the above description) p would fail to be simple.

Exercises 6.3.1

6.3.2

Find the singular points of the algebraic curve in lR2 given by f(x,y) = y2 + 2x 2 - x 4 = 0, and sketch the curve. In each of the following cases, show that the curve f(x, y) in ]R2 has just one singular point. (i) f(x,y)=x 3 +x 2 +y2 (ii) f(x,y) = x 6 - x 2y 3 _ y5 (iii) f(x, y) = (x 2 + y2)2 - y(3x 2 _ y2).

84

6.3.3

6.3.4

6.3.5

6.3.6

6.3.7

6.3.8

6.3.9

6.3.10

Singularities of Affine Curves

In each of the following cases, show that the curve f(x,y) in ffi,2 has just one singular point. (i) f(x, y) = (x 2 + y2)3 - 4x 2y2 f(x,y) = x 2y2 + 36x + 24y + 108 (ii) (iii) f(x,y) = y3 + x 2 + 2xy - 6y2 - 2x + 14y -11. In each of the following cases, find all the singular points of the given algebraic curve f(x, y) in ffi,2, and show that they are double points. (i) f = (x 2 - 1)2 - y2(3 + 2y) (ii) f = x 2(3y - 2x 2) - y2(1 _ y)2. Let a, b be positive real numbers. The quartic curve f defined by a2y2 - b2x 2 = x 2y2 is known as the bullet nose. Show that the curve has exactly one singular point in ]R2, and no further singular points in «:2. Show that the astroid f = (1 - x 2 - y2)3 - 27x 2y2 has exactly four singular points in ]R2, and exactly four more when regarded as a curve in ee 2 . Show that p = (cx,O) is the only singularity of the cubic curve f = x(x - cx)2 + y2(a - cx + x) in ]R2. (f is the pedal curve of the standard parabola y2 - 4ax with respect to p.) Show that p = (cx, 0) is the only singularity of the quartic curve f = {x(x - cx) + y2}2 - (x - cx)2 - y2 in ffi,2. (f is the pedal curve of the unit circle x 2 + y2 = 1 with respect to the pedal point p.) This exercise relates to Example 2.9. Let ¢(x) be a polynomial of degree d 2 3 with coefficients in IK. Verify that every singular point of the affine curve f = y2 - ¢(x) in IK2 must lie on the line y = o. Show that the point (a,O) is a singular point of f if and only if a is a repeated root of ¢(x). Use these results to show that the curve f = y2 - (5 - x 2)(4x4 - 20x 2 + 25) in ]R2 has exactly two singularities. Let f be a curve of degree d, having at least m distinct singular points lying on a line 1. Show that if 2m > d then 1is a component of f.

7 Tangents to Affine Curves

In this chapter we introduce 'tangents' at a point p on an affine curve f via the intersection numbers of Chapter 6. Intuitively, a tangent at p is a line I which has higher contact with f than one would expect. The most general case (in some sense) is when p is a simple point on f, and there is a unique tangent line I given by an explicit formula; this provides the content of Section 7.2. Normally the tangent I at a simple point p has contact of order 2 with f at p, but when it is ~ 3, we have very special points on f called 'flexes', which play a potentially important role in understanding the geometry of a curve. In the remainder of the chapter, we give a number of examples illustrating how to find the tangents to affine curves at singular points p.

7.1 Generalities about Tangents Let p be a point of multiplicity m on an algebraic curve f in OC2 • Then automatically I(p,f,/) ~ m for every line I through p. A tangent line (or just tangent) to f at p is a line I through p for which I(p,f,I) ~ m+ 1. We say that two curves f, g are tangent at a point p of intersection when there exists a line I which is both a tangent to f at p, and a tangent to g at p: two curves f, g are tangent when there exists an intersection point p at which they are tangent. Our first proposition reduces the problem of determining tangents to that of factorizing a binary form.

Lemma 7.1 Let p = (a, b) be a point of multiplicity m on an algebraic curve f(x,y) in OC2 , and let g(X, Y) = f(X + a, Y + b). The tangents to f at p are the linear components of the LOT in g(X, Y), translated to p. In particular, when p = (0,0) the tangents at p are the linear components of the LOT in f(X, Y) itself. 85

Tangents to Affine Curves

86

Proof Write g = Gm+ Gm+1 +... + Gd where each Gk is a binary form of degree k, and Gm =1= O. Let I be the line through p = (a, b) in the direction (X, Y); I is given parametrically as x(t) = a + tX, y(t) = b + tY, and is defined by -Y(x - a) + X(y - b) = O. The intersection polynomial associated to the parametrization is cjJ(t)

f(a

+ tX,b + tY)

g(tX, tY)

+ Gm+1(tX,tY) + ... tmGm(X, Y) + t m+1 Gm+1 (X, Y) + ....

Gm(tX,tY)

I is a tangent if and only if I (p, f, I) 2 m + 1, i.e. t m+1 is a factor of cjJ(t), i.e. Gm(X, Y) = 0, i.e. -Yx +Xy is a linear factor of Gm. The result follows, as the translate to p is 1. D

7.2 Tangents at Simple Points Consider first the case m = 1 of a simple point p on a curve Maclaurin expansion of the polynomial g(X, Y) at the origin is g(X, Y) = fx(p)X

+ fy(p)Y +

f.

The

HOT

and there is a unique tangent line which is given by the formula

(x - a)fx(p) + (y - b)fy(p)

= o.

Example 7.1 Let P = (a, b) be a point on the line f = etX + f3 y + y in JK2 , so eta + f3b + y = O. Then fx = Ct, fy = f3 and the tangent at P to the line is defined by (x - a)fx(p) + (y - b)fy(p), i.e. etX + py + y. Thus the tangent to a line at any point is the line itself. Example 7.2 Consider the circle f = x 2 + y2 - 1 in JR2. Singular points are given by 0 = f = x 2 + y2 - 1, 0 = fx = 2x, 0 = fy = 2y. Clearly, the curve is non-singular. The tangent at (a, b) on the circle has the equation (x - a).2a + (y - b).2b = 0, i.e. ax + by = a2 + b2 = 1. In particular, the tangent at the point (1,0) has equation x = 1. Example 7.3 Here is a neat illustration of the power of elementary geometric ideas in the real affine plane. An ellipse can be inscribed in any given parallelogram. By this we mean that given a parallelogram, there exists an ellipse which is tangent to each of the four lines comprising the sides of the parallelogram. Suppose the parallelogram has vertices A,

7.2 Tangents at Simple Points D

87

A

affine map ~

c

B

c'

B'

Fig. 7.1. Inscribing an ellipse in a parallelogram B, C, D as in Figure 7.1. By the Three Point Lemma there is a unique affine map ¢ taking A, B, C respectively to A' == (1,1), B' == (1,-1), C' == (-1, -1) and necessarily mapping D to D' == (-1, 1). For the

parallelogram A', B', C', D' the italicized assertion is clearly true: the unit circle x 2 + y2 = 1 is an inscribed ellipse, tangent to each of the four sides. Under the inverse mapping ¢-l, the circle is mapped to an ellipse. Moreover, since affine maps preserve tangency, that ellipse is likewise tangent to each of the four sides of the original parallelogram. Let p be a simple point on a curve f in ]I{2. Then the intersection number of the unique tangent line to f at p with f is ~ 2. In general, the intersection number will be exactly two, but at exceptional points on the curve one might expect that number to take higher values. The point p is a flex of f when the intersection number is ~ 3; p is an ordinary flex when the intersection number is = 3, and an undulation when it is 2:: 4. In Chapter 13 we will take up the question of how to find flexes, at least in principle. For the moment, we content ourselves with the very special case of curves which are graphs of polynomials, recovering a standard calculus test for their inflexional behaviour. Example 7.4 Given a polynomial p(x) over ]I{ the graph in ]I{2 is the zero set of the curve f(x,y) == y - p(x). The curve f is non-singular, and by Section 7.2 the tangent to f at the point p = (a, p(a)) has equation y = (x - a)p'(a) + p(a). The intersections of the tangent with f at pare given by ¢(x) == 0 where, using the Taylor expansion of p(x), ¢(x) = p(x) - (x - a)p'(a) - p(a) =

~(x -

a)2p"(a)

+

HOT.

88

Tangents to Affine Curves

°

Thus x = a is a root of the equation ¢(x) = of multiplicity ~ 2, and has multiplicity ~ 3 if and only if p"(a) = 0. We conclude that the graph of a polynomial p(x) has a flex at x = a ~f and only if p"(a) = 0. For instance for n ~ 2, the graph of the polynomial p(x) = x n in JK2 has tangent y = at (0,0), and (0,0) is a flex if and only if = p'(O), i.e. if and only if n ~ 3. In particular, y = x 3 has an ordinary flex at x = 0, and y = x 4 has an undulation at x = 0.

°

°

Exercises 7.2.1

7.2.2

7.2.3

Let m, n be posItIve integers. Show that the curve f(x,y) xmyn - 1 is non-singular. Let p be a point on f, and let q, r be the points where the tangent line at p meets the x-axis, y-axis respectively. Show that pq / pr is constant, and find its value. (pq is the distance from p to q, and pr is the distance from p to r.) Find the four lines through (0,0) which are tangent to the cubic curve y2 = x(x 2 + 7x + 1) in ]R2 at some other point. Sketch the curve, and the four lines. Let a, b be positive real numbers. Show that the hyperbola x 2 / a2 - y2 /b 2 = 1 in ~2 is non-singular, and find the equation of the tangent line at the point (a, f3). Let (a, f3) be a point on the hyperbola with f3 =1= O. Find functions x( a) and y(f3) such that (x(C{),O) and (0, y(f3)) are the respective points where the tangent line meets the x-axis and the y-axis. Find a quartic curve f(x,y) in ~2 with the property that the point (x(a), y(f3)) lies on the curve, for any choice of (a,f3). Show that any point (x,y) on f(x, y) satisfies the relation -a < x < a. Let (x, y) be any point on the curve f(x, y) with (x, y) =1= (0,0). Show that x = x(C{) for some C{ with C{ < -a or C{ > a. Deduce that there is a point (a, f3) on the hyperbola with f3 =1= 0 for which x = x(a), y = y(f3). Sketch the zero set of the curve f (x, y). (The curve f is the bullet nose of Exercise 6.3.5.)

7.3 Tangents at Double Points Let us return to Lemma 7.1, and look more carefully at tangents to curves at singular points. We have a point p = (a,b) of multiplicity m on a curve f in JK2, and obtain the tangents as the linear factors of the LOT in the polynomial g(X, Y) = f(X + a, Y + b). In the case m = 1 of a simple point, the LOT are linear, and we have a unique tangent, independently

7.3 Tangents at Double Points

89

o acnode

crunode

cusp

Fig. 7.2. Types of real double point

of the ground field IK. But when p is a singular point the LOT yield a form of higher degree, and the situation is more complicated. It is worth looking at the case m = 2 of double points in detail. In that case, the LOT have a Taylor expansion g(X, Y) = X 2 fxx(p)

+ 2XY fxy(p) + y 2 fyy(p) +

HOT

and the tangents are obtained by factorizing the quadratic part. There are two possibilities: the tangents are distinct (and p is said to be a node) or the tangents coincide (and p is said to be a cusp); in the case of a cusp the repeated tangent is called the cuspidal tangent. The discriminant ~ of the quadratic part given below distinguishes nodes (~ =1= 0) from cusps (~=

0)

~ = f xy(p)2 - f xx(p)fyy(p).

Example 7.5 The reader will readily verify that p = (-2,2) is a singular point of the sextic f(x, y) = y3(4 - y)3 - 4x 4 (x + 3)2 in ([:2. Here, writing x = X - 2, y = Y + 2, we get g(X, Y)

= f(X

- 2, Y

+ 2) = -24(X 2 + 2y 2 ) + HOT. LOT in g(X, Y) are X 2 + 2y 2 . Over

Thus p is a double point. The the real field the LOT do not factorize, and there are no tangents. But over the complex field there are factors X ± iJ2 Y, yielding distinct tangents (x + 2) ± iJ2(y - 2) = 0, so p is a node. Over the real field there are further distinctions. Any curve f in ~2 can be considered as a curve in ([:2, and any point p in ~2 on f represents a real point in ([:2. Suppose p is a double point on the complex curve. Then either p is a node, or it is a cusp. In the case of a cusp, the (unique) tangent line is real. But in the case of a node, the tangent lines are either both real, or complex conjugate. In the former case, we say that p is a crunode on the real curve f, and in the latter case, that p is an acnode. Figure 7.2 illustrates instances of the three types of real double

Tangents to Affine Curves

90 y

y

y

x

A< 0 Fig. 7.3. Double points in a family of cubics

point. There is more to these pictures than meets the eye: for the acnode and crunode, it can be shown that they are 'correct', in a strictly defined technical sense, and the same is true for the cusp, provided it is 'ordinary' in the sense of Exercise 7.4.3.

x 3 + AX 2 in }R2 has a unique singular point p = (0, 0) of multiplicity 2. For A > 0, there are distinct real tangents, and p is a crunode; for A < 0, there are distinct complex conjugate tangents, Example 7.6 The cubic y2

=

and p is an acnode; for A = 0, the point p is a cusp. (Figure 7.3.)

Example 7.7 The quartic y2

+ x4 + y4 = 0 in }R2

has a unique singular point p = (0,0), namely a cusp with repeated tangent y = O. That may seem rather strange at first, since p is the only point in the zero set! It is better to think of f as a curve in C 2 (so having an infinite zero set) whose tangent at p happens to have a real equation.

Exercises 7.3.1

7.3.2

7.3.3

Show that the cubic curve f = (x + y)3 - (x - y)2 in IR2 is irreducible. Find the singular points of !, and the tangents at these points. Show that the cubic curve! = x 3 + y3 - 3x 2 - 3y2 + 3xy + 1 in }R2 is irreducible. Show that! has exactly one singular point, and find the tangents at that point. Show that the cubic curve f = y3_y2+x3-x2+3xy2+3x2y+2xy in }R2 has exactly one singular point, and determine the tangents at that point.

7.4 Tangents at Points of Higher Multiplicity

7.3.4

7.3.5

7.3.6 7.3.7

7.3.8

7.3.9

91

A cubic curve f in C 2 is given by f = x 2y + xy(y -1) + (y -1)2. Show that f has exactly one singular point, at p = (0, 1). Show that p is a node of f, and that the tangents to f at pare y = wx + 1, Y = w 2 x + 1 where w is a primitive complex cube root of unity. The Bernouilli lemniscate is the quartic curve in JR2 defined by f = (x 2 + y2)2 - x 2 + y2. Show that the curve has exactly one singular point, namely a crunode at (0, 0). Are there any further singular points in ee 2 ? Show that the quartic curve f = (x 2 - 1)2 - y2(3 + 2y) in JR2 has precisely three singular points, all of which are crunodes. Show that the quartic curve f = x 2(3y - 2x 2) - y2(1 - y)2 in JR2 has two singular points, one a cusp and the other a crunode. Show that there are no further singular points. In Exercise 6.3.6, it was shown that the astroid defined by the formula f = (1 - x 2 - y2)3 - 27x 2y 2 has exactly four singular points in JR2 and exactly four further singular points in C 2. Show that all four singular points in JR2 are cusps, and find the tangents at these cusps. Show that the four singular points in ee 2 are nodes. (You do not need to find the tangents at the nodes.) Let ¢(x) be a· polynomial of degree d ~ 3 with coefficients in oc. In Exercise 6.3.9, it was shown that any singular point of the curve f = y2 - ¢(x) in OC2 lies on the line y = 0, and that the point p = (a, 0) is singular on f if and only if a is a repeated root of ¢(x). Assuming p is singular, show that it is a double point, and is a cusp if and only if a is a zero of ¢(x) of multiplicity ~ 3.

7.4 Tangents at Points of Higher Multiplicity Let us return once more to Lemma 7.1, and consider the general situation. We have a point p = (a,b) of multiplicity m on a curve f in OC2 , and obtain the tangents as the linear factors of the LOT in the polynomial g(X, Y) = f(X + a, Y + b). Consider first the situation over the complex field, where the LOT have a unique factorization

(t) with distinct ratios (ak : bk ), and J11 + ... + J1s = m. Then Gm(X, Y) = 0 if and only if akX + bk Y = 0 for some k. Thus for each linear factor

92

Tangents to Affine Curves y

x

Fig. 7.4. The four-leaved clover

akX + bk Y of Gm(X, Y), we have a unique tangent to j at p of multiplicity Ilk, namely the line ak(x - a) + bk(y - b) = O. Counting tangents properly (in the sense that we add up their multiplicities) we see that over the complex field there are exactly m tangents at p, so in particular at least one. The most general situation (in some sense) is when p is an ordinary point on j, i.e. it has exactly m distinct tangents. (Thus a node is an ordinary double point.) Next consider the situation over the real field. The first remark to make is that there may be no tangents at p. (Example 7.6.) However, Gm(X, Y) has a unique factorization (t) over the complex field, where the ratios (ak : bk ) are either real, or occur in complex conjugate pairs; then for each real ratio (ak : bk ) we have a corresponding tangent ak(x - a) + bk(y - b) = 0, and can define its 'multiplicity' as in the complex case. Example 7.8 The sextic curve j = (x 2 + y2)3 - 4x 2y2 in ]R2 is the fourleaved clover. (Figure 7.4.) The curve has exactly one singular point, namely the quadruple point p = (0, 0) with two tangents x = 0, y = 0 both of multiplicity 2. Example 7.9 The idea behind the concept of a 'flex' can be extended from simple to singular points. Let p be a point of multiplicity m on a curve j in OC2 • Then for any line 1 through p, we have I(p,j, 1) 2 m, and 1 is a tangent to j at p if and only if I(p,j, 1) 2 m + 1. A tangent 1 at p is ordinary when l(p,j, 1) = m + 1, and inflexional when l(p,j, 1) 2 m + 2. When m = 1, this says that p is a 'flex'. For instance, both tangents x = 0,

7.4 Tangents at Points of Higher Multiplicity: Exercises

93

y = 0 at p = (0,0) to the four-leaved clover of Example 7.8 meet the curve at p with intersection number 6, so are inflexional.

Suppose we have a point p of intersection of two curves!, g in 1I{2. The question arises: what are the tangents at p to h = f g? And the answer is given by the following proposition. Lemma 7.2 Let p be a point of intersection of two curves f, g in OC2 , and let h = ! g. Then for any line 1 through p, the respective intersection numbers i, j, k of 1 at p with !, g, h are related by k = i + j. Moreover the tangents, to h at p comprise the tangents to f at p, and the tangents to g at p. Proof Since multiplicities are invariant under affine mappings, it is no restriction to suppose that p = (0,0). Let 1 be any line through p, parametrized as x = x(t), Y = y(t), and let a(t), P(t), y(t) be the intersection polynomials associated respectively to f, g, h. Then y(t)

h(x(t),y(t)) = fg(x(t),y(t)) f(x(t), y(t))g(x(t), y(t))

= a(t)fJ(t).

We can write a(t) = tia(t), f1(t) = tjb(t) where a(O) =1= 0, b(O) =1= 0. Then y(t) = ti+jc(t) where c(t) = a(t)b(t) has the property that c(O) =1= 0; it follows that k = i + j. Now let m ~ i, n ~ j be the multiplicities of p on f, g. Then p has multiplicity m+n on h, by Lemma 6.7. According to the definitions, l is a tangent at p to h if and only if m + n + 1 ~ k = i + j, i.e. if and only if m + 1 S i or n + 1 s j, i.e. if and only if 1 is a tangent at p to !, or 1 is a tangent at p to g. The result follows. D

Exercises 7.4.1

7.4.2

7.4.3

Let a be a non-zero complex number. Show that the affine curve ! = y3(4a - y)3 - 4x 4 (x + 3a)2 in C 2 has five singular points, namely two triple points, a node, and two cusps. Verify the statement made in Example 7.8, namely that in JR2 the four-leaved clover f = (x 2+ y2)3 -4x 2y2 has exactly one singular point, a quadruple point at the origin. Show that there are no further singular points in C 2 . Let p be a cusp on an algebraic curve f in OC2 , with tangent line t. Show that I(p,f, t) z 3. p is said to be an ordinary cusp when t is an ordinary tangent. In the case when p = (0,0) and t is the line y = 0, show that p is an ordinary cusp if and only

94

7.4.4

Tangents to Affine Curves

if fxxx(O, 0) =1= O. (Write down explicitly the quadratic and cubic terms in f.) Let p be a cusp on an algebraic curve f in OC2 • Show that if p is ordinary, it is not possible to have more than one irreducible component of f passing through p. Give an example of a curve f which has a cusp p through which pass two irreducible components of f.

8 Rational Affine Curves

Lines have the rather special property that they can be parametrized by polynomial functions x(t), y(t), indeed by functions x(t) = Xo + Xlt, y(t) = Yo + Ylt. Likewise, the parabola y 2 = X can be parametrized as x(t) = t 2, y(t) = t. However, this pattern soon breaks down. Example 8.1 We claim that the conic x 2 + y2 = 1 in }R2 cannot be polynomially parametrized, in the sense that there do not exist nonconstant polynomials x = x(t), y = y(t) with x 2+y2 = 1. (We suppress the variable t for concision.) Suppose that were possible. Differentiating this identity with respect to t, we would obtain a second identity x' x + y' y = 0, where the dash denotes differentiation with respect to t. Think of these identities as two linear equations in x, y. Thus we obtain xz = y', yz = -x' where z = xy' - x'y. Write d, e, f for the degrees of the polynomials x(t), y(t), z(t). Assume z(t) is not zero, as a polynomial in t. Then, taking degrees in these relations, we obtain d + f = e - 1, e + f = d - 1 and hence f = -1, which is impossible. Thus z(t) is zero, implying that x'(t), y'(t) are zero, and hence that x(t), y(t) are constant, which is the required contradiction. If we replace 'polynomial' functions by 'rational' functions, we obtain a much more useful concept, fundamental to the theory of algebraic curves. Recall that a rational function of t is one which is a quotient u(t)/v(t) of two polynomials u(t), v(t) with non-zero denominator v(t). Example 8.2 In ~2 consider the circle x 2 + y2 = a2, and the point p = (-a, 0) where a > O. The line x = -a is the tangent at p. Any other line through p has the form y = t(x + a) for some scalar t and meets the circle at p, and some other point, whose coordinates depend on t. To find 95

96

Rational Affine Curves y

Fig. 8.1. Rationality of circle and hyperbola

the second point, substitute in the equation of the circle to get

+ t 2 )X 2 + 2at2 x + a2 (t 2 - 1) = O. x = -a must be a root, so (x + a) must be a factor. By inspection, the other factor is (1 + t 2 )X + a(t 2 -1), so the coordinates of the second point (1

of intersection are 2

") _ a( 1 - t ) x (t 1 2'

+t

y(t) = t(X(t)

+ a) =

2at -1- 2 ·

+t

p = (-a, 0) is the only point on the circle that does not correspond to

any value of t. Working over the complex (instead of the real) field, we obtain the same formulas. The only difference is that then x(t), y(t) fail to be defined when t = ±i.

8.1 Rational Curves

The circle example above leads us to the following definition. Let f be an irreducible curve in OC2 . The curve f is rational when there exist rational functions x(t), y(t) satisfying the following conditions (i) For all but finitely many values of t, the functions x(t), y(t) are defined and satisfy f(x(t), y(t)) = 0. (ii) For any point (x, y) satisfying f(x, y) = 0, with a finite number of exceptions, there is a unique t for which x = x(t), y = y(t). In view of our convention, that we are working either over the real or the complex field, condition (ii) implies that the zero set of a rational curve is non-empty. Here is a simple geometric construction which shows (in principle) that non-singular conics are rational. Take a fixed point p = (rx, f3) on the conic, and consider the 'pencil' y = t(x - rx) + f3 of all

8.1 Rational Curves

97

lines through p. The construction is illustrated in Figure 8.1 for the circle and the hyperbola. Substituting the equation of the line in f(x, y) = 0, we get a quadratic in x (the intersection polynomial associated to that line) whose roots correspond to points where the line meets the conic. x = lI.. is a root, corresponding to p, so x - lI.. is a factor. The other factor can be found by inspection, and yields x in terms of t; then, substituting in y = t(x-a)+{3, we get y also in terms oft. There are two situations where the line fails to intersect the conic in a further point. The first is \vhen the line is tangent to the conic at p, and the quadratic in x has x = lI.. as a repeated root. The second situation is when the intersection polynomial has degree 1, i.e. the coefficient of x 2 in the quadratic vanishes; since that coefficient is itself a quadratic in t, that can only happen for at most two values of t.

Example 8.3 Consider the hyperbola x 2 - y2 = a 2 , and the point p = (-a, 0). The line x = -a is the tangent at p. Any other line through p has the form y = t(x + a). Substitution yields the quadratic (1 - t 2 )x 2 - 2at 2 x - a2 (l

+ t2 ) = o.

x = -a must be a root, so (x + a) must be a factor. By inspection, the other factor is (1 - t 2 )x + a(1 + t 2 ), yielding the rational parametrization

+ t2 ) 1 - t2 '

_ a(l

x( t) -

2at y(t) = 1 _ t 2 ·

p = (-a, 0) is the only point on the hyperbola that does not correspond to any value of t. The rational functions x(t), y(t) are defined for all values of t except for t = ±1, corresponding to the lines y = ±(x + a) parallel to the 'asymptotes' y = ±x. (We will have more to say about this concept in Example 12.11.) Lemma 8.1 Let f, g be affine equivalent curves in if and only if g is rational.

I[{2,.

then f is rational

Proof Since f, g are affine equivalent there exists an affine mapping ¢(x,y) and a scalar A =1= 0 for which g(x,y) = Af(¢(x,y)) for all x, y. Now suppose g is rational, so there exist rational functions x(t), y(t) satisfying conditions (i), (ii) of the above definition. Write ¢(x, y) = (X, Y), where X = px + qy + lI.., Y = rx + sy + {3 and define X(t), Y (t) by X(t) = px(t) + qy(t) + lI.., Y (t) = rx(t) + sy(t) + {3. Then X(t), Y(t) are rational, and defined whenever both x(t), y(t) are; moreover, in

98

Rational Affine Curves

that case 0 = g(x(t), y(t)) = Af(¢(x(t), y(t))) = Af(X(t), Y (t)), and hence o = f(X(t), Y(t)). It remains to show that all but finitely many points (X, Y) with f(X, Y) = 0 have the form X = X(t), Y = Y(t) for some t. Any point (X, Y) with f(X, Y) = 0 has the form (X, Y) = ¢(x,y) with g(x,y) = Af(X, Y) = O. And for all but finitely many (x,y), hence all but finitely many (X, Y), there exists a t with x = x(t), Y = y(t), hence X = X(t), Y = Y(t). D Example 8.4 Any irreducible complex conic is rational, since by Lemma 5.3 any such conic is affine equivalent to the parabola y2 = x or the general conic y2 = x 2 + 1, both of which are rational. Likewise any irreducible real conic having a non-empty zero set is rational, since by Lemma 5.2 any such conic is affine equivalent to the parabola y2 = x, the real ellipse y2 = -x 2 + 1 or the hyperbola y2 = x 2 + 1, all of which are rational. The above technique for finding rational parametrizations of conics applies in principle to cubics having exactly one singular point, i.e. any line through the singular point meets the curve at most once elsewhere. Indeed, in principle, it applies to any irreducible curve of degree d having a singular point of multiplicity (d - 1). Example 8.5 The cubic f = y2 - x 3 in ]R2 has a unique singular point p = (0,0), namely a cusp, with tangent y = O. The pencil of lines y = through p meets the curve when the intersection polynomial x 2 (t 2 -x) = with the factor x 2 corresponding to the intersection of multiplicity 2 p, and the remaining intersection given by x = t 2 , Y = tx = t 3.

at tx 0, at

Example 8.6 The folium of Descartes, i.e. the cubic f = x 3 + y3 + 3xy in ]R2 has a unique singular point at p = (0,0), namely a crunode with tangents x = 0, y = 0. (Figure 8.2.) The pencil of lines y = tx through p meets the curve when the intersection polynomial x 2 {( 1 + t 3)x + 3t} = 0, with the factor x 2 corresponding to the intersection of multiplicity 2 at p, and the remaining intersection given by -3t2

-3t

x

= 1 + t3 '

Y

= tx = 1 + t 3 .

Note that t = 0 corresponds to the tangent y = 0, which intersects the curve only at p, and when t = -1 the intersection polynomial has degree 2, and there is no further point of intersection. This corresponds to the 'asymptote' y = -x, a concept we will discuss in Section 12.6.

99

8.1 Rational Curves

x

Fig. 8.2. Rationality of the folium of Descartes

x

Fig. 8.3. Rationality of xy

+ (x 2 + y2)2

However this pattern of examples does not persist. In our final example, we present a rational quartic f in }R2 having a unique singular point at the origin. However, rationality cannot be established via the pencil of lines through the singular point - instead we consider a 'pencil' of circles. Example 8.7 Consider the quartic f == xy + (x 2 + y2)2 in IR2 . The curve f has a unique singular point, namely a crunode at p == (0,0), the zero set is depicted in Figure 8.3. We cannot establish rationality via

100

Rational Affine Curves

lines y = tx through p; for instance any such line with t < 0 meets f in exactly two points other than p. Instead, we consider the 'pencil' of circles gt = x 2 + y2 - ty centred on the y-axis and passing through p. Eliminating (x 2 + y2) between the relations f = 0, gt = 0 yields y(x + t 2y) = O. The solution y = 0 corresponds to the intersection at the origin, otherwise, substituting y = -x/t2 in gt = 0, we obtain the rational parametrization - t3

x = - -4 1+t '

x

Y

t

= -ti = 1 + t 4 ·

This example is on the level of a trick. The real question is why the 'pencil' of circles gt should have been considered in the first place. The answer lies in a set of ideas which will make perfect sense once we move from the affine to the projective plane in Chapter 9.

Exercises 8.1.1

8.1.2

8.1.3

8.1.4

8.1.5

Find a rational parametrization x = x(t), y = y(t) of the circle x 2 + y2 = 5 with the extra property that for all rational parameters t the numbers x( t) and y( t) are rational. (The point of the question is that you do need to think about which point on the circle you want to work with. The 'obvious' choices don't work; you need one with rational coordinates.) A cubic curve f in IR 2 is defined by f = ay2-xy2-ax2-x3, where a > o. Show that f is irreducible, and has exactly one singular point, namely a crunode. Find a rational parametrization for f. A cubic curve f in C 2 is defined by f = ay2 - xy2 - x 3 where a > o. Show that f is irreducible, and has a unique singular point, namely a cusp. Find a rational parametrization for f. A cubic curve f in IR 2 is given by f = x 2y + xy(y - 1) + (y - 1)2. Show that f has exactly one singular point, namely an acnode. Construct a rational parametrization for f. In Example 8.6, it was shown that the folium of Descartes, given by f = x 3 + y3 + 3xy admits the rational parametrization -3t

x = - -3 1+t '

8.1.6

-3t2 Y = 1 + t3·

Let a, b, c be the parameters of three distinct points. Show that the points are collinear if and only if abc = -1. In Example 1.8, it was shown that the pedal curve of the standard parabola y2 = 4ax where a > 0, with respect to the pedal point

8.2 Diophantine Equations p = (Ll,O) satisfies the equation of the cubic

8.1.7

8.1.8

8.1.9

8.1.10

8.1.11

8.1.12 8.1.13 8.1.14

8.1.15

101

f

= x(x - Ll)2

+

y2(a - Ll + x) in }R2. And in Exercise 6.2.1, it was shown that p is a double point of f. Find a rational parametrization for f. For any real number A =1= 1 an irreducible cubic curve f in lR2 is defined by the formula f(x,y) = x(x - A)2 + (x + 1 - A)y2. Show that f has exactly one singular point p, whose coordinates depend on A. Construct a rational parametrization for f. Show that the quartic curve f = x 4 - x 2Y + y3 in }R2 has a unique singular point, namely a triple point at the origin. Find a rational parametrization for f. Show that the quartic curve f = y(x 2 + y2) - x 4 - y4 in }R2 has a unique singular point, namely a triple point at the origin. (The curve f is the boomerang illustrated in Figure 6.3.) Find a rational parametrization for f. Show that the quartic curve f = (x 2 + y2)2 - y(3x 2 - y2) in }R2 is irreducible, and has a unique singular point, namely a triple point at p = (0,0). Find a rational parametrization of f. Let f be the quartic curve in the real affine plane }R2 defined by f(x,y) = 5x 2y2 + x 2y + xy2 - 3x 2 + y2. Show that there is a conic g(x, y) in }R2 with the property that if (x, y) =1= (0,0) and f(x,y) = 0 then g(l/x, l/y) = O. Deduce that f is rational. Find a rational parametrization for the quartic curve defined by f = x 4 - x 2y - y3. (Example 6.13.) Find a rational parametrization for the sextic curve defined by f = x 6 - x 2 y3 _ y5. Let f be an irreducible curve in ee 2 of degree d, having a singular point of multiplicity (d -1) at some point p. Why does f have no other singular points? Show, by considering the pencil of lines through p, that f is rational. (Most of the previous exercises can be viewed as special cases of this one.) Show that the quartic f = y2 - x 2(x 2 - 1) in }R2 is rational, by considering its intersections with the 'pencil' of parabolas gt = Y - tx(x - 1).

8.2 Diophantine Equations Conics appear in the problem of finding integral solutions of polynomial equations in several variables. The subject is named after Diophantus of Alexandria, working around the middle of the third century.

102

Rational Affine Curves

Example 8.8 In Example 2.2 we raised a classical problem of Greek mathematics, namely that of finding all right-angled triangles with integer sides, i.e. all positive integers X, Y, Z with X 2+ y 2 = Z2. In this extended example, we will present a complete solution of this problem, based on the fact that the circle admits a rational parametrization. We can assume our triangles are primitive, in the sense that X, Y, Z have no common factor. In that case, no two of X, Y, Z can have a common factor. If, for instance, X, Y had a common factor, they would have a common prime factor p which would divide Z2, and hence Z, contradicting the assumption that the triangle is primitive. In particular, X, Y cannot both be even. What is not quite so obvious is that X, Y cannot both be odd. The proof rests on the fact that the square of an even number is congruent to 0 mod 4, whilst the square of an odd number is congruent to 1 mod 4. If X, Y were both odd then X 2 + y 2 == 1 + 1 = 2 mod 4, so Z2 == 2 mod 4, a contradiction. It is no restriction to suppose that Y is even. The point (x,y) on the circle x 2+y2 = 1 defined by x = XjZ, y = Y jZ is then a rational point, i.e. x, yare both rational, with the fractions in their lowest terms. By Example 8.2 the circle is parametrized by 1- t 2 1 + t2 '

X=--

2t y = 1 + t2 ·

Clearly, if t is rational then x, yare rational. Conversely, suppose x, y are rational, then the first formula shows that t 2 is rational, and then the second formula shows that t is rational. We can therefore assume t is rational, say t = ujv with u, v coprime integers, and for (x, y) to lie in the positive quadrant, we need 0 :::; t :::; 1, i.e. 0 :::; u :::; v. Thus all positive rational solutions are given by

X Z

v 2 - u2 v2 + u2 '

X=-=---

Y Z

2uv + u2

y=-=--

v2

with u, v coprime integers satisfying 0 :::; u :::; v. Thus there exists a positive integer A for which

AY = 2uv, We claim that A = 1. The integer A divides v2 + u2, v2 - u2 and hence their sum 2v 2, and difference 2u 2. But U, v are coprime, so A divides 2, and either A = 1 or A = 2. We will exclude the latter case. Suppose A = 2. Since we are assuming Y is even, the middle relation shows that 4 divides 2uv, so 2 divides uv and one of u, v is even. Now u, v cannot both be

8.2 Diophantine Equations

103

even, since they are coprime, so one is even and one is odd; it follows that one of u2 , v2 is even and the other is odd, so v2 + u2 is odd. That contradicts the fact that 2 divides AZ = v2 + u2 , establishing that A = 1, and yielding the complete solution Y = 2uv,

Here are some of the simplest primitive triangles, obtained by taking u < v S 5, the first entry providing the familiar 3,4,5 triangle of school geometry. u 1 2 1 3 2 4

v 2

3 4 4 5 5

X

Y

3 5 15 7 21 9

4 12 8 24 20 40

Z 5

13 17 25 29 41

It is worth pondering this example a little longer. It shows that there are infinitely many rational points on the conic x 2 +y2-1. More generally, the argument shows that if we start with a conic having rational coefficients and apply the above geometric construction starting from a rational point, then we will establish the existence of infinitely many rational points on that conic. Thus (in principle) such a conic has either no rational points, or infinitely many; the former case can arise. Example 8.9 Consider the conic x 2 + y2 = 3. Suppose this has a rational point x = X /Z, y = y /Z. (Clearly, we can suppose that the denominators are the same.) Thus X 2 + y 2 = 3Z 2 • We can assume that X, Y, Z have no common factor. We claim that 3 divides neither X nor Y. For if 3 divides X then, since 3 divides 3Z 2 we see that 3 divides Y. But then 9 divides X 2 + Y 2 = 3Z 2 , so 3 divides Z 2, and hence 3 divides Z, contrary to assumption. It follows that X == ±1 mod 3, Y == ±1 mod 3 so X 2 == 1 mod 3, y 2 == 1 mod 3 and X 2 + y 2 == 1 + 1 = 2 mod 3, so X 2 + y 2 cannot be divisible by 3, a contradiction. Thus our conic has no rational points, otherwise expressed, the zero set in (Q? is empty. On an intuitive level this example is very surprising, the circle manages to weave its way through all the points with rational coordinates! Example 8.10 A famous problem of number theory is to find all positive integers X, Y, Z with x n + y n = zn, where n 2 3. (The Fermat

104

Rational Affine Curves

Problem.) Equivalently, one seeks positive rational points x = X /Z, y = Y /Z on the Fermat curve x n + yn = 1, of degree n. The curve is named after the French mathematician Fermat (1601-1665) who wrote in the margin of one of his books that he had found a 'truly marvellous proof' that for n ~ 3 the equation has no positive integer solutions. For over three centuries mathematicians tried to discover Fermat's 'proof', without success. The technique of Example 8.8 no longer works, since (as will be shown in the final chapter) the curve cannot be rationally parametrized for n ~ 3. As the years passed, larger and larger integers N were found with the property that Fermat's Conjecture held for all n < N; indeed, in recent decades, a small army of computer scientists dedicated themselves to Fermat's 'conjecture'. In 1983, the German mathematician Faltings established general results, one of whose consequences is that for a given n ~ 4, there are at most finitely many (positive) rational points on the Fermat curve. And finally in 1996, the English mathematician Wiles showed that Fermat's conjecture does indeed hold. Example 8.11 We can pursue the idea of rational parametrization to find rational solutions of some Diophantine equations of higher degree. Consider, for instance, the cubic y2 = x 3 + x 2 , having just one singular point, namely a crunode at the origin. Parametrizing this via the pencil of lines y = tx through the singular point we obtain the rational parametrization x = t 2 - 1, y = t 3 - t. Clearly, by taking rational values of t we obtain points on the cubic with rational coordinates, and conversely all such points arise in this way. But more is true. Taking integer values of t we obtain points (x, y) on the cubic with integer coordinates. Conversely, let (x, y) =1= (0,0) be a point on the cubic with integer coordinates. Then the line y = tx joining it to the origin has a rational slope t. But then x = t 2 - 1, so t 2 is an integer, and hence t is an integer as well.

This approach to finding rational points depends on the fact that the curve can be rationally parametrized. The cubic of the next example cannot be rationally parametrized, though the reader will have to wait till the final chapter for a proof; however, that does not stop us finding some rational points. Example 8.12 On the non-singular cubic y2 = x 3 + 17 one can certainly spot some 'obvious' rational points, such as a = (4,9), b = (2,5), c = (-1,4). But enthusiasm for this approach is likely to wane long before you reach such solutions as (5234,378661), indeed you need an II-digit

8.2 Diophantine Equations: Exercises

105

calculator even to check this is a solution! A more profitable philosophy is that of constructing new rational points from old, via the classical secant method of taking the line through two given rational points and looking for a third point where the line meets the cubic. For instance, the line joining a, b is y = 2x + 1, and eliminating y between this and the curve yields the cubic x 3 - 4x 2 - 4x + 16 = O. This is satisfied by x = 4, x = 2; the third root is determined by the fact that the sum of the roots is 4, giving x = -2. Substituting back in the line we get y = -3, giving us a new rational point d = (-2, -3). It is clear from the method that it is general: if the line joining two distinct rational points on a cubic curve (with rational coefficients) produces a third point, then that point is rational. It was a fluke that d has integer coefficients, the line joining b, c produces the rational point e = (-8/9,109/27). The secant method is attractive from the computational viewpoint, in the sense that it can be implemented on a computer. It is also attractive from the algebraic viewpoint, an idea we will pursue in Chapter 17, in the projective context. Of course for the secant method to produce anything new we need to start from at least two rational points, as in the above example. What if we can only spot one rational point? The way forward is the tangent method whereby the secant joining two points is replaced by the tangent line at a single point.

+ 2x - 2, one can spot the rational points (1, ±1). The secant method yields nothing, since the line joining these points is x = 1, which meets the curve only at these points. However the tangent method is productive. The tangent at a = (1,1) is 5x-2y-3 = 0, and eliminating y between this and the curve we obtain the cubic 4x 3 - 25x 2 + 38x - 17 = o. We know that x = 1 is a repeated root, and the third root is determined by the fact that the sum of the roots is 25/4, yielding x = 17/4: substituting back in the tangent equation gives y = 73/8, producing a new rational point (17/4,73/8).

Example 8.13 On the non-singular cubic y2

= x3

And what happens when one cannot spot a rational point? Surprisingly, at the time of writing no algorithm is known for deciding whether a cubic (with rational coefficients) possesses a rational point. Exercises 8.2.1

In Exercise 8.1.13, we found a rational parametrization for the sextic curve f = x 6 - x 2 y3 - y5. Use this rational parametrization to find all integer solutions of the equation f(x, y) = o.

106 8.2.2 8.2.3

Rational Affine Curves Spot a rational point on the cubic y2 = x 3 - 3x 2 + 3x + 1, and use the tangent method to find at least one more rational point. Spot a rational point on the cubic x 3 - 3x 2y + 5y2- 2y = 0, and use the tangent method to find at least one more rational point.

8.3 Conics and Integrals One of the early aims of integration theory was to find explicit formulas for integrals r(t) dt of the functions r(t) which arose naturally in physical problems. It was realized that this could be achieved for the class of real rational functions r(t) = u(t)lv(t) with u(t), v(t) real polynomials in t. Indeed it is proved in algebra texts that any rational function can be expressed as a linear combination of 'partial fractions' of the forms

J:

1 (t - a)P'

bt+ c

where t 2 + dt + e is irreducible. All such expressions can be explicitly integrated (the methods are presented in calculus texts) so the same is true for any rational function r(t). However, numerous physical problems give rise to integrals which, although they fail to have rational integrands, are at least capable of being reduced to such integrals. A simple example is b dx

l

~1

a

+ x2 ·

It is an elementary exercise to check that the substitution x reduces the integral to one of the form

=

2tl(1 - t 2)

rd~

Jc

1 - t2

with a rational integrand. In fact (as calculus texts point out) this substitution applies to a much wider class of integrals; it will reduce any integral

l

b

R(x,y)dx

(*)

where R(x,y) is a rational function of x,y, and y = ~1 + x 2 , to one with a rational integrand. In the above example R(x,y) = 1/y. Although the rational substitution x = 2t/(1 - t 2) is presented in calculus texts as a 'trick' for evaluating integrals, it has a very clear underlying geometry. Firstly x, y satisfy the equation of a hyperbola

8.3 Conics and Integrals y2 -

X

107

2 = 1, and secondly, the hyperbola is a rational curve. Using the

pencil of lines y = tx + 1 through the point (1,0) we see that the 'upper' branch of the hyperbola is parametrized by the formulas below, with -1 < t < 1, 2t 1 + t2 X = 1 _ t2 ' Y = 1 - t2 . Having grasped the geometric idea we see that, in principle, we ought to be able to handle any integral (*) where R(x, y) is a rational function of x, y and y = Vax2 + f3x + y. Indeed x, yare then related by y2 = ax 2 + f3x + y defining a real conic which can be rationally parametrized, at least provided it is irreducible and has real points. More generally, this argument will apply to any such conic R(x, y), for by Lemma 5.2 it can be put into the shape y2 = ax 2 + fJx + y by affine transformations.

9 Projective Algebraic Curves

One of the main functions of this book is to place algebraic curves in a natural setting (the complex projective plane) where they can be studied easily. For some readers, particularly those whose background is not in mathematics, this may prove to be a psychological barrier. I can only assure them that the reward is much greater than the mental effort involved. History has shown that placing algebraic curves in a natural setting provides a flood of illumination, enabling one much better to comprehend the features one meets in everyday applications. Let me motivate this by looking briefly at the important question of understanding how two curves intersect each other. The simplest situation is provided by two lines. In general, you expect two distinct lines to meet in a single point. But there are lines (x = 0 and x = 1 for instance) which do not intersect. This really is a nuisance. It would be much nicer to say that these lines intersect at a single point, namely a 'point at infinity'. In this chapter, we will extend the ordinary affine plane to a 'projective plane' by adding points at infinity, and gain much as a result.

9.1 The Projective Plane The construction is based on the following intuition. Think of the affine plane OC2 as a plane L in OC 3 which does not pass through the origin 0, and let La be the parallel plane through o. Then we have a natural one-to-one correspondence between points in JI(2, and lines through the origin 0 in JI(3 not in La. To a point in L we assign the unique line through 0 and that point, and conversely, to a line through 0 not in La we assign the point where it meets L. (Figure 9.1.) In this way, we conceive of lines through 0 in OC 3 in La as in some sense 'points at infinity' in JI(2. That motivates the following formal definitions. 108

9.1 The Projective Plane

109

Fig. 9.1. Affine plane in 3-space

The projective plane pJI(2 is the set of lines through the origin 0 in These lines are called the points of POC2 . Given a non-zero vector X = (Xl, X2, X3) in OC 3 there is a unique line through X, 0 determining a unique point in pJI(2, denoted by (Xl : X2 : X3). Beware, there is no point (0 : 0 : O)! We call X a representative, and Xl, X2, X3 homogeneous coordinates for the point. Homogeneous coordinates are not unique; for any non-zero scalar A, the vector AX represents the same point in POC2 . Thus, given two points A = (al : a2 : a3), B = (b i : b2 : b3) in POC2 the relation A = B means that there exists a scalar A =1= 0 for which b i = Aal, b 2 = Aa2, b 3 = Aa3. For many practical purposes we will use homogeneous coordinates labelled x, y and z. JI(3.

Example 9.1 The sphere model of p~2. Each line through the origin in meets the unit sphere x 2 + y2 + z2 = 1 in two diametrically opposite points: so p}R2 can be thought of as a sphere, with diametrically opposite points identified. We will expand on this model of the real projective plane as we proceed.

}R3

110

Projective Algebraic Curves

Exercises 9.1.1

The complex conjugate point associated to a point P = (a : b : c) in pe 2 is defined to be the point P = (a : b : c) where a, b, c are the complex conjugates of a, b, c. Show that this concept is well-defined, i.e. that the point P does not depend on the representative chosen for the point P. The point P is said to be real when P = P. Show that P is real if and only if P has a representative with real homogeneous coordinates.

9.2 Projective Lines Now consider any plane U through the origin in :oc3, so necessarily having an equation ax + by + cz = 0, where a, b, c are scalars, not all zero. Every line through the origin in U represents a point in p:oc2 . The resulting set of points in p:oc2 is called the line in p:oc2 with equation ax + by + cz = o. Examples are the coordinate lines x = 0, y = 0 and z = O. In the spherical model of the real projective plane, lines correspond to intersections of the unit sphere x 2 + y2 + z2 = 1 with planes through the origin, hence to great circles. Example 9.2 A set of points in p:oc2 is collinear when they all lie on one line. The condition for three points PI = (Xl: Yl : Zl), P2 = (X2 : Y2 : Z2), P3 = (X3 : Y3 : Z3) to be collinear is easily obtained. It is the condition for the non-zero vectors PI, P2, P3 in :oc3 to lie on a single plane through the origin, i.e. for those vectors to be linearly dependent, i.e. for the determinant Xl Yl Zl X2 Y2 Z2 = o. X3 Y3 Z3 Example 9.3 Through any two distinct points in p:oc2 there is a unique line. That is simply the statement that through two distinct lines through the origin in :oc3 there is a unique plane through the origin. To find the equation of the line through two distinct points with representatives PI = (Xl,Yl,Zl), P2 = (X2,Y2,Z2) we proceed as follows. We seek all representatives P = (x,Y,z) for which PI, P2, P are coplanar; by Example 9.2 the condition is Xl Yl Zl X2 Y2 Z2 = o. X

Y

Z

9.2 Projective Lines

For instance, if PI P2 is y = o.

= (0 : 0 : 1),

P2

111

= (1 : 0 : 1) then the line joining PI,

The next example describes the crucial property which distinguishes the affine from the projective plane.

Example 9.4 Any two distinct lines in POC2 intersect in a unique point. Indeed, two distinct lines in POC2 correspond to two distinct planes through the origin in OC 3 , so intersect in a unique line through the origin in OC 3 , i.e. in a unique point in POC2 . It is this property which marks the fundamental difference between the affine plane and the projective plane. A practical question is to find the point of intersection of two distinct lines ax+by+cz = 0 and a'x+b'y+c'z = O. By linear algebra, a solution of these equations is (X, Y , Z) where

x=\:, ;, I, y=-I;, ;, I,

z=I:, :' I·

Note that at least one of X, Y, Z is =1= 0, else (by linear algebra) the vectors (a, b, c), (a', b', c') are linearly dependent, and the lines coincide. At this point, it is worth pointing out that POC 2 is a 'projective plane' in the sense of Section 2.3. The three points (1 : 0 : 0), (0 : 1 : 0), (0 : 0 : 1) are not collinear; Example 9.3 tells us that through any two distinct points there is a unique line, and Example 9.4 tells us that any two lines intersect in at least one point.

Example 9.5 Any projective line ax + by + cz = 0 in POC 2 can be 'rationally parametrized'. (A formal treatment of these ideas will be given in Chapter 18.) Recall that a line in POC2 corresponds to a plane through the origin in OC 3 , and that any two distinct points A, B on the line correspond to basis vectors for that plane. It follows that any point on the plane has the form X = sA + tB for some scalars s, t. Writing A = (al,a2,a3), B = (b l ,b 2,b 3), X = (x,y,z) that means we can write x = sal + tb l , Y = sa2 + tb 2, z = sa3 + tb 3 for some ratio (s : t). For instance, the line z = 0 passes through the points A = (1 : 0 : 0), B = (0 : 1 : 0) yielding the parametrization x = s, y = t, z = O. As in the affine case, the parametrization is not unique, it depends on the choice of A, B. A few words are in order on the question of 'visualizing' the zero set of a projective line. Recall first the affine case. In the real case, we have the familiar lines in the IR.2 ; and in the complex case, we saw in Example 2.13

Projective Algebraic Curves

112

s

L

Fig. 9.2. Real projective line as a circle

that a line in C 2 could be thought of as a real plane. Consider now the projective case, where a line is defined by a plane through the origin in OC 3 • It will be no restriction to take the plane z = 0, so that the points of the (projective) line correspond to the (affine) lines through the origin in the (x, y)-plane, and are determined by the ratio (x : y). Provided x =1= 0 we can identify the ratio with the quotient y / x in IK. Thus we can view the points of the projective line as the elements of OC plus an extra element 00. In the real and complex cases, this gives rise to simple visualizations. Example 9.6 In the real affine plane, let S be a circle, let P be a point on S, and let L be a line not passing through P. We think of L as a copy of JR. Define stereographic projection to be the natural mapping S - {P} ~ L, which takes a point Q =1= P on S to the point on L where it meets the line through P, Q. (Figure 9.2.) Under this mapping the points of S - {P} correspond one-to-one with the elements of JR., and we can extend the bijection to the whole of S by mapping P itself to the element 00. Thus we can think of a real projective line as a circle. Example 9.7 In real affine space, let S be a sphere, let P be a point on S, and let L be a plane not passing through P. We think of L as a copy of C. Here too we can define stereographic projection to be the natural mapping S - {P} ~ L, which takes a point Q =1= P on S to the point on

9.2 Projective Lines: Exercises

113

Fig. 9.3. COlnplex projective line as a sphere

L where it meets the line throughP, Q. (Figure 9.3.) Under this mapping the points of S - {P} correspond one-to-one with the elements of C, and we can extend the bijection to the whole of S by mapping P itself to the element 00. Thus we can think of a complex projective line as a sphere. This continues the train of thought begun in Example 2.13, namely that 'curves' in the complex projective plane can be thought of as real surfaces. Example 9.8 Just for the fun of it, consider the projective plane P2~ over the field 2 2 with two elements 0, 1. There are seven points: (0 : 0 : 1), (1 : 0 : 1), (0 : 1 : 1), (1 : 1 : 1), (1 : 0 : 0), (0 : 1 : 0), (1 : 1 : 0). And there are seven lines: x = 0, y = 0, Z = 0, x = y, y = Z, Z = x, z = x + y. Think of it as in Figure 9.4.

Exercises 9.2.1

In each of the following cases, find the equation of the line joining the points A, B in PC 2 . (i)

(ii) (iii) (iv)

A A A A

= (1 : 0 : -1) = (1 : 0 : 0) = (-1 : 1 : 1) = (1 : i : 0)

B B B B

= (1 : 1 : -2) = (1 : 2 : 3) = (2 : 3 : 3) = (1 : -i : 0).

114

Projective Algebraic Curves

(1:0:0)

Fig. 9.4. The projective plane over Z2

9.2.2

In each of the following cases find the point of intersection of the two given lines in pee 2 . (i)

(ii) (iii) 9.2.3

9.2.4

9.2.5

2x + 3y + z = 0, x + y + z = 0, x + 3y - 2z = 0,

x - y + 2z = 0 x + y + 2z = 0 y + z = o.

The complex conjugate line associated to a line L = ax + by + cz in pee 2 is the line L = ax + by + cz. Show that this concept is well-defined, i.e. that the line L does not depend on the equation of L. L is said to be real when L = L. Show that L is real if and only if it has a defining equation with real coefficients. Let P be a non-real point in pee 2 • Show that the line joining P, P is real. Let L be a non-real line in pee 2. Show that the point of intersection of L, L is real. Nine points Pij in pee 2 are defined as follows, where OJ is a primitive complex cube root of unity. (These points will arise naturally in a geometric context in Example 13.6.) POO =

P10 P20

= =

(0 : -1 : 1) (1 : 0 : -1) (-1 : 1 : 0)

= (0 : -OJ : 1)

P02 = (0 : -OJ 2 : 1)

P 11 = (1 : 0 : -OJ) P 21 = (-OJ: 1 : 0)

P 12 = (1 : 0 : _OJ2) P22 = (-OJ 2 : 1 : 0).

POl

9.3 Affine Planes in the Projective Plane

115

Any two of these points determine a line. Show that in total there are twelve such lines, and that each one passes through exactly three of the points Pij. You might find it interesting to form a diagram of these nine points and twelve lines, and then compare it with that in Figure 2.2. 9.2.6

Show that the projective plane PZ~ has precisely 13 points, and precisely 13 lines. How many points lie on a line? And how many lines pass through a point?

9.3 Affine Planes in the Projective Plane We need to say something about the fundamental matter of how affine planes 'sit' in projective planes. To this end, we return to the basic intuition of Section 9.1. We start from an arbitrary affine plane L in JK 3, not through the origin 0, and denote by L o the parallel plane through O. That gave us a natural one-to-one correspondence between points in L, and lines in JK3 through 0 not lying in the plane L o. In the language of the preceding section, L o defines a line in pJK2, the line at infinity associated to L, whose points are the points at infinity; explicitly, if L has equation ax + by + cz = d then L o has equation ax + by + cz = O. Thus we obtain a natural one-to-one correspondence between points in Land points in pJK2 not lying on the line L o. In other words, we can think of the projective plane pJK2 as the 'affine' plane L, plus an associated 'line at infinity' L o. That is the underlying geometric picture. The reader should bear in mind that the 'line at infinity' depends on a choice of plane L, there is nothing unique about it. For practical purposes, we need to be more explicit about exactly how we identify L with the affine plane JK2. The idea is that, provided L is not parallel to a given coordinate axis, we can identify L with the corresponding coordinate plane (obtained by setting the coordinate equal to zero) by projection onto that plane, in the direction of the axis. The correspondence could be written down quite explicitly, by solving the equation ax + by + cz = d for one of x, y, z in terms of the other two. For instance the affine planeL defined by x + y + z = 1 is not parallel to the z-axis, and can be identified with the coordinate plane z = 0 via (x,y) "" (x,y, 1- x - y). For most practical purposes, it will be sufficient to take L to be one of the planes x = 1, y = 1, z = 1, with associated lines at infinity x = 0, y = 0, z = O. These choices give rise to three basic identifications:

116

Projective Algebraic Curves

Fig. 9.5. Hemisphere model of PIR2

choice

identification

x=1 y=1 z= 1

(y, z) (z,x) (x, y)

1'-1

1'-1

1'-1

(1 : y : z) (x : 1 :z) (x : y : 1)

Example 9.9 The hemisphere model of pffi.2. Suppose we are given a plane Lo through the origin 0 in ffi.3. Each line through 0 meets the closed unit hemisphere x 2 + y2 + z2 = 1, La 2 0, with boundary a great circle, at least once. More precisely, every line through 0 meets the open hemisphere x 2 + y2 + z2 = 1, Lo > 0 just once, whilst lines which meet the boundary great circle x 2 + y2 + z2 = 1, Lo = 0 do so twice. Thus, in contrast to the sphere model, we have only to identify diametrically opposite points on the boundary. Perhaps this represents the best visualization of pffi.2, with the open hemisphere corresponding to ffi.2, and the boundary circle to a line. Looking at the hemisphere from a distant point on the line perpendicular to L o through 0 one 'sees' the projective plane as a disc. (Figure 9.5.) Points in the interior correspond one-to-one with points in the real affine plane ffi.2; the boundary circle corresponds to a line, but 'opposite' points have to be identified. It is conceptually important to realize that, whereas the sphere model provides

9.4 Projective Curves

117

us with a single representation of the real projective plane, the hemisphere model provides a whole family of representations, one for each choice of the plane Lo.

9.4 Projective Curves In this section we will work in the projective plane POC2 , with homogeneous coordinates x, y, z. By a projective algebraic curve of degree d in POC2 we mean a non-zero form F(x, y, z) of degree d, up to multiplication by a non-zero scalar. As in the affine case, we will abbreviate the term 'algebraic curve' to 'curve'. Projective curves of degree 1, 2, 3, ... are called lines, conics, cubics, and so on. Over the real field we refer to real projective curves, and over the complex field to complex projective curves. Given a curve F we can associate to it the set C(F) = {(x,y,z) E OC 3 : F(x,y,z) = O}. This set has the crucial property of being a cone, meaning that if (x,y,z) is a point in C(F) then so too is (tx, ty, tz), for any choice of scalar t; that is immediate from the defining property F(tx,tY,tz) = tdF(x,y,z) of forms. (Lemma 3.12.) In view of this fact, it makes sense to define the zero set of F to be the set V(F) defined below; the key fact is that whether a point belongs to V(F) does not depend on the choice of representative for that point. V(F)

= {(x: y : z)

E

POC2

:

F(x,y,z)

= O}.

Recall from Section 3.4 that any form F over the field OC admits a unique factorization F = CF~l ... F;s with c =1= 0 in OC, and the Fi irreducible forms such that Fj is not a factor of Fk for j =1= k. When F is a projective curve, we refer to Fl, ... , Fs as the irreducible components of F. And, as in the affine case, the zero set of F is the union of the zero sets of Fl, ... , Fs . Example 9.10 Let F be a curve in the real projective plane p~2. We can think of the zero set in terms of the sphere model of the projective plane. Since the set C(F) is a cone, the zero set is completely determined by the 'curve' of intersection with the sphere x 2 + y2 + z2 = 1. Thus we can think of the zero set as a 'curve' on the sphere, with diametrically opposite points identified. (Figure 9.6.) For instance, when F is a line the cone is a plane through the origin, intersecting the sphere in a great circle. Likewise, we can think of the zero set in terms of the hemisphere

118

Projective Algebraic Curves

Fig. 9.6. Projective curve in the spherical model

model, where it is completely determined by the 'curve' of intersection with the hemisphere x 2 + y2 + z2 = 1, z ~ O. Thus we can think of the zero set as a 'curve' on the hemisphere, with diametrically opposite points on the boundary great circle identified. For instance, when F is a line the resulting cone intersects the hemisphere in a great semicircle, and we identify the two end points.

9.5 Affine Views of Projective Curves

The object of this section is to establish the basic relations between affine and projective curves. Suppose we have a projective curve F, and make a choice of affine plane L with equation ax + by + cz = d. Then by eliminating one of the variables x, y, z between the relations F(x,y,z) = 0, ax + by + cz = d we obtain an affine curve f in the (y, z)-plane, the (x, z)plane or the (x, y)-plane. We assume here that the coefficient of the variable in the equation of L is non-zero. We refer to f as an affine view of F. Thus, to any projective curve F, we associate a family of affine views f, one for each choice of affine plane L and each choice of variable. Example 9.11 Consider the real projective conic F = x 2 + y2 - z2. The affine views of F corresponding to the planes z = 1, x + z = 1 and x + y + z = 1 are the real ellipse x 2 + y2 = 1, the parabola y2 = 1 - 2x, and the hyperbola 2xy = 2x + 2y - 1. This example makes the point

9.5 Affine Views of Projective Curves z

119 y

z

x

the view x=l

the view y=l

x

the view z=l

Fig. 9.7. Three affine views of a cubic curve

that different affine views of a projective curve may well fail to be affine equivalent. Perhaps the best mental picture is to start from the spherical model of the real projective plane, with F defining a 'curve' on the surface of the unit sphere. An affine view is then determined by an affine plane L, with L o the parallel plane through o. The plane L o then determines a hemispherical model of the real projective plane, with the curve on the sphere giving a curve on the open hemisphere, and opposite points of intersection with the great circle L o == 0 identified. For instance, when F is a line, the intersection with the sphere is a great circle, intersecting the hemisphere in 'half' a great circle, with its end points identified. As L o changes, so the view of the 'curve' will change. In practice, we will work with the three principal affine views, meaning those associated to the affine planes x == 1, y == 1, z == 1. (Note that any point in the projective plane has a representative with either x == 1, y == 1 or z == 1 so these views cover the whole plane.) The process of obtaining the equation for f by substituting x == 1, y == 1 or z == 1 in F(x, y, z) is known as dehomogenization, since it destroys the homogeneity of F. Example 9.12 Consider, for instance, the projective cubic F == yz2 - x 3 in PIR 2 . Dehomogenizing with respect to x, y, z we obtain the three affine views of Figure 9.7, namely f == y - x 3 in the (x,y)-plane, g == yz2 - 1 in the (y, z )- plane, and h == z2 - x 3 in the (z, x)- plane. No two of these affine views are affine equivalent.

It is illuminating to think of Example 9.12 in terms of hemispherical models. If we take the hemispheres resulting from the planes x == 0,

120

Projective Algebraic Curves

the view y=l

the view x=l

the view z=l

Fig. 9.8. Three hemispherical views of a cubic curve

y

= 0, Z = 0 in JR. 3 , we obtain the three pictures in Figure 9.8 which make

it more plausible that they are different 'views' of the same curve F. That brings us to one of the key constructions in this book, namely that of reversing the above process. More precisely, given any affine curve f(x, y) of degree d in OC2 , and any affine plane L in OC 3 not through the origin, and not parallel to the z-axis, there exists a projective curve F(x,Y,z) of degree d in POC2 with the property that F(x,Y,z) = f(x,y) for every point (x,Y,z) in L. Indeed, if L is defined by an equation 1 = 1, where 1 = ax + by + cz with c =1= 0, and f(x, y) = L aijx i yj, we have only to observe that we can take F(x,y,z) = Zdf

CT' f) =

LaijxiyjZd- H .

Note that the condition c =1= 0 ensures that F has a term of degree d with non-zero coefficient. This is the process of homogenization with respect to the form l, you homogenize f by multiplying each monomial by that power of 1 necessary to bring the degree up to d. In practice, the only case of this construction we will meet is when L is the plane z = 1, so F(x,y,z)

= zdf (~,~) = Laijxiyjzd-i-j.

For instance, to the affine line f = ax + by + c we associate the projective line F = ax + by + cz. Note that f itself is one of the family of affine views provided by F; indeed, if we homogenize f to obtain F, and then dehomogenize using z again, we are back to f. However, beware! That can fail when the order of the processes is reversed. For instance, if we dehomogenize the projective curve F = z2(x 2 + z2), we obtain the affine curve f = x 2 + 1, and then homogenization with respect to z yields a different projective curve G = x 2 + z2. Of course the process of homogenization applies equally well when the variables in the affine

9.5 Affine Views of Projective Curves

121

z

y

x

x

Fig. 9.9. Two affine views of the eight-curve

plane are labelled as x, z (when we homogenize with respect to y) or as y, z (when we homogenize with respect to x). Example 9.13 Consider the cubic f = y - x 3 in PIR2 • The associated projective curve is F = yz2-x3. But, as we saw in Example 9.12, the zero sets of the principal affine views f = y - x 3, g = z2 - x 3 and h = yz2 - 1 are visually quite different. At first sight it is difficult to imagine that the views g, h have any connexion with the original curve f. In particular, the view g shows that there is a 'cusp' at infinity on f, something that one might not have expected. This example makes a very fundamental conceptual point. An affine curve f is simply one out of a very large family of affine views of the associated projective curve F. By working solely in the affine case, we deny ourselves the rich geometry provided by the projective situation. It is virtually impossible to get a genuine understanding of the geometry of an affine curve without moving into the projective situation. Here is another illuminating illustration. Example 9.14 The projective curve in PIR 2 associated to the eight-curve f = y2 - x 2 + x 4 is F = y2 z2 - x 2z 2 + x 4. This meets the line at infinity z = 0 when x 4 = 0, yielding the point at infinity Y = (0 : 1 : 0) on the y-axis. The affine view given by y = 1 is g = z2 - x 2 z 2 + x 4 , and in that view Y corresponds to the origin in the (z, x )-plane. The zero set of g is

122

Projective Algebraic Curves

easily sketched, by writing g = 0 in the form z2 = x 4 j(x 2 -1), and reveals that the origin is an isolated point on the zero set of g. (Figure 9.9.) Thus Y is an 'isolated' point on the projective curve - another unexpected revelation. There is a very simple relationship between the zero sets of an affine curve f and its homogenization F with respect to z. Since F(x, y, 1) = f(x,y) we have f(x,y) = 0 if and only if F(x,y, 1) = O. Identifying the point (x,y) in JI(2 with the point (x : y : 1) in pJI(2 (as above), we see that the zero set of F can be thought of as the zero set of f, plus the points at infinity (x : y : 0) satisfying F(x, y, 0) = O. Note that F(x, y, 0) is a binary form in x, y, so finding the points at infinity on the curve is tantamount to finding the linear factors of that form.

Example 9.15 Any projective curve F in pe 2 has an infinite zero set. Indeed the zero set of F 'contains' the zero set of any affine curve f in ee 2 obtained by dehomogenization, so is infinite by Lemma 2.1. Example 9.16 To any line ax + by + c in JI(2 we can associate a line ax + by + cz in pJI(2. The zero set of the projective line comprises that of the affine line together with a unique point at infinity (x : y : 0) for which ax + by = 0, i.e. the point (-b : a : 0). Note that the point at infinity on the line does not depend on the coefficient c. All lines parallel to ax + by + c = 0 in JI(2 have the same point at infinity. In particular, the point at infinity on the x-axis is X = (1 : 0 : 0) and the point at infinity on the y-axis is Y = (0 : 1 : 0). Example 9.17 The parabola f = y2 - x in JR2 gives rise to the conic F = y2- xz in pJR2 which meets the line at infinity z = 0 when F(x,y,O) = y2 = 0, i.e. at the single point X = (1 : 0 : 0). Example 9.18 The Maltese cross (Figure 6.6) is the quartic in JR2 defined by f = xy(x 2 - y2) - (x 2 + y2). The associated projective curve in pJR2 is F = xy(x 2 - y2) - z2(x 2 + y2), which meets the line at infinity z = 0 when xy(x 2 - y2) = O. Thus we obtain the points at infinity on the lines x = 0, y = 0, y = x and y = -x, namely (0 : 1 : 0), (1 : 0 : 0), (1 : 1 : 0) and (1 :-1 :0).

Example 9.19 The general circle in JR2 with centre (a,b) and radius r > 0 is f = (x - a)2 + (y - b)2 - r 2. The associated projective curve is F = (x-az)2+(y-bz)2- r 2z 2 in pJR2. This meets the line at infinity z = 0

9.5 Affine Views of Projective Curves: Exercises

123

when x 2 + y2 = 0, giving no points in pffi.2. However, we can also think of F as a projective curve in PCC 2 , in that case the relation x 2 + y2 = 0 yields y = ±ix, so there are two points at infinity in PCC 2 , namely the complex conjugate points I = (1 : i : 0) and J = (1 : -i : 0). The points I, J in Example 9.19 play a special role in the history of curve theory; they are called the circular points at infinity, since any circle (thought of as a complex projective curve) passes through them. The notation has its origins in the biblical names Isaak and Jakob. Real algebraic curves for which the associated complex projective curve passes through I, J are said to be circular, and play an important role in mechanical engineering problems. We have already met a number of circular curves, for instance, the pedal curves of the parabola and the unit circle, the three- and four-leaved clovers, and the astroid.

Exercises

9.5.1

Find the points at infinity on the projective curves in pffi.2 corresponding to the following curves I in ffi.2. (i)

(ii) (iii) (iv) (v) 9.5.2

(ii) (iii) (iv)

=

=

x 5 + y5 - 2xy2 x 2y2 + x 2 _ y2.

I I I I

= = = =

x 5 + y5 - 2x 2 - 5xy + 2y 2 x 5 + y5 - 5x 2 y 2 + 3x - 3y (2x + y)(x + y)2 + (2x - y)(x x 4y + x 2y3 + x 4 - y3 + 1.

+ y) + (x -

y)

Let I = cI~l ... I~s be the unique factorization of the polynomial into irreducible factors, and let F, F1, ... , F s be the forms obtained from I, 11, ... , Is by homogenization. Show that F = cF? ... F;s is the unique factorization of the form F into irreducible forms. Let h be any irreducible conic in ffi.2 having at least one real point and let H be the corresponding projective conic in PCC 2 . Show that if H passes through the circular points at infinity I, J then

I

9.5.4

= x 3 - xy2 - y = (y - x 2)2 - xy3 = x 4 + 4xy - y4

Find the points at infinity on the projective curves in pffi.2 corresponding to the following curves I in ffi.2. (i)

9.5.3

I I I I I

124

Projective Algebraic Curves h is a circle. (Point out precisely where you use the hypothesis that h is irreducible, and where you use the hypothesis that h

9.5.5

9.5.6

has a real point.) Let !(x,Y) be a curve of degree d in lR. 2 , and let F(x,Y,z) be the corresponding projective curve in pe 2 . Show that f(x, y) is circular if and only if its HOT are divisible by x 2 + y2. Use this characterization to verify that the pedal curves of the parabola and the unit circle, the three- and four-leaved clovers, and the astroid are all circular curves. Let F, G be two curves in PlR. 2 intersecting in finitely many points. Show that the intersections are either real, or occur in complex conjugate pairs.

10 Singularities of Projective Curves

The next step in our development is to extend the concept of 'singularity' from the affine to the projective situation. We will follow the same pattern as in the affine case. The starting point is to extend the idea of intersection number (of a line with a curve at some point) to the projective situation; we can then define the 'multiplicity' of a point on a projective curve, and use this to introduce 'singular' points. As an application of these ideas, we return to conics, and show that by thinking of conics in the projective (rather than the affine) plane we can gain geometric insight into the delta invariants of Chapter 5.

10.1 Intersection Numbers For projective curves we can mimic what we did in Chapter 6 for affine curves. Let F(x,y,z) be a curve of degree d in POC2 • And let L be a line. L is determined by any two distinct points, say A = (al : a2 : a3) and B = (b l : b2 : b3 ): then, as in Example 9.5, the line L can be parametrized as Xl = sal + tbl, x2 = sa2 + tb 2, x3 = sa3 + tb 3. The intersections of F with L are given by (s, t) = 0, where is defined by (s, t) = F(sal

+ tbl, sa2 + tb 2, sa3 + tb 3).

Since F(x, y, z) is a form of degree d we have (As, At) = A,d(s, t) for any scalar A, so (s, t) is a binary form of degree d, the intersection form. Of course, may be identically zero. It is worth comparing this with the situation in the affine case where an intersection polynomial cjJ(t), associated to an affine curve f of degree d and a line 1, is only known to be of degree s d. Concerning the generalities of how lines intersect projective curves, we have the following analogue of Lemma 4.4. 125

126

Singularities of Projective Curves

Lemma 10.1 Let F be a curve of degree d in POC2 , and let L be a line. Then either L meets F in S d points, or L is a component of F. Thus, for a curve F with no line components, the degree d is an upper bound for the number of intersections of F with any line L. Proof As above, we can associate an intersection form of degree d to the (parametrized) line L and the curve F. Provided is not identically zero, the equation (s, t) = 0 has S d roots, and there are S d points of intersection. Suppose now that is identically zero, so F vanishes at every point on L. Let L have equation ax + by + cz = O. It is no restriction to suppose that c =1= 0, so X = x, Y = y, Z = ax + by + cz is an invertible linear mapping. Then F(X, Y, Z) vanishes at every point of Z = 0, so the binary form F(X, Y, 0) is identically zero, and Z must be a factor of F(X, Y,Z). In terms of the variables x, y, z that means that L is a factor of F(x,y,z), as required. D Next, let us look in more detail at the way in which a line L intersects a projective curve F of degree d. Assume L is not a component of F. Let P be a point on L corresponding to the ratio (so : to), in some parametrization of L. We define the intersection number I(P,F,L) to be the multiplicity of (so : to) as a root of the equation (s, t) = 0; that means that (s, t) has a factor (tos - sot)m for some integer m ~ 0, and that I(P,F,L) = m. Clearly I(P,F,L) is an integer ~ 0, and vanishes if and only if P is not an intersection of F, L. It is a convention that I(P,F,L) = 00 when L is a component of F.

Example 10.1 The projective curve corresponding to the eight-curve 2 4 f = y2 - x + x in JR2 is F = y2 z2 - x 2z 2 + x 4 in pJR2. Let L be the line x = O. Then L is the line through P = (0 : 0 : 1), Q = (0 : 1 : 0) and parametrized as x = 0, y = t, Z = s. The resulting intersection form is (s,t) = s2 t2, having roots (1 : 0) and (0 : 1) both of multiplicity 2; the root (1 : 0) corresponds to P, whilst (0 : 1) corresponds to Q. Since both roots have multiplicity 2 the intersection numbers are I(P,F,L) = 2, I(Q,F,L) = 2. The next step in our development is to establish that I(P,F,L) does not depend on the chosen parametrization of the line L. We follow the paradigm of the affine case, by establishing a preliminary lemma. By a projective change of parameter we mean an invertible linear map U(s, t) = (u, v) where u = as + yt, v = f3s + bt and a, 13, y, b are scalars with ab - f3y =1= o. We now have

10.1 Intersection Numbers

127

Lemma 10.2 Suppose that two forms (s, t), \P(u, v) are related by a projective change of parameter, i.e. (s, t) == \P(U(s, t)) for some projective change of parameter U(s, t). Then (so, to) is a zero of multiplicity m of (s, t) if and only if U(so, to) is a zero of multiplicity m of \P(u, v). Proof Write U(so, to) == (uo, vo). Observe (using the Factor Theorem) that -tos + sot is a factor of (t) if and only if (so, to) is a zero of (t), if and only if U(so, to) is a zero of \P(U(s, t)), if and only if -vou + uov is a factor of \P(u, v). However, by Lemma 4.6 corresponding factors t - to, u - u(to) have the same multiplicity, as required. D

Lemma 10.3 I(P,F,L) depends only on P, F, L, it does not depend on the choice of parametrization of L. Proof This follows exactly the same lines as the corresponding result (Lemma 6.3) in the affine case. Consider two parametrizations of L, the first via distinct points A, B with parameter the ratio (s : t), yielding the intersection form (s, t) == F(sA + tB), and the second via distinct points C, D with parameter the ratio (u : v), yielding the intersection form \P(u, v) == F(uC + vD). The connexion between (s, t), \P(u, v) is easily established. Let A == liC + [3D, B == yC + bD. Then, by direct calculation (s, t) == F(sA

+ tB) == F(u(s, t)C + v(s, t)D) == \P(u(s, t), v(s, t))

where u(s, t) == liS+yt, v(s, t) == [3s+6t. Thus (s, t) is obtained from \P(u, v) by the projective change of parameter U(s, t) == (u(s, t), v(s, t)). (Note that lib - [3y =1= 0 else A, B coincide.) Then (so : to) is a zero of (s, t) if and only if U(so, to) is a zero of \P(u, v), and it follows from Lemma 10.2 that the multiplicities of the zeros coincide. The result follows from the definition of I(P,F,L). D The total number of intersections of F with L (counted properly) is the sum of the intersection numbers I(P,F,L) with P on F. As the sum of the multiplicities of the roots of (s, t) is ~ d, we deduce that the total number of intersections of a curve F of degree d with a line L is ~ d. Over the complex field the intersection form has exactly d zeros, counted with multiplicities, so the total number of intersections (counted properly) is precisely d, in particular has at least one zero. Thus we have established

128

Singularities of Projective Curves

Lemma 10.4 Let F be a curve of degree d in PCC 2 , and let L be a line which is not a component of F. Then L meets F in exactly d points, counted properly. In particular, L meets F in at least one point. Lemma 10.4 is a special case of a celebrated result in the theory of algebraic curves, namely Bezout's Theorem. Roughly speaking, this says the following. Any two curves F, G in PCC 2 with no common component intersect in only finitely many points P. Moreover, it is possible to associate an 'intersection number' I (P, F, G) to any such curves F, G, and any point P, in such a way that the sum of the intersection numbers at all points of intersection is de, where d = deg F, e = deg G. And in the special case when G is a line L, this 'intersection number' agrees with the number I(P,F,L) defined above. The proof of Bezout's Theorem is presented in Chapter 14, together with the algebraic ideas on which it depends. It is worth remarking at this stage that the definition of I(P,F,L) has a fatal limitation. We used the fact that L can be parametrized globally by parameters s, t. In principle, one could extend the idea by replacing L by any curve G which can be globally parametrized. However, this approach founders on the fundamental fact that rather few algebraic curves have this property. (We will have more to say about this matter in the final chapter.) In practice you can reduce the computation of intersection numbers in the projective plane to one in an affine plane, via the following result.

Lemma 10.5 Let P be an intersection point of a curve F of degree d with a line L in the projective plane pJI{2. Dehomogenize with respect to one oj' the variables x, y, z to obtain a point p, a curve j, and a line I in the affine plane JI{2. Then I(P,F,L) =I(p,f,l). Proof At least one of the homogeneous coordinates of P is non-zero. Without loss of generality, assume it is z. Let B = (b i : b2 : 0) be the unique point where z = 0 meets L, and let A = (al : a2 : 1) be any point on L distinct from B. Then the projective line L is parametrized as sA + tB, with s = 0 corresponding to B, and gives rise to an intersection form (s, t) = F(sA + tB). Likewise, the affine line 1 is parametrized as a + tb, where a = (aI, a2), b = (b l , b2), and gives rise to an intersection polynomial¢(t) = f(a + tb). Moreover, under the identification (x,y) "" (x : y : 1) the point on I with parameter to corresponds to the point on

10.2 Multiplicity of a Point on a Curve

simple point

double point

129

triple point

Fig. 10.1. Simple, double and triple points

L with parameter s = 1, t = to. For s =1= 0 we have (s, t)

= F(sA + tB) = sdf(a + ub) = sd1>(u)

where u = tj s. Thus the zeros (so, to) of ( t) = t 2 , and I (p, f, l) = 2, agreeing with the result of Example 10.1.

10.2 Multiplicity of a Point on a Curve Let P be a point on a curve F in pJI(2. Consider the pencil of all lines L through P. By the multiplicity of P on F we mean the minimal value m of the intersection number I (P, F, L) as L varies over the pencil, i.e. I(P,F,L) 2 m for every line L through P, and there exist lines L for which I(P,F,L) = m. Points of multiplicity 1,2,3,4, ... are said to be simple, double, triple, quadruple, ... points of F. A crude mental picture for a point P of multiplicity m is that there are m 'branches' of the curve self-intersecting at P. (Figure 10.1.) But, as in the affine case, that is not the whole story. In view of Lemma 10.5, we have the following result, which allows us to compute multiplicities via the technique of Lemma 6.4. Lemma 10.6 Let P be a point on a curve F in POC2 . Dehomogenize with

130

Singularities of Projective Curves

respect to one of the variables x, y, z to obtain a point p on a curve Then the multiplicity of P on F coincides with that of p on f.

f

in

]K2.

Example 10.3 The eight-curve gives rise to the projective curve F == y2 z2 - x 2{z2 - x 2) in pffi.2, intersecting the line at infinity at the unique point Q == (O : 1 : 0). To find the multiplicity of Q we dehomogenize with respect to y to obtain the affine curve f == z2 - x 2(z2 - x 2) and the point q == (O,O) in the (x,z)-plane. Here the LOT are z2, so q has multiplicity 2 on f, and hence Q has multiplicity 2 on F.

Exercises 10.2.1

10.2.2

Let F be an irreducible quartic curve in PCC 2. Show that F cannot have a point P of multiplicity z 4. Show also that if F has a triple point P then P is the only point on F of multiplicity ~ 2. Let P be a point on a projective curve F in POC2 of multiplicity z m. Show that P is a point on the projective curve F z of multiplicity z (m - 1). And show, by means of an example, that P could have multiplicity> m - 1.

10.3 Singular Points A point P on a projective curve F is singular when it has multiplicity z 2. The curve F itself is singular when it has at least one singular point, otherwise it is non-singular. We will see in Chapter 18 that an irreducible curve F has at most finitely many singular points.

Example 10.4 A cubic curve F in POC2 with two singular points P, Q necessarily reduces to a conic, and the line L joining P, Q. Indeed, since P, Q are singular, we have I(P,F,L) z 2, I(Q,F,L) ~ 2 so the total number of intersections of L with F is z 4, contradicting Lemma 10.1 unless L is a component of F. Here is a simple criterion for a point to be singular on a curve F, analogous to Lemma 6.6 in the affine case.

Lemma 10.7 A point P is a singular point on a curve F if and only if F{P) == 0 and Fx{P) == Fy{P) == Fz{P) == o. Proof The condition for P == (PI : P2 : P3) to be singular is that I(P,F,L) ~ 2 for every line L through P. We need to interpret this in

10.3 Singular Points

131

detail. Let L be any line through P, and let Q = (ql : q2 : q3) be another point on L. Recall that the intersection form {s, t) = F{sP + tQ) is a form of degree d in s, t so has the form {s, t) = sdFo{P, Q) + sd-ltF1(P, Q) + ... + tdFd{P, Q) where each Fk{P, Q) is a polynomial in the entries of P, Q. The point P corresponds to the ratio (1 : 0) and the condition I{P,F,L) ~ 2 is that (1 : 0) should have multiplicity ~ 2 as a root of {s, t) = 0, i.e. that {s,t) has t 2 as a factor, i.e. that Fo{P,Q) = 0, Fl{P,Q) = o. The condition Fo{P, Q) = 0 holds automatically, as P lies on F, so it remains to interpret the condition F 1(P, Q) = o. Write

+ ... + tdFd{P,Q) so Fl{P, Q) = rs in the Multiplicity Inequality if and only F, G are tangent at P; equivalently, I (P, F, G) = rs if and only if F, G do not have a common tangent at P. In particular, I (P , F, G) = 1 if and only if P is simple both on F and on G, and the tangents at P are distinct. That yields a useful corollary to the Multiplicity Inequality, namely

Lemma 14.9 Let F, G be curves in pe 2 of degrees m, n with no common component, intersecting in mn distinct points. Then each point of intersection P is simple on F and on G, and the tangents at P are distinct. The general picture is that even if two curves of degrees m, n fail to intersect in mn distinct points, that can always be achieved by arbitrary small deformations of one of the equations. A proof of this fact requires topological concepts, so we will content ourselves with an example.

Example 14.8 Consider the conics F b = x 2 + y2 + (
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