EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN) Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at √ s = 13 TeV with the ATLAS detector The ATLAS Collaboration
2017

M Aaboud
Université Clermont Auvergne
CNRS/IN2P3
LPC
Clermont-FerrandFrance

Also at TRIUMF
VancouverBCCanada

G Aad
B Abbott
O Abdinov
B Abeloos
S H Abidi
O S Abouzeid
Niels Bohr Institute
Dipartimento di Fisica
40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b)
University of Copenhagen
KobenhavnDenmark

Università della Calabria
RendeItaly

Faculty of Physics and Applied Computer Science
Marian Smoluchowski Institute of Physics
AGH University of Science and Technology
Krakow

Jagiellonian University
KrakowPoland

N L Abraham
H Abramowicz
H Abreu
R Abreu
Y Abulaiti
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

B S Acharya
Department of Physics and Astronomy
Graduate School of Science
Iowa State University
AmesIA

Kobe University
KobeJapan

Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

S Adachi
Department of Physics and Astronomy
Graduate School of Science
Iowa State University
AmesIA

Kobe University
KobeJapan

Also at Department of Physics, King's College London
LondonUnited Kingdom

L Adamczyk
Also at Department of Physics, King's College London
LondonUnited Kingdom

J Adelman
M Adersberger
T Adye
A A Affolder
Niels Bohr Institute
Dipartimento di Fisica
40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b)
University of Copenhagen
KobenhavnDenmark

Università della Calabria
RendeItaly

Faculty of Physics and Applied Computer Science
Marian Smoluchowski Institute of Physics
AGH University of Science and Technology
Krakow

Jagiellonian University
KrakowPoland

T Agatonovic-Jovin
C Agheorghiesei
Also at
Novosibirsk State University
NovosibirskRussia

J A Aguilar-Saavedra
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Physics Department
An-Najah National University
NablusPalestine

S P Ahlen
F Ahmadov
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

G Aielli
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

S Akatsuka
Faculty of Science
Kyoto University
KyotoJapan

H Akerstedt
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

T P A Åkesson
E Akilli
A V Akimov
G L Alberghi
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

J Albert
Kyoto University of Education
KyotoJapan

P Albicocco
M J Alconada Verzini
Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET
La PlataArgentina

S C Alderweireldt
M Aleksa
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

I N Aleksandrov
C Alexa
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

G Alexander
T Alexopoulos
M Alhroob
B Ali
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

M Aliev
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

G Alimonti
Also at Department of Physics, King's College London
LondonUnited Kingdom

J Alison
S P Alkire
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

B M M Allbrooke
B W Allen
P P Allport
A Aloisio
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

A Alonso
Niels Bohr Institute
Dipartimento di Fisica
40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b)
University of Copenhagen
KobenhavnDenmark

Università della Calabria
RendeItaly

Faculty of Physics and Applied Computer Science
Marian Smoluchowski Institute of Physics
AGH University of Science and Technology
Krakow

Jagiellonian University
KrakowPoland

F Alonso
Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET
La PlataArgentina

C Alpigiani
A A Alshehri
M I Alstaty
B Alvarez Gonzalez
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

D Álvarez Piqueras
Department of Physics
Department of Physics and Astronomy
Instituto de Fisica Corpuscular (IFIC), Centro Mixto Universidad de Valencia -CSIC
University of British Columbia
171, 172VancouverBCSpain, Canada

Department of Physics
University of Victoria
Victoria BC55 173Canada

University of Warwick
CoventryUnited Kingdom

M G Alviggi
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

B T Amadio
Y Amaral Coutinho
Also at Department of Physics, King's College London
LondonUnited Kingdom

C Amelung
D Amidei
S P Amor
Dos Santos
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at
Novosibirsk State University
NovosibirskRussia

A Amorim
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

S Amoroso
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

G Amundsen
C Anastopoulos
L S Ancu
N Andari
T Andeen
C F Anders
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

J K Anders
Oliver Lodge Laboratory
University of Liverpool
LiverpoolUnited Kingdom

K J Anderson
A Andreazza
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

V Andrei
Also at Department of Physics, King's College London
LondonUnited Kingdom

S Angelidakis
I Angelozzi
A Angerami
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

A V Anisenkov
Also at
Novosibirsk State University
NovosibirskRussia

N Anjos
A Annovi
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

C Antel
Also at Department of Physics, King's College London
LondonUnited Kingdom

M Antonelli
A Antonov
D J Antrim
University of Iowa
Iowa CityIAUnited States of America

F Anulli
Also at Department of Physics, King's College London
LondonUnited Kingdom

M Aoki
L Aperio Bella
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

G Arabidze
Y Arai
J P Araque
Also at Department of Physics, King's College London
LondonUnited Kingdom

V Araujo Ferraz
Also at Department of Physics, King's College London
LondonUnited Kingdom

A T H Arce
R E Ardell
Department of Physics
Royal Holloway University of London
SurreyUnited Kingdom

F A Arduh
Instituto de Física La Plata, Universidad Nacional de La Plata and CONICET
La PlataArgentina

J-F Arguin
S Argyropoulos
University of Iowa
Iowa CityIAUnited States of America

M Arik
Also at Department of Physics, King's College London
LondonUnited Kingdom

A J Armbruster
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

L J Armitage
School of Physics and Astronomy
Mary University of London
LondonQueenUnited Kingdom

O Arnaez
H Arnold
M Arratia
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

O Arslan
A Artamonov
G Artoni
S Artz
S Asai
N Asbah
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

A Ashkenazi
L Asquith
K Assamagan
R Astalos
Also at Department of Physics, King's College London
LondonUnited Kingdom

M Atkinson
N B Atlay
Physics Department
Dallas TX, United States of America 44 Physics Department
Southern Methodist University
University of Texas
at Dallas, Richardson TXUnited States of America

K Augsten
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

G Avolio
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

B Axen
M K Ayoub
G Azuelos
Also at TRIUMF
VancouverBCCanada

A E Baas
Also at Department of Physics, King's College London
LondonUnited Kingdom

M J Baca
H Bachacou
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

K Bachas
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

M Backes
M Backhaus
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

P Bagnaia
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

M Bahmani
Institute of Nuclear Physics Polish Academy of Sciences
KrakowPoland

H Bahrasemani
J T Baines
M Bajic
Niels Bohr Institute
Dipartimento di Fisica
40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b)
University of Copenhagen
KobenhavnDenmark

Università della Calabria
RendeItaly

Faculty of Physics and Applied Computer Science
Marian Smoluchowski Institute of Physics
AGH University of Science and Technology
Krakow

Jagiellonian University
KrakowPoland

O K Baker
School of Physics and Astronomy
Mary University of London
LondonQueenUnited Kingdom

E M Baldin
Also at
Novosibirsk State University
NovosibirskRussia

P Balek
Physics Department
Dipartimento di Matematica e Fisica
INFN Sezione di Lecce; (b)
Lancaster University
LancasterUnited Kingdom

Università del Salento
LecceItaly

F Balli
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

W K Balunas
E Banas
Institute of Nuclear Physics Polish Academy of Sciences
KrakowPoland

A Bandyopadhyay
Sw Banerjee
Also at Department of Physics & Astronomy
University of Louisville
LouisvilleKYUnited States of America

A A E Bannoura
Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics
University of Ljubljana
LjubljanaSlovenia

L Barak
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

E L Barberio
D Barberis
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

M Barbero
T Barillari
M-S Barisits
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

J T Barkeloo
T Barklow
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

N Barlow
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

S L Barnes
Also at
Novosibirsk State University
NovosibirskRussia

B M Barnett
R M Barnett
Z Barnovska-Blenessy
Also at Department of Physics, King's College London
LondonUnited Kingdom

A Baroncelli
Also at Department of Physics, King's College London
LondonUnited Kingdom

G Barone
A J Barr
L Barranco Navarro
Department of Physics
Department of Physics and Astronomy
Instituto de Fisica Corpuscular (IFIC), Centro Mixto Universidad de Valencia -CSIC
University of British Columbia
171, 172VancouverBCSpain, Canada

Department of Physics
University of Victoria
Victoria BC55 173Canada

University of Warwick
CoventryUnited Kingdom

F Barreiro
J Barreiro Guimarães Da Costa
Also at Department of Physics, King's College London
LondonUnited Kingdom

R Bartoldus
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

A E Barton
Physics Department
Dipartimento di Matematica e Fisica
INFN Sezione di Lecce; (b)
Lancaster University
LancasterUnited Kingdom

Università del Salento
LecceItaly

P Bartos
Also at Department of Physics, King's College London
LondonUnited Kingdom

A Basalaev
A Bassalat
Also at Physics Department
An-Najah National University
NablusPalestine

R L Bates
S J Batista
J R Batley
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

M Battaglia
Niels Bohr Institute
Dipartimento di Fisica
40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b)
University of Copenhagen
KobenhavnDenmark

Università della Calabria
RendeItaly

Faculty of Physics and Applied Computer Science
Marian Smoluchowski Institute of Physics
AGH University of Science and Technology
Krakow

Jagiellonian University
KrakowPoland

M Bauce
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

F Bauer
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

H S Bawa
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

Also at Department of Physics
California State University
FresnoCAUnited States of America

J B Beacham
M D Beattie
Physics Department
Dipartimento di Matematica e Fisica
INFN Sezione di Lecce; (b)
Lancaster University
LancasterUnited Kingdom

Università del Salento
LecceItaly

T Beau
P H Beauchemin
Institut für Astro-und Teilchenphysik
Leopold-Franzens-Universität, Innsbruck
Austria

P Bechtle
H P Beck
Also at Department of Physics
University of Fribourg
FribourgSwitzerland

H C Beck
K Becker
M Becker
M Beckingham
Department of Physics
Research Center for Advanced Particle Physics
Kyushu University
FukuokaJapan

C Becot
A J Beddall
Also at Department of Physics & Astronomy
University of Louisville
LouisvilleKYUnited States of America

A Beddall
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

V A Bednyakov
M Bedognetti
C P Bee
T A Beermann
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

M Begalli
Also at Department of Physics, King's College London
LondonUnited Kingdom

M Begel
J K Behr
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

A S Bell
Department of Physics and Astronomy
University College London
LondonUnited Kingdom

G Bella
L Bellagamba
Also at Department of Physics, King's College London
LondonUnited Kingdom

A Bellerive
Department of Physics
Carleton University
OttawaONCanada

M Bellomo
K Belotskiy
O Beltramello
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

N L Belyaev
O Benary
D Benchekroun
Université Clermont Auvergne
CNRS/IN2P3
LPC
Clermont-FerrandFrance

Also at Department of Physics, King's College London
LondonUnited Kingdom

M Bender
K Bendtz
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

N Benekos
Y Benhammou
E Benhar Noccioli
School of Physics and Astronomy
Mary University of London
LondonQueenUnited Kingdom

J Benitez
University of Iowa
Iowa CityIAUnited States of America

D P Benjamin
M Benoit
J R Bensinger
S Bentvelsen
L Beresford
M Beretta
D Berge
E Bergeaas Kuutmann
N Berger
J Beringer
S Berlendis
N R Bernard
G Bernardi
C Bernius
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

F U Bernlochner
T Berry
Department of Physics
Royal Holloway University of London
SurreyUnited Kingdom

P Berta
Department of Physics
Carleton University
OttawaONCanada

C Bertella
Also at Department of Physics, King's College London
LondonUnited Kingdom

G Bertoli
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

F Bertolucci
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

I A Bertram
Physics Department
Dipartimento di Matematica e Fisica
INFN Sezione di Lecce; (b)
Lancaster University
LancasterUnited Kingdom

Università del Salento
LecceItaly

C Bertsche
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

D Bertsche
G J Besjes
Niels Bohr Institute
Dipartimento di Fisica
40 (a) INFN Gruppo Collegato di Cosenza, Laboratori Nazionali di Frascati; (b)
University of Copenhagen
KobenhavnDenmark

Università della Calabria
RendeItaly

Faculty of Physics and Applied Computer Science
Marian Smoluchowski Institute of Physics
AGH University of Science and Technology
Krakow

Jagiellonian University
KrakowPoland

O Bessidskaia Bylund
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

M Bessner
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

N Besson
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

C Betancourt
A Bethani
S Bethke
A J Bevan
School of Physics and Astronomy
Mary University of London
LondonQueenUnited Kingdom

J Beyer
R M Bianchi
O Biebel
D Biedermann
R Bielski
K Bierwagen
N V Biesuz
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

M Biglietti
Also at Department of Physics, King's College London
LondonUnited Kingdom

T R V Billoud
H Bilokon
M Bindi
A Bingul
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

C Bini
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

S Biondi
Also at Department of Physics, King's College London
LondonUnited Kingdom

Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

T Bisanz
C Bittrich
D M Bjergaard
C W Black
J E Black
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

K M Black
R E Blair
T Blazek
Also at Department of Physics, King's College London
LondonUnited Kingdom

I Bloch
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

C Blocker
A Blue
W Blum
U Blumenschein
School of Physics and Astronomy
Mary University of London
LondonQueenUnited Kingdom

S Blunier
Also at Department of Physics, King's College London
LondonUnited Kingdom

G J Bobbink
V S Bobrovnikov
Also at
Novosibirsk State University
NovosibirskRussia

S S Bocchetta
A Bocci
C Bock
M Boehler
D Boerner
Department of Experimental Particle Physics, Jožef Stefan Institute and Department of Physics
University of Ljubljana
LjubljanaSlovenia

D Bogavac
A G Bogdanchikov
C Bohm
Also at Department of Physics, King's College London
LondonUnited Kingdom

V Boisvert
Department of Physics
Royal Holloway University of London
SurreyUnited Kingdom

P Bokan
Also at II Physikalisches Institut
Georg-August-Universität
GöttingenGermany

T Bold
Also at Department of Physics, King's College London
LondonUnited Kingdom

A S Boldyrev
A E Bolz
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

M Bomben
M Bona
School of Physics and Astronomy
Mary University of London
LondonQueenUnited Kingdom

M Boonekamp
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

A Borisov
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

G Borissov
Physics Department
Dipartimento di Matematica e Fisica
INFN Sezione di Lecce; (b)
Lancaster University
LancasterUnited Kingdom

Università del Salento
LecceItaly

J Bortfeldt
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

D Bortoletto
V Bortolotto
Also at Department of Physics, King's College London
LondonUnited Kingdom

D Boscherini
Also at Department of Physics, King's College London
LondonUnited Kingdom

M Bosman
J D Bossio Sola
Departamento de Física, Universidad de Buenos Aires
Buenos AiresArgentina

J Boudreau
J Bouffard
E V Bouhova-Thacker
Physics Department
Dipartimento di Matematica e Fisica
INFN Sezione di Lecce; (b)
Lancaster University
LancasterUnited Kingdom

Università del Salento
LecceItaly

D Boumediene
Université Clermont Auvergne
CNRS/IN2P3
LPC
Clermont-FerrandFrance

C Bourdarios
S K Boutle
A Boveia
J Boyd
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

I R Boyko
J Bracinik
A Brandt
G Brandt
O Brandt
Also at Department of Physics, King's College London
LondonUnited Kingdom

U Bratzler
B Brau
J E Brau
W D Breaden Madden
K Brendlinger
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

A J Brennan
L Brenner
R Brenner
S Bressler
Physics Department
Dipartimento di Matematica e Fisica
INFN Sezione di Lecce; (b)
Lancaster University
LancasterUnited Kingdom

Università del Salento
LecceItaly

D L Briglin
T M Bristow
D Britton
D Britzger
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

F M Brochu
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

I Brock
R Brock
G Brooijmans
Nevis Laboratory
Columbia University
IrvingtonNYUnited States of America

T Brooks
Department of Physics
Royal Holloway University of London
SurreyUnited Kingdom

W K Brooks
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

J Brosamer
E Brost
J H Broughton
P A Bruckman De Renstrom
Institute of Nuclear Physics Polish Academy of Sciences
KrakowPoland

D Bruncko
Also at Institute of Physics
Academy of Sciences
BakuAzerbaijan, Azerbaijan

A Bruni
Also at Department of Physics, King's College London
LondonUnited Kingdom

G Bruni
L S Bruni
Also at Department of Physics, King's College London
LondonUnited Kingdom

B H Brunt
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

M Bruschi
Also at Department of Physics, King's College London
LondonUnited Kingdom

N Bruscino
P Bryant
L Bryngemark
Department of Physics
Department of Physics
The Chinese University of Hong Kong
Shatin, Hong KongN.T

Department of Physics and Institute for Advanced Study
The University of Hong Kong
Hong Kong, The Hong Kong

University of Science and Technology
Clear Water Bay, Kowloon, Hong KongChina

T Buanes
Q Buat
P Buchholz
Physics Department
Dallas TX, United States of America 44 Physics Department
Southern Methodist University
University of Texas
at Dallas, Richardson TXUnited States of America

A G Buckley
I A Budagov
F Buehrer
M K Bugge
O Bulekov
D Bullock
T J Burch
S Burdin
Oliver Lodge Laboratory
University of Liverpool
LiverpoolUnited Kingdom

C D Burgard
A M Burger
B Burghgrave
K Burka
Institute of Nuclear Physics Polish Academy of Sciences
KrakowPoland

S Burke
I Burmeister
J T P Burr
E Busato
Université Clermont Auvergne
CNRS/IN2P3
LPC
Clermont-FerrandFrance

D Büscher
V Büscher
P Bussey
J M Butler
C M Buttar
J M Butterworth
Department of Physics and Astronomy
University College London
LondonUnited Kingdom

P Butti
Departamento de Física, Pontificia Universidad Católica de Chile
Departamento de Física
CERN
GenevaSantiago; (b)Switzerland

Institute of High Energy Physics
Universidad Técnica Federico Santa María
ValparaísoChile

Department of 51 Physics
Chinese Academy of Sciences
Beijing

Physics Department
Nanjing University
Tsinghua University
100084BeijingJiangsu; (c)

Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics
University of Chinese Academy of Science (UCAS)
BeijingChina

School of Physics
Department of Physics and Astronomy
Key Laboratory for Particle Physics, Astrophysics and Cosmology, Ministry of Education; Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai(also at PKU-CHEP)
University of Science and Technology of China
Shandong University
ShandongAnhui; (b)China

W Buttinger
A Buzatu
Also at
Novosibirsk State University
NovosibirskRussia

A R Buzykaev
Also at
Novosibirsk State University
NovosibirskRussia

S Cabrera Urbán
Department of Physics
Department of Physics and Astronomy
Instituto de Fisica Corpuscular (IFIC), Centro Mixto Universidad de Valencia -CSIC
University of British Columbia
171, 172VancouverBCSpain, Canada

Department of Physics
University of Victoria
Victoria BC55 173Canada

University of Warwick
CoventryUnited Kingdom

D Caforio
Cavendish Laboratory
University of Cambridge
CambridgeUnited Kingdom

Department of Physics, Alexandru Ioan
of Brasov, Brasov; (b) Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest; (c)
Transilvania University
D. Cinca 46 , V. Cindro 78 , I.A. Cioara 23, C. Ciocca 22a, 16 , F. Cirotto 106a22b, 106bA. Ciocio

National Institute for Research and Development of Isotopic and Molecular Technologies, Physics Department, Cluj Napoca; (e) University Politehnica Bucharest, Bucharest
Cuza University of Iasi
Iasi

West University in Timisoara
TimisoaraRomania

Department of Physics
National Tsing Hua University
Taiwan, Taiwan

Department of Physics
Indiana University
Bloomington INUnited States of America

Institute for Mathematics, Astrophysics and Particle Physics
Louisiana Tech University
RustonLAUnited States of America

Nikhef National Institute for Subatomic Physics
Radboud University Nijmegen/Nikhef
109NijmegenNetherlands

Department of Physics
University of Amsterdam
110AmsterdamNetherlands

DeKalb IL, United States of America 111 Budker Institute of Nuclear Physics, SB RAS, Novosibirsk
Department of Physics
Northern Illinois University
112Russia

New York University
113New York, NYUnited States of America

Faculty of Science
Ohio State University
114ColumbusOHUnited States of America

Dodge Department of Physics and Astronomy
Okayama University
OkayamaJapan

Department of Physics
University of Oklahoma
116NormanOKUnited States of America

Oklahoma State University
117StillwaterOKUnited States of America

Czech Republic 118 Center for High Energy Physics
Palacký University
RCPTMOlomouc

LAL, Univ. Paris-Sud, CNRS/IN2P3
University of Oregon
119EugeneORUnited States of America

120 Graduate School of Science
Université Paris-Saclay
OrsayFrance

Department of Physics
Osaka University
121OsakaJapan

Department of Physics
University of Oslo
122OsloNorway

Dipartimento di Fisica
INFN Sezione di Pavia; (b)
Oxford University
OxfordUnited Kingdom

Department of Physics
Università di Pavia
124PaviaItaly

Department of Physics
University of Pennsylvania
Philadelphia PA, 125 140United States of America

Department of Physics and Astronomy
University of Washington
141SeattleWAUnited States of America

Department of Physics
University of Sheffield
142SheffieldUnited Kingdom

Department Physik
Shinshu University
143NaganoJapan

Department of Physics
Universität Siegen
144SiegenGermany

Faculty of Mathematics, Physics & Informatics
SLAC National Accelerator Laboratory
Simon Fraser University
145BurnabyBC, Stanford CACanada, United States of America

Department of Subnuclear Physics
Department of Physics
Institute of Experimental Physics of the Slovak Academy of Sciences, Kosice, Slovak Republic 147 (a)
Comenius University
Bratislava

Cape Town
Department of Physics
School of Physics
Department of Physics
University of Cape Town
University of Johannesburg
University of the Witwatersrand
JohannesburgJohannesburg; (c)South Africa

Physics Department
Stockholm University
Oskar Klein Centre, Stockholm149Sweden

Departments of Physics & Astronomy and Chemistry
Royal Institute of Technology
150StockholmSweden

Department of Physics and Astronomy
Stony Brook University
Stony Brook151NYUnited States of America

School of Physics
University of Sussex
152BrightonUnited Kingdom

Institute of Physics, Academia Sinica, Taipei
Department of Physics, Technion: Israel Institute of Technology
Raymond and Beverly Sackler School of Physics and Astronomy
University of Sydney
153, 154, 155Sydney, HaifaAustralia, Taiwan, Israel

Department of Physics
Tel Aviv University
Tel Aviv156Israel

International Center for Elementary Particle Physics
Department of Physics
Aristotle University of Thessaloniki
157ThessalonikiGreece

Graduate School of Science and Technology
The University of Tokyo
158TokyoJapan

Department of Physics
Tokyo Metropolitan University
159TokyoJapan

Tokyo Institute of Technology
160Japan

Department of Physics
Tomsk State University
161TomskRussia

University of Toronto
TorontoONCanada

Department of Physics and Astronomy
University of Trento
TrentoItaly

Faculty of Pure and Applied Sciences, and Center for Integrated Research in Fundamental Science and Engineering
York University
164TorontoONCanada

Department of Physics and Astronomy
University of Tsukuba
165TsukubaJapan

Department of Physics and Astronomy
Tufts University
166MedfordMAUnited States of America

Dipartimento di Chimica, Fisica e Ambiente
INFN Gruppo Collegato di Udine, Sezione di Trieste, Udine; (b) ICTP, Trieste; (c)
University of California Irvine
IrvineCAUnited States of America

Department of Physics and Astronomy
Università di Udine
168UdineItaly

Department of Physics
University of Uppsala
169UppsalaSweden

University of Illinois
Urbana IL

Department of Particle Physics
Waseda University
175TokyoJapan

Department of Physics
The Weizmann Institute of Science
176RehovotIsrael

Fakultät für Mathematik und Naturwissenschaften
Fachgruppe Physik
University of Wisconsin
Madison WI, 177 Fakultät für Physik und Astronomie, Julius-Maximilians-UniversitätWürzburgUnited States of America, Germany

Department of Physics
Bergische Universität Wuppertal
179WuppertalGermany

Yale University
180 Yerevan Physics InstituteNew Haven, YerevanCTUnited States of America, Armenia

Centre de Calcul de l'Institut National de Physique Nucléaire et de Physique des Particules (IN2P3)
182VilleurbanneFrance

Institute of Physics, Academia Sinica, Taipei
Academia Sinica Grid Computing
Taiwan

Also at Departament de Fisica de la Universitat Autonoma de Barcelona
BarcelonaSpain

Also at Departamento de Fisica e Astronomia
Faculdade de Ciencias
Universidade do Porto
Portugal

Also at
Tomsk State University
Tomsk

Moscow Institute of Physics and Technology State University
DolgoprudnyRussia

Also at The Collaborative Innovation Center of Quantum Matter (CICQM)
BeijingChina

Also at Universita di Napoli Parthenope, Napoli
Italy

Also at Institute of Particle Physics (IPP)
Canada

Also at Horia Hulubei National Institute of Physics and Nuclear Engineering
BucharestRomania

Also at Department of Physics, St. Petersburg State
Polytechnical University
St. PetersburgRussia

Department of Financial and Management Engineering
Also at Borough of Manhattan Community College, City University of New York, New York City, United States of America s Also at
University of the Aegean
ChiosGreece

Also at Louisiana Tech University, Ruston LA, United States of America v Also at Institucio Catalana de Recerca i Estudis Avancats
ICREA
BarcelonaSpain

Also at Department of Physics
The University of Michigan
Ann Arbor MIUnited States of America

Also at Graduate School of Science
Fakultät für Mathematik und Physik
Albert-Ludwigs-Universität
Osaka University
Osaka, FreiburgJapan, Germany

Also at Institute for Mathematics, Astrophysics and Particle Physics
Department of Physics
Radboud University Nijmegen/Nikhef
NijmegenNetherlands

TX, United States of America ab Also at Institute of Theoretical Physics
The University of Texas at Austin
Austin

ac Also at CERN, Geneva, Switzerland Also at Georgian Technical University (GTU),Tbilisi, Georgia ae Also at Ochadai Academic Production
Ilia State University
TbilisiGeorgia

Departamento de Física, Pontificia
Ochanomizu University
TokyoJapan

School of Physics
Universidad Católica de Chile
Chile

Shandong University
ShandongChina a

Department of Physics
Also at Departamento de Fisica Teorica y del Cosmos, Universidad de Granada, Granada
California State University
Portugal

The Barcelona Institute of Science and Technology
School of Physics, Sun Yat-sen University
Faculty of Physics, M.V.Lomonosov
Sacramento CA, United States of America al Also at Moscow Institute of Physics and Technology State University, Dolgoprudny, Russia am Also at Departement de Physique Nucleaire et Corpusculaire an Also at Institut de Física d'Altes Energies (IFAE)
Université de Genève
Geneva, Barcelona, Guangzhou, SofiaSwitzerland, Spain, China, Bulgaria

Department of Physics
ar Also at National Research Nuclear University MEPhI, Moscow
Moscow State University
MoscowRussia, Russia

Department of Physics
Stanford CA, United States of America at Also at Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Budapest, Hungary au Also at Giresun University, Faculty of Engineering, Turkey av Also at CPPM, Aix-Marseille Université and CNRS/IN2P3, Marseille
Stanford University
France

ax Also at Institute of Physics, Academia Sinica, Taipei
Nanjing University
JiangsuChina, Taiwan

Department of Physics, Kuala Lumpur
az Also at LAL, Univ. Paris-Sud, CNRS/IN2P3
University of Malaya
Malaysia

Université Paris-Saclay
OrsayFrance

EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN) Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at √ s = 13 TeV with the ATLAS detector The ATLAS Collaboration

Phys. Rev. D
96112010201710.1103/PhysRevD.96.112010Reproduction of this article or parts of it is allowed as specified in the CC-BY-4.0 license.
The results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of √ s = 13 TeV are presented. The dataset used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb −1 . No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pair production and up to 1.25 TeV for squark pair production.

Introduction

Supersymmetry (SUSY) [1][2][3][4][5][6] is a theoretical framework of physics beyond the Standard Model (SM) which predicts for each SM particle the existence of a supersymmetric partner (sparticle) differing by half a unit of spin. The partner particles of the SM fermions (quarks and leptons) are the scalar squarks (q) and sleptons (˜ ). In the boson sector, the supersymmetric partner of the gluon is the fermionic gluino (g), whereas the supersymmetric partners of the Higgs (higgsinos) and the electroweak gauge bosons (winos and bino) mix to form charged mass eigenstates (charginos) and neutral mass eigenstates (neutralinos). In the minimal supersymmetric extension of the Standard Model (MSSM) [7,8] two scalar Higgs doublets along with their higgsino partners are necessary, resulting in four chargino states (χ ± 1,2 ) and four neutralinos (χ 0 1,2,3,4 ). SUSY addresses the SM hierarchy problem [9][10][11][12] provided that the masses of at least some of the supersymmetric particles (most notably the higgsinos, the top squarks and the gluinos) are near the TeV scale.

In R-parity-conserving SUSY [13], gluinos or squarks are pair produced at the Large Hadron Collider (LHC) via the strong interaction and decay either directly or via intermediate states to the lightest supersymmetric particle (LSP). The LSP, which is assumed to be the lightest neutralino (χ 0 1 ) in this paper, is stable and weakly interacting, making it a candidate for dark matter [14,15].

The decay topologies targeted in this paper are largely inspired by decay chains that could be realized in the pMSSM scenario, which is a two-dimensional subspace of the 19-parameter phenomenological Minimal Supersymmetric Standard Model (pMSSM) [16,17]. Four SUSY models with gluino or squark pair production and different decay topologies are considered. The first two models, referred to as the gluino and squark one-step models for the rest of this paper, are SUSY simplified models [18][19][20] in which pair-produced gluinos or squarks decay via the lightest chargino (χ ± 1 ) to the LSP. In the model with gluino production, the gluino decays to the lightest chargino and two SM quarks viag → qq χ ± 1 , as illustrated in Figure 1 (left). The gluino decay is assumed to proceed via virtual first-and second-generation squarks, hence no bottom or top quarks are produced in the simplified model. The chargino then decays to the LSP by emitting an on-or off-shell W boson,χ ± 1 → W ( * )±χ 0 1 , depending on the available phase space. In the MSSM this decay chain is realized when the gluino decays, via a virtual squark that is the partner particle of the left-handed SM quark, to the chargino with a dominant wino component. In the squark production model, the squark decays to the chargino viaq → q χ ± 1 , followed by the same chargino decay, as illustrated in Figure 1 (middle). The third model, referred to as the gluino two-step model for the rest of this paper, assumes gluino pair production with a subsequent decay to the chargino viag → qq χ ± . The chargino then decays via emission of an on-or off-shell W boson to the second lightest neutralino according toχ ± → W ±χ 0 2 . In the last step of the cascade, the second lightest neutralino decays via emission of a Z boson to the LSP. The decay chain of this signal model is illustrated in Figure 1 (right). The model is used as a proxy for SUSY scenarios with many decay products in the final state. Within the MSSM, additional decay modes lead to a significant reduction in the cross-section times branching fraction for this particular decay.

Finally, the fourth set of SUSY models, the pMSSM model, is selected to have a bino-dominated neutralino as the LSP, kinematically accessible gluinos, and a higgsino-dominated multiplet at intermediate mass.

The higgsino multiplet contains two neutralinos (theχ 0 2 andχ 0 3 ) and a chargino. The decays proceed predominantly via virtual third-generation supersymmetric quarks due to their enhanced couplings with the higgsinos. Examples of dominant characteristic decay chains of this model for mχ ± 1 ∼ < 500 GeV and mg ∼ > 1200 GeV areg → ttχ 0 2,3 andg → tbχ ± 1 , withχ 0 2,3 decaying to Z/hχ 0 1 andχ ± 1 to W ±χ0 1 . In this search, the experimental signature consists of a lepton (electron or muon), several jets, and missing transverse momentum (E miss T ) from the undetectable neutralinos and neutrino(s). Depending on the sparticle masses of the model considered, different amounts of energy are available in their decays. Therefore, the number of leptons and jets in the final state, as well as their kinematic properties, depend on the mass spectrum in the model of interest. Four signal regions with jet multiplicities ranging from two to six are defined to provide sensitivity to a broad range of mass spectra in the gluino and squark one-step models. For the two-step and pMSSM models, a dedicated signal region requiring nine jets is constructed to take advantage of the large jet multiplicities in these models. In each signal region, the event yield is compared with the SM prediction, which is estimated using a combination of simulation and observed data in control regions. The results of all Run-1 ATLAS searches targeting squark and gluino pair production are summarized in Ref. [28]. The same SUSY models considered in this paper were also targeted in other Run-2 ATLAS searches using different experimental signatures [29][30][31].

This paper is structured as follows. After a brief description of the ATLAS detector in Section 2, the simulated data samples for the background and signal processes used in the analysis as well as the dataset and the trigger strategy are detailed in Section 3. The reconstructed objects and quantities used in the analysis are described in Section 4 and the event selection is presented in Section 5. The background estimation and the systematic uncertainties associated with the expected event yields are discussed in Sections 6 and 7, respectively. Finally, the results of the analysis are presented in Section 8, and are followed by a conclusion. ATLAS [32] is a general-purpose detector with a forward-backward symmetric design that provides almost full solid angle coverage around the interaction point. 1 The main components are the inner detector (ID), which is surrounded by a superconducting solenoid providing a 2 T axial magnetic field, the calorimeter system, and the muon spectrometer (MS), which is immersed in a magnetic field generated by three large superconducting toroidal magnets. The ID provides track reconstruction within |η| < 2.5, employing pixel detectors close to the beam pipe, silicon microstrip detectors at intermediate radii, and a straw-tube tracker with particle identification capabilities based on transition radiation at radii up to 1080 mm. The innermost pixel detector layer, the insertable B-layer [33], was added during the shutdown between LHC Run 1 and Run 2, at a radius of 33 mm around a new, narrower, beam pipe. The calorimeters cover |η| < 4.9. The forward region (3.2 < |η| < 4.9) is instrumented with a liquid-argon (LAr) calorimeter for both the electromagnetic and hadronic measurements. In the central region, a lead/LAr electromagnetic calorimeter covers |η| < 3.2, while the hadronic calorimeter uses two different detector technologies, with scintillator tiles (|η| < 1.7) or liquid argon (1.5 < |η| < 3.2) as the active medium. The MS consists of three layers of precision tracking chambers providing coverage over |η| < 2.7, while dedicated fast chambers allow triggering over |η| < 2.4. The ATLAS trigger system used for real-time event selection [34] consists of a hardware-based first-level trigger and a software-based high-level trigger.

ATLAS detector

Simulated event samples and data samples

Three simplified SUSY signal models and a set of pMSSM scenarios are considered in this search. Gluinos or squarks are assumed to be produced in pairs (gg orqq). In the case of the simplified models, 100% branching ratios to the decay of interest are assumed.

The gluino/squark one-step simplified models have three free parameters: the masses of the gluino or squark (mg /q ), the lightest chargino (mχ ± 1 ), and the lightest neutralino (mχ 0 1 ). Other sparticles that do not appear in the decay chain are set to have a high mass. To probe a broad range of SUSY mass spectra, two model parameterizations are considered. In the first type, mg /q and the mass ratio x ≡ (mχ ± 1 − mχ 0 1 )/(mg /q − mχ 0 1 ) are free parameters, while mχ 0 1 is fixed to 60 GeV. In the second type, mg /q and mχ 0 1 are free parameters, while mχ ± 1 is fixed by setting x = 1/2. For the rest of this paper, the former type is referred to as variable-x and the latter one is referred to as x = 1/2.

The gluino two-step simplified model has two free parameters that are varied to probe different mass configurations: the masses of the gluino (mg) and the lightest neutralino (mχ 0 1 ). The masses of the lightest chargino and the second-lightest neutralino are constrained to be mχ ± 1 = (mg + mχ 0 1 )/2 and mχ 0 2 = (mχ ± 1 + mχ 0 1 )/2, respectively. All other sparticles are kinematically inaccessible. In the pMSSM scenario, the sparticle masses are varied by scanning the gluino mass parameter M 3 (related to mg) and the bilinear Higgs mass parameter µ (related to mχ ± 1 and mχ 0 2 ). The scan ranges are 690 GeV < M 3 < 2140 GeV and −770 GeV < µ < −160 GeV. The bino mass parameter M 1 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the center of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the center of the LHC ring, and the y-axis points upward. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polar angle θ as η = − ln tan(θ/2). Rapidity is defined as y = 0.5 ln[(E + p z )/(E − p z )] where E denotes the energy and p z is the component of the momentum along the beam direction. (related to mχ 0 1 ) was set to 60 GeV. The remaining model parameters, defined in Ref. [35], are set to
M A = M 2 = 3 TeV, A τ = 0, tan β = 10, and A t = A b = mL L(1,2,3) = m (ẽ R ,μ R ,τ R ) = mQ L(1,2,3) = m (ũ R ,c R ,t R ) = m (d R ,s R ,b R ) = 5
TeV, such that the mass of the lightest Higgs boson is compatible with 125 GeV and all other sparticles are kinematically inaccessible. Mass spectra consistent with electroweak symmetry breaking were generated using SOFTSUSY 3.4.0 [36] and the decay branching ratios were calculated with SDECAY/HDECAY 1.3b/3.4 [37].

The signal samples were generated at leading order (LO) using M G 2.2.2 [38] with up to two extra partons in the matrix element, interfaced to P 8.186 [39] for parton showers and hadronization. The CKKW-L matching scheme [40] was applied for the matching of the matrix element and the parton shower, with a scale parameter set to a quarter of the mass of the sparticle produced. The ATLAS A14 [41] set of tuned parameters (tune) was used for the shower and the underlying event, together with the NNPDF2.3 LO [42] parton distribution function (PDF) set. The E G 1.2.0 program [43] was used to describe the properties of the bottom and charm hadron decays in the signal samples.

The signal cross-sections were calculated at next-to-leading order (NLO) in the strong coupling constant, adding the resummation of soft gluon emission at next-to-leading-logarithmic accuracy (NLL) [44][45][46][47][48]. The nominal cross-section and its uncertainty are taken from an envelope of cross-section predictions using different PDF sets and factorization and renormalization scales, as described in Ref. [49], considering only the four light-flavor left-handed squarks (ũ L ,d L ,s L , andc L ).

The simulated event samples for the signal and SM backgrounds are summarized in Table 1. Additional samples are used to assess systematic uncertainties, as explained in Section 7.

To generate tt and single-top-quark events in the Wt and s-channel [50], the P -B v2 [51] event generator with the CT10 [52] PDF set in the matrix-element calculations was used. Electroweak t-channel single-top-quark events were generated using the P -B v1 event generator. This event generator uses the four-flavor scheme for the NLO matrix-element calculations together with the fixed four-flavor PDF set CT10f4. For all top quark processes, top quark spin correlations are preserved (for the singletop t-channel, top quarks are decayed using MadSpin [53]). The parton shower, fragmentation, and the underlying event were simulated using P 6.428 [54] with the CTEQ6L1 [55] PDF set and the corresponding P 2012 tune (P2012) [56]. The top quark mass was set to 172.5 GeV. The EvtGen 1.2.0 program was also used to describe the properties of the bottom and charm hadron decays in the tt and the single-top-quark samples. The h damp parameter, which controls the p T of the first additional emission beyond the Born configuration, was set to the mass of the top quark. The main effect of this is to regulate the high-p T emission against which the tt system recoils. The tt events are normalized using the cross-sections computed at next-to-next-to-leading order (NNLO) with next-to-next-to-leadinglogarithmic (NNLL) corrections [57]. The single top quark events are normalized using the NLO+NNLL cross-sections for the Wt-channel [58] and to the NLO cross-sections for the tand s-channels [59].

Events containing W or Z bosons with associated jets (W/Z+jets) [60] were simulated using the S 2.2.1 event generator [61]. Matrix elements were calculated for up to two partons at NLO and four partons at LO using the Comix [62] and OpenLoops [63] generators. They were merged with the S 2.2.1 parton shower [64] with massive band c-quarks using the ME+PS@NLO prescription [65]. The NNPDF3.0 NNLO PDF set [66] was used in conjunction with a dedicated parton shower tuning developed by the S authors. The W/Z+jets events are normalized using their NNLO cross-sections [67].

The diboson samples [68] were generated using the S 2.1.1 and 2.2.1 event generators using the CT10 and NNPDF3.0 PDF sets, respectively. The fully leptonic diboson processes were simulated including final states with four charged leptons, three charged leptons and one neutrino, two charged leptons and two neutrinos, and one charged lepton and three neutrinos. The semileptonic diboson processes were simulated with one of the bosons decaying hadronically and the other leptonically. The processes were calculated for up to one parton (for Z Z) or no additional partons (for WW, W Z) at NLO and up to three partons at LO. The response of the detector to particles was modeled either with a full ATLAS detector simulation [72] using G 4 [73] or with a fast simulation [74]. The fast simulation is based on a parameterization of the performance of the electromagnetic and hadronic calorimeters and on G 4 elsewhere. All background (signal) samples were prepared using the full (fast) detector simulation. All simulated events were generated with a varying number of minimum-bias interactions overlaid on the hard-scattering event to model the multiple proton-proton interactions in the same and nearby bunch crossings. The minimumbias interactions were simulated with the soft QCD processes of P 8.186 using the A2 tune [75] and the MSTW2008LO PDF set [76]. Corrections were applied to the samples to account for differences between data and simulation for trigger, identification and reconstruction efficiencies.

The proton-proton data analyzed in this paper were collected by ATLAS during 2015 and 2016 at a center-of-mass energy of 13 TeV with up to 50 simultaneous interactions per proton bunch crossing. After application of data-quality requirements related to the beam and detector conditions, the total integrated luminosity corresponds to 36.1 fb −1 . The uncertainty in the combined 2015 and 2016 integrated luminosity is 3.2%. It is derived from a calibration of the luminosity scale using x-y beam-separation scans. This methodology is further detailed in Ref. [77].

The data were collected using the higher-level triggers that select events based on the magnitude of the missing transverse momentum, E miss T . The triggers used are close to fully efficient for events with an offline-reconstructed E miss T greater than 200 GeV.

Event reconstruction

In each event, proton-proton interaction vertices are reconstructed from at least two tracks, each with a transverse momentum p T > 400 MeV and consistent with the beamspot envelope. The primary vertex (PV) of the event is selected as the vertex with the largest p 2 T of the associated tracks. A distinction is made between preselected and signal leptons and jets. Preselected leptons and jets are used in the E miss T computation and are subject to a series of basic quality requirements. Signal leptons and jets are a subset of the preselected objects with more stringent requirements and are used for the definition of signal, control and validation regions. To avoid double-counting of the preselected jets, electrons, and muons, a sequence of overlap-removal procedures based on the angular distance ∆R = (∆y) 2 + (∆φ) 2 is applied. First, any jet reconstructed within ∆R < 0.2 of a preselected electron is rejected. This prevents electromagnetic energy clusters simultaneously reconstructed as an electron and a jet from being selected twice. Next, to remove bremsstrahlung from muons followed by a photon conversion into electron pairs, electrons within ∆R < 0.01 from a preselected muon are discarded. Subsequently, the contamination from muons from decays of heavy hadrons is suppressed by removing muons that are within ∆R < min(0.04 + (10 GeV)/p µ T , 0.4) from preselected jets meeting the previous criteria, or ∆R < 0.2 from a b-tagged jet or a jet containing more than three tracks with p T > 500 MeV. In the former case, the p T -dependent angular separation mitigates the rejection of energetic muons close to jets in boosted event topologies. Finally, jets reconstructed with ∆R < 0.2 from a preselected muon are rejected.

Signal electrons are required to satisfy the likelihood-based tight identification criteria detailed in Ref. [89]. Signal muons and electrons satisfy a sequence of ηand p T -dependent isolation requirements on trackingbased and calorimeter-based variables, defined as the GradientLoose [90] isolation criteria. Compatibility of the signal lepton tracks with the PV is enforced by requiring the distance |z 0 sin θ| to be less than 0.5 mm, where z 0 is the longitudinal impact parameter. In addition, the transverse impact parameter, d 0 , divided by its uncertainty, σ(d 0 ), must satisfy |d 0 /σ(d 0 )| < 3 for signal muons and |d 0 /σ(d 0 )| < 5 for signal electrons.

Corrections derived from data control samples are applied to simulated events to calibrate the reconstruction and identification efficiencies, the momentum scale and resolution of leptons and the efficiency and mis-tag rate of b-tagged jets.

Event selection

Each event must satisfy the trigger selection criteria, and must contain a reconstructed primary vertex. Non-collision background and detector noise are suppressed by rejecting events with any preselected jet not satisfying a set of quality criteria [91]. Exactly one signal lepton, either an electron or a muon, is required. Events with additional preselected leptons are rejected to suppress the dilepton tt, single-top (Wt-channel), Z+jets and diboson backgrounds. The following observables are used in the definition of signal regions in the analysis.

The missing transverse momentum, E miss T , is defined as the magnitude of p miss T , the negative vectorial sum of the transverse momenta of preselected muons, electrons, jets, and identified and calibrated photons. The calculation of p miss T also includes the transverse momenta of all tracks originating from the PV and not associated with any identified object [92, 93].

The transverse mass, m T , is defined from the lepton transverse momentum p T and p miss
T as m T = 2p T E miss T (1 − cos[∆φ( p T , p miss T )]),
where ∆φ( p T , p miss T ) is the azimuthal angle between p T and p miss T . For W+jets and semileptonic tt events, in which one on-shell W boson decays leptonically, the observable has an upper endpoint at the W-boson mass. The m T distribution for signal events extends significantly beyond the distributions of the W+jets and semileptonic tt events.

The effective mass, m eff , is the scalar sum of the p T of the signal lepton and all signal jets and E miss T :
m eff = p T + N jet j=1 p T, j + E miss T .
The effective mass provides good discrimination against SM backgrounds, especially for the signal scenarios where energetic jets are expected. Gluino production leads to higher jet multiplicity than squark production. High-mass sparticles tend to produce harder jets than low-mass sparticles. Thus the optimal m eff value depends on the different signal scenarios. To achieve sensitivity to a wide range of SUSY scenarios with a limited number of signal regions, this variable is binned in the final region definition instead of one simple m eff cut. The detailed description can be found in Section 5.1.

The transverse momentum scalar sum, H T , is defined as
H T = N jet j=1 p T, j ,
where the index j runs over all the signal jets in the event. Empirically, the experimental resolution of E miss T scales with H T , and the ratio E miss T / H T is useful for suppressing background events with large E miss T due to jet mismeasurement.

The aplanarity is a variable designed to provide more global information about the full momentum tensor of the event. It is defined as (3/2) × λ 3 , where λ 3 is the smallest eigenvalue of the normalized momentum tensor [94] calculated using the momenta of the jets and leptons in the event. Typical measured aplanarity values lie in the range 0 -0.3, with values near zero indicating relatively planar background-like events. Signal events tend to have high aplanarity values, since they are more spherical than background events due to multiple objects emitted in the sparticles decay chains.

Signal region definitions

Five sets of event selection criteria, each defining a signal region (SR), are designed to maximize the signal sensitivity. Each SR is labeled by the minimum required number of jets and, optionally, the characteristics of the targeted supersymmetric mass spectrum. Four of the five SRs, 2J, 4J high-x, 4J low-x, and 6J, target the gluino/squark one-step models. The fifth SR, 9J, targets the gluino two-step and pMSSM models. Table 2 summarizes the four SRs targeting the gluino/squark one-step models. The four SRs are mutually exclusive. For setting model-dependent exclusion limits ("excl"), each of the four SRs is further binned in b-veto/b-tag and m eff , and a simultaneous fit is performed across all 28 bins of the four SRs. This choice enhances the sensitivity to a range of new-physics scenarios with different properties such as the presence or absence in the final state of jets containing b-hadrons, and different mass separations between the supersymmetric particles. For model-independent limits and null-hypothesis tests ("disc" for discovery), the event yield above a minimum value of m eff in each SR is used to search for an excess over the SM background.

The 2J SR provides sensitivity to scenarios characterized by a relatively heavyχ 0 1 and small differences between mg, mχ ± 1 , and mχ 0 1 , where most of the decay products tend to have small p T . Events with one low-p T lepton and at least two jets are selected. The minimum lepton p T is 7 (6) GeV for the electron (muon), and the maximum p T is scaled with the number of signal jets in the event as 5 GeV × N jet up to 35 GeV. The maximum p T requirement balances background rejection and signal acceptance for models with increasing mass splittings, where there are more energetic lepton and jets. Stringent requirements on E miss T and on m eff enhance the signal sensitivity by selecting signal events in which the final-state neutralinos are boosted against energetic initial-state radiation (ISR) jets. The SM background is further suppressed by a tight requirement on E miss T /m eff . The 4J high-x SR is optimized for models where mχ 0 1 is fixed to 60 GeV and x ≈ 1, i.e., mχ ± 1 is close to mg. The W boson produced in the chargino decay is significantly boosted, giving rise to a high-p T lepton. The main characteristics of signal events in this model are large m T values and relatively soft jets emitted from the sparticle decay. Tight requirements are placed on E miss T , m T , and E miss T /m eff . The 4J low-x SR targets models where mχ 0 1 is fixed to 60 GeV and x ≈ 0, i.e., mχ ± 1 is close to mχ 0 1 . The large mg /q -mχ ± 1 mass splitting leads to high jet activity, where events are expected to have higher m eff and larger aplanarity than in the high-x scenarios. The W boson tends to be off-shell, leading to small m T , and accordingly an upper bound is imposed to keep this region orthogonal to the 4J high-x SR.  for gluino (squark) Table 3: Overview of the selection criteria for the signal region used for pMSSM and gluino two-step models. SR 9J
N = 1 = 1 = 1 = 1 p T [GeV] > 7(6) for e(µ) and > 35 > 35 > 35 < min(5 · N jet , 35) N jet ≥ 2 4-5 4-5 ≥ 6 E miss T [GeV] > 430 > 300 > 250 > 350 m T [GeV] > 100 > 450 150-450 > 175 Aplanarity ... > 0.01 > 0.05 > 0.06 E miss T /m eff > 0.25 > 0.25 ... ... N b−jet (excl) = 0 for b-veto, ≥ 1 for b-tag m eff [GeV] (excl) 3 bins ∈ [N = 1 p T [GeV] > 35 N jet ≥ 9 E miss T [GeV] > 200 m T [GeV] > 175 Aplanarity > 0.07 E miss T / H T [GeV 1/2 ] ≥ 8 m eff [GeV] (excl) [1000, 1500], [>1500] m eff [GeV] (disc) > 1500
The 6J SR is optimized for models with x = 1/2, targeting scenarios with large sparticle mass. Events with one high-p T lepton and six or more jets are selected. Requirements on m T , E miss T , m eff , and aplanarity are imposed to reduce the SM background from tt and W + jets production. The sensitivity is improved for scenarios with large mg /q and small mχ 0 1 by introducing a higher m eff bin. Finally, one signal region, 9J SR, is defined to target the pMSSM and gluino two-step models. The selection criteria are summarized in Table 3. At least nine jets are required, targeting the models' long decay chains in which multiple vector or Higgs bosons are produced. The background is further suppressed by tight requirements on the aplanarity and on E miss T / H T . For setting model-dependent exclusion limits ("excl"), the SR is separated into 1000 < m eff < 1500 GeV and m eff > 1500 GeV to achieve good discrimination power for different gluino masses. For model-independent null-hypothesis tests ("disc"), events selected with m eff > 1500 GeV are used to search for an excess over the SM background.

Background estimation

The dominant SM backgrounds in most signal regions originate from top quark (tt and single top) and W+jets production. In this section, the techniques employed to estimate the contribution of these backgrounds in the signal regions are detailed.

Additional sources of background in all signal regions originate from the production of Z+jets, tt in association with a W or Z boson, and diboson (WW, W Z, Z Z) events. Their contributions are estimated entirely using simulated event samples normalized to NLO cross-sections.

The contribution from multi-jet processes with a misidentified lepton is found to be negligible once the lepton isolation and E miss T requirements used in this search are imposed. A data-driven matrix method, following the implementation described in Ref. [21], determined this in previous iterations of the analysis [22]. As this background is found to be negligible, it is not further considered in the analysis.

The dominant top quark and W+jets backgrounds in the 2J, 4J high-x, 4J low-x, and 6J signal regions are estimated by simultaneously normalizing the predicted event yields from simulation to the number of data events observed in dedicated control regions (CR) using the fitting procedure described in Section 8. The simulation is then used to extrapolate the measured background rates to the corresponding signal regions.

The CRs are designed to have high purity in the background process of interest, a sufficiently large number of events to obtain small statistical uncertainties in the background prediction, and a small contamination by events from the signal models under consideration. Moreover, they are designed to have kinematic properties resembling as closely as possible those of the signal regions, in order to provide good estimates of the kinematics of background processes there. This procedure limits the impact of potentially large systematic uncertainties in the expected yields from the extrapolation.

Tables 4-7 list the criteria that define the control regions corresponding to signal regions 2J, 4J highx, 4J low-x, and 6J. As described in Section 5, these signal regions contain multiple bins in m eff . The same binning is maintained for the control regions, so that every signal region bin in m eff has corresponding control regions with the same requirements on m eff and, therefore, the backgrounds are estimated independently in each m eff bin.

Dedicated top and W+jets control regions, respectively denoted by TR and WR, are constructed in each bin of m eff . The TR and WR are distinguished by requiring at least one or exactly zero b-tagged signal jets, respectively. Cross-contamination from top and W+jets processes between these two types of control regions is accounted for in the fit. The measured top and W+jets background rates from the TR and WR regions in a given m eff bin are extrapolated to the signal region within the same m eff bin. The signal regions in a given m eff bin may be further separated into regions with at least one or exactly zero b-tagged signal jets as described in Section 5. For such signal regions separated by b-tagged jet multiplicity, the extrapolation is performed from both the TR and WR regions to each individual bin of b-tagged jet multiplicity.

To validate the extrapolation from control to signal regions using simulated event samples, dedicated validation regions (VRs) are defined for each set of control and signal regions. The selection criteria defining these VRs are also shown in Tables 4-7. The same binning in m eff used in the control and signal regions is also maintained in the validation regions. The VRs are designed to be kinematically close to the signal regions, with only a small contamination from the signal in the models considered in this search. The VRs are not used to constrain parameters in the fit, but provide a statistically independent cross-check Table 4: Overview of the control and validation region selection criteria corresponding to the 2J SR. The top and W+jets control regions are denoted by TR and WR, respectively.

2J

WR   of the extrapolation. The observed event yields in the VRs are found to be consistent with the background prediction as further discussed in Section 8.
/ TR VR E miss T VR m T N = 1 p T [GeV] > 7(6) for e(µ) and < min(5 · N jet , 35) N jet ≥ 2 N b−jet = 0 / ≥ 1 ... ... m T [GeV] [N = 1 p T [GeV] > 35 N jet 4-5 N b−jet = 0 / ≥ 1 ... ... ... m T [GeV] [
One of the dominant background components in the 2J, 4J high-x, 4J low-x, and 6J SRs is tt production with dileptonic final state, where one lepton fails to be reconstructed ("missing lepton") or is a semihadronically decaying τ lepton; this background is characterized by high values of m T . To validate the above described background estimation technique, which is largely a simulation-based extrapolation from low-m T control regions populated by events with semileptonic tt decays, an alternative method was developed. This method (hereafter referred to as the object replacement method) uses events in a dileptonic control region. To emulate the missing lepton case, the p T of one of the two leptons is added vectorially to the calculation of E miss T . To emulate the hadronic τ decay case, one of the two leptons is re-simulated as a hadronic tau decay using the Tauola generator [95] with appropriate energy scale and resolution corrections. The accuracy of this alternative background estimation technique was validated on simulated samples as well as in data validation regions. The background estimates derived from this object replacement method are found to be consistent with those obtained from the standard semi-data-driven approach as further demonstrated in Section 8.

While the background estimation strategy described above works well for the signal regions 2J, 4J    high-x, 4J low-x, and 6J, it is not viable for the 9J SR. The reason for this is that the simulation-based extrapolation from the control regions, which are typically located around the peak region of the transverse mass distribution (m T ∼ 80 GeV), to the high-m T signal regions (m T 80 GeV) is affected by large theoretical uncertainties at high jet multiplicities. Because the peak and tail regions of the m T distribution are dominated by semileptonic and dileptonic final states from tt decays, respectively, additional jets from initial-or final-state radiation are required to obtain the same jet multiplicity for dileptonic tt final states. Inadequate modeling of such additional jets is the dominant source of the theoretical uncertainty. To reduce the dependence on the modeling of additional jets, a dedicated data-driven background estimation technique was designed for the 9J SR. The method relies on the assumption that the m T distribution is approximately invariant under changes in the jet multiplicity requirements. This assumption is found to be valid when tight m eff requirements as used in this analysis are applied such that the overall activity in the calorimeter and thus the missing transverse momentum resolution are not significantly affected by variations in the jet multiplicity. Based on the m T invariance, mutually exclusive control regions CR A,B,C are defined in the m T -N jet plane, where CR A is located at high m T and low N jet , CR B at low m T and low N jet , and CR C at low m T and high N jet . The precise requirements of these regions are defined in Table 8 and illustrated in Figure 2. Based on these regions, the background in the high m T and high N jet signal region can then be estimated with the following equation Table 8: Overview of the control and validation region selection criteria corresponding to the 9J SR. The control regions CR A,A ,B,C,C are further divided into bins of exactly 0 or ≥ 1 b-tagged signal jets to enrich top and W+jets backgrounds, respectively.
N = 1 p T [GeV] > 35 N jet 4-5 N b−jet = 0 / ≥ 1 ... ... m T [GeV][N = 1 p T [GeV] > 35 N jet ≥ 6 N b−jet = 0 / ≥ 1 ... ... m T [GeV][

CR A CR B CR C VR m T CR C VR N jet CR A N = 1 p T [GeV] ≥ 35 N jet 5-6 5-6 ≥ 9 7-8 7-8 ≥ 9 5-6 p jet T [GeV] ≥ 30 N b−jet = 0 / ≥ 1 = 0 / ≥ 1 = 0 / ≥ 1 ... = 0 / ≥ 1 ... = 0 / ≥ 1 m T [GeV] > 175<N CR A N CR B = N est SR 9J N CR C → N est SR 9J = N CR A N CR B N CR C ,
where N est <region> is the (estimated) number of events in a given region. The residual small correlations between m T and N jet that bias the background estimate in the signal region can then be expressed in terms of a simulation-based closure parameter defined as
f closure = N sim SR 9J N sim,est SR 9J = N sim SR 9J · N sim CR B N sim CR C · N sim CR A ,
where N sim <region> is the number of events in a given region as predicted by simulation while N sim,est SR 9J

is the estimated number of events in the signal region based on the simulation predictions in regions A, B, and C. The estimated number of background events in the signal region can then be rewritten as
N est SR 9J = f closure · N obs CR A N obs CR B · N obs CR C = N sim SR 9J · N CR A N CR B N CR C obs N CR A N CR B N CR C sim = N sim SR 9J · N obs CR C N sim CR C µ C · N CR A N CR B obs N CR A N CR B sim µ A/B ,
where N obs <region> is the observed number of events in a given region, µ C is the normalization parameter in region C, and the normalization parameter µ A/B is fitted simultaneously with the normalization µ B of the backgrounds in region CR B according to
N obs CR B = N sim CR B · N obs CR B N sim CR B µ B and N obs CR A = N sim CR A · N CR A N CR B obs N CR A N CR B sim µ A/B N obs CR B N sim CR B µ B .
The control regions listed in Table 8 are optimized to provide a sufficient number of events in the backgrounds of interest, low contamination from the signal models considered, and a closure parameter f closure close to unity. All control regions are fitted simultaneously in two bins requiring either zero or at least one b-tagged signal jet to enrich the contributions from the W+jets and top backgrounds, respectively. Therefore, the normalization factors µ B , µ C , and µ A/B exist separately for the W+jets and top backgrounds. The top backgrounds considered in the fit comprise tt as well as single-top production processes, which are treated with a common set of normalization parameters.

To validate that the fitted ratio of low-m T to high-m T events (µ A/B ) extrapolates to high values of N jet , a validation region VR m T with seven or eight jets and high m T requirements is introduced. Similarly, a validation region VR N jet with at least nine jets and moderate m T requirements is introduced to validate the extrapolation of the normalization factor µ C in region CR C to higher m T values. Since the normalization factors for different jet multiplicities are expected to differ, a control region CR C along with its normalization factor (µ C ) is introduced. This region is only used to obtain the background estimate in VR m T . Similarly, a control region CR A is constructed to obtain the normalization factor µ A /B that is needed for the background estimation in validation region VR N jet . The definition of the validation regions along with their corresponding control regions is given in Table 8.

Systematic uncertainties

Experimental and theoretical sources of systematic uncertainty are described in this section. Their effects are evaluated for all simulated signal and background events.

The dominant experimental systematic effects are the uncertainties associated with the jet energy scale (JES) and resolution (JER) and with the b-tagging efficiency and mis-tagging rate. The impact of the jet-related uncertainties on the total background prediction ranges from 1.3% in the 6J SR to 18% in the 9J SR. Similarly, the impact of the uncertainties associated with the b-tagging procedure amounts to 1.9% in the 6J SR bins with at least one b-tagged jet and increases to 9.5% in the 6J SR bins with no b-tagged jets. The simulation is reweighted to match the distribution of the average number of proton-proton interactions per bunch crossing (µ) observed in data. The uncertainty in µ is propagated by varying up and down the reweighting factor: it becomes relevant in the signal regions characterized by the highest jet multiplicities.

Uncertainties in the theoretical predictions and the modeling of simulated events are also considered. For the W+jets and the tt and single top backgrounds, they affect the extrapolation from each m eff bin in the control regions to the corresponding bin in the signal regions. In the 9J SR the f closure parameter used in the background estimation in this channel is affected as well. For all the other background sources, they impact the inclusive cross-section of each specific process, the acceptance of the analysis selection requirements and the shape of the m eff distribution in each SR.

An uncertainty stems from the choice of MC event generator modeling the tt, single top, diboson and W/Z+jets processes. For tt and single top, P -B is compared with MG5_ M @NLO [38] and the relative difference in the extrapolation factors is evaluated. For W/Z+jets, the predictions from S are compared with MG5_ M @NLO [38]. For dibosons, the event yield predictions from S are compared with -interfaced to P . The impact of varying the amount of initialand final-state radiation is evaluated for tt and single top production. Specific samples are used, with altered renormalization and factorization scales as well as parton shower and NLO radiation [50]. Moreover, the difference between the predictions from -interfaced to P and to H ++ [96] is computed to estimate the uncertainty associated with the parton shower modeling. For W/Z+jets samples, the uncertainties in the renormalization, factorization, resummation scales and the matching scale between matrix elements and parton shower (CKKW-L) are evaluated by varying up and down by a factor of two the corresponding parameters in S . For tt and W+jets samples, the uncertainties due to choosing the PDF set CT10 [52] are considered.

Inclusive WW bb events generated using MG5_ MC@NLO [38] are compared to the sum of tt and Wt production, to assign an uncertainty to the interference effects between single top and tt production at NLO. The uncertainty in the inclusive Z+jets cross-section, amounting to 5%, is accounted for [97]. An overall 6% systematic uncertainty in the inclusive cross-section of diboson processes is also considered. In Table 9: Breakdown of the dominant systematic uncertainties in the background estimates in the 2J and 4J highx SRs. The individual uncertainties can be correlated and do not necessarily add up in quadrature to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background.   addition, the S parameters controlling the renormalization, factorization, resummation and matching scales are varied by a factor of two to estimate the corresponding uncertainties. An uncertainty of 30% is assigned to the small contributions of tt + W/Z/WW.

Signal region
2J b-tag 2J b-veto 4J high-x b-tag 4J high-x b-veto

Signal region
4J low-x b-tag 4J low-x b-veto 6J b-tag 6J b-veto
The total systematic uncertainty in the predicted background yields in the various signal regions ranges from 12% in the 2J SR bins with ≥ 1 b-tagged jet, to 50% in the 9J SR. The largest uncertainties in the SR bins with ≥ 1 b-tagged jet originate from the modeling of tt events and amount to 5% in the 2J SR, increasing to 40% in the 9J SR. Similarly, in the SR bins where b-tagged jets are vetoed, the dominant source of systematic uncertainty is the modeling of W+jets events, ranging from 9% in the 6J SR to 20% in the 4J low-x SR. Other important uncertainties are those associated with the finite size of the MC samples, which amount to 18% in the 6J SR, and the theoretical uncertainties originating from the modeling of the diboson background, amounting to 26% in the 6J SR. Tables 9-11 list the breakdown of the dominant systematic uncertainties in background estimates in the various signal regions.

For the signal processes, the modeling of initial-state radiation can be affected by sizable theoretical uncertainty. The uncertainties in the expected yields for SUSY signal models are estimated with variations of a factor of two to the MG5_ MC@NLO parameters corresponding to the renormalization, factorization Table 11: Breakdown of the dominant systematic uncertainties in the background estimates in the 9J SR. The individual uncertainties can be correlated and do not necessarily add up in quadrature to the total background uncertainty. The percentage shows the size of the uncertainty relative to the total expected background.

Signal region 9J

Total background expectation 7

Total background systematic uncertainty ±4 [50%]

Statistical uncertainty of MC samples ±0.7

and jet matching scales, and to the P shower tune parameters. The overall uncertainties range from about 1% for signal models with large mass splitting between the gluino or squark, the chargino, and the neutralino, to 35% for models with very compressed mass spectra.

Results and Interpretation

The statistical interpretation of the results is performed based on a profile likelihood method [98] using the HistFitter framework [99]. The likelihood function consists of a product of Poisson probability density functions for the signal and control regions that contribute to the fit. The inputs to the likelihood function are the observed numbers of data events and the expected numbers of signal and SM background events in each region. Three normalization factors, one for signal, one for W + jets, one for tt and single top, are introduced to adjust the relative contributions of the main background and signal components. The small sources of SM background, i.e., diboson, Z + jets and tt + V, are estimated directly from simulation. The uncertainties are implemented in the fit as nuisance parameters, which are correlated between the SRs and the CRs. The systematic uncertainties described in Section 7 are constrained by Gaussian probability density functions, while the statistical uncertainties are constrained by Poisson probability density functions.

The observed numbers of events in the signal regions are given in Tables 12-14, along with the SM background prediction as determined with the background-only fit. In a background-only fit, the data event yields in the CRs are used to determine the two background normalization factors: for W + jets and for tt and single top production. The fit is independent of the observation in the SR, and does not consider signal contamination in the CRs. The above-mentioned signal normalization parameter is therefore not included in this fit configuration.

The compatibility of the observed and expected event yields in both the validation and signal regions is illustrated in Figures 3-7. No significant excess in data is observed over the SM prediction.

The top and W + jets background normalization factors obtained for the 2J, 4J low-x, 4J high-x, and 6J SRs are shown in bins of m eff in Figure 8. A trend toward smaller normalization factors at large values of m eff is observed, which demonstrates the necessity of applying the same binning requirements in control and  [GeV]. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. The uncertainties in this table are symmetrized for propagation purposes but truncated at zero to remain within the physical boundaries.

2J b-tag

All   signal regions. The predicted event yields from tt events in which both top quarks decay semileptonically are cross-checked using the alternative object-replacement method described in Section 6. Figure 9 shows that the background estimates obtained from the two methods are consistent. Figures 10-11 show the m eff distribution in 2J, 4J low-x, 4J high-x and 6J in b-tag and b-veto signal regions after fit. Figure 12 shows the m eff distribution in 9J signal region after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

Using the results of the background-only fit, a model-independent limit fit is performed to test for the presence of any beyond-the-Standard-Model (BSM) physics processes that contribute to the SR ("disc" SR in Table 2) . The BSM signal is assumed to contribute only to the SR and not to the CRs, thus giving a conservative estimate of background in the SR. Observed (S 95 obs ) and expected (S 95 exp ) 95% confidence level (CL) upper limits on the number of BSM signal events are derived using the CL s prescription [100]. Table 15 presents these limits, together with the upper limits on the visible BSM cross-section, σ 95 obs , defined as the product of acceptance, selection efficiency and production cross-section. The upper limits on the visible BSM cross-section are calculated by dividing the observed upper limit on the beyond-SM events by the integrated luminosity of 36.1 fb −1 . Moreover, the discovery p-values are given. They quantify the probability under the background-only hypothesis to produce event yields greater than or equal to the observed data.

Additionally, the results are interpreted in the specific supersymmetric scenarios described in Section 3 using model-dependent limit fits. A model-dependent limit fit takes the data event yields in multiple, statistically independent SRs and their associated CRs to compute an upper limit on the cross-section of a targeted SUSY model. The fit includes the expected signal contributions to the SRs and to the CRs, scaled by a floating signal normalization factor. The background normalization factors are also determined simultaneously in the fit.

The sparticle mass in a specific SUSY model can be excluded if the upper limit of the signal normalization factor obtained in the fit is smaller than unity.

For the gluino/squark one-step models, a model-dependent fit is performed over all bins of the 2J, 4J high-x, 4J low-x, and 6J SRs. An independent set of background normalization factors are allocated for each bin of each SR ("excl" SR in Table 2) and its associated CRs. Figure 13 (top and middle) shows the observed and expected exclusion bounds at 95% CL for the one-step simplified models with gluino and squark production. Gluino masses up to 2.1 TeV and squark masses up to 1.25 TeV are excluded. Figure 13 (bottom) shows the exclusion contours of the 9J SR (Table 3) for the gluino two-step as well as the pMSSM scenario described in Section 3. In both cases the limits reach well beyond 1.7 TeV in gluino mass.  Table 15: Results of the model-independent limit fits. For each SR, the observed 95% CL upper limit on the visible cross-section ( σ 95 obs ), the observed (S 95 obs ) and expected (S 95 exp ) 95% CL upper limits on the BSM event yield, and the one-sided discovery p-value (p(s = 0)) are presented. The p-values are capped at 0.5 if fewer events than the fitted background estimate are observed.
V R m V R m V R m V R m V R m V R E V R E V R E V R E V R E S R b -t a g S R b -t a g m S R b -t a g m S R b -t a g m S R b -t a g m S R b -v e to S R b -v e to m S R b -v e to m S R b -v e to m S R b -v e

SR
V R m V R m V R m V R m V R h y b ri d V R h y b ri d m V R h y b ri d m V R h y b ri d m
V R a p la n a ri ty V R a p la n a ri ty m V R a p la n a ri ty m V R a p la n a ri ty m
S R b -t a g S R b -t a g m S R b -t a g m S R b -t a g m S R b -v e to S R b -v e to m S R b -v e to m S R b -v eV R m V R m V R m V R m V R m
V R a p la n a ri ty V R a p la n a ri ty m V R a p la n a ri ty m V R a p la n a ri ty m V R a p la n a ri ty m        Figure 13: Exclusion contours for gluino one-step x = 1/2 (top left), gluino one-step variable-x (top right), squark one-step x = 1/2 (middle left) and squark one-step variable-x (middle right), gluino two-step (bottom left), and the pMSSM scenario (bottom right). The red solid line corresponds to the observed limit with the red dotted lines indicating the ±1σ variation of this limit due to the effect of theoretical scale and PDF uncertainties in the signal cross-section. The dark gray dashed line indicates the expected limit with the yellow band representing the ± 1 σ variation of the median expected limit due to the experimental and theoretical uncertainties. For reference, exclusion bounds from previous searches with 20.3 fb −1 at 8 TeV center-of-mass energy [28] and 3.2 fb −1 at 13 TeV center-ofmass energy [22,30] are overlaid where applicable by the gray area (the observed limit is shown by the solid line, while the dashed line shows the expected limit) .
S R b -t a g S R b -t a g m S R b -t a g m S R b -t a g m S R b -t a g m S R b -v e to S R b -v e to m S R b -v e to m S R b -v e to m S R b -v e

Conclusion

A search for the pair production of squarks and gluinos in proton-proton collisions provided by the LHC at a center-of-mass energy of √ s = 13 TeV has been performed by the ATLAS Collaboration. Events containing one isolated electron or muon, two or more jets, and large missing transverse momentum are selected in the data collected in 2015 and 2016, corresponding to an integrated luminosity of 36.    [79] M. Cacciari, G. P. Salam      [94] C. Chen, New approach to identifying boosted hadronically decaying particles using jet substracture in its center-of-mass frame, Phys.

Figure 1 :
1The decay topologies of the simplified signal models considered in this search: gluino one-step (left), squark one-step (middle), and gluino two-step (right).

The search presented in this paper uses the ATLAS data collected in proton-proton collisions at the LHC during 2015 and 2016 at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 36.1 fb −1 . The analysis extends previous ATLAS searches with similar event selections performed with data collected in 2010-2012 (LHC Run-1) [21] and in 2015 (Run-2) [22], at center-of-mass energies of 8 TeVand 13 TeV, respectively. Similar searches for gluinos and squarks with decays via intermediate supersymmetric particles were performed by the CMS Collaboration in Run 1 [23, 24] and Run 2 [25-27].

For the tt + W/Z/WW processes [69], all events were simulated using MG5_ MC@NLO 2.2.2 at LO interfaced to the P 8.186 parton shower model, with up to two (tt + W), one (tt + Z) or no (tt + WW) extra partons included in the matrix element. The EvtGen 1.2.0 program [43] was used to describe the properties of the bottom and charm hadron decays. The ATLAS shower and underlying-event tune A14 was used together with the NNPDF2.3 LO PDF set. The events are normalized using their NLO cross-sections [70, 71].

Three-dimensional topological energy clusters in the calorimeters are used as input to the anti-k t algorithm with a radius parameter R = 0.4 [78-80] to reconstruct preselected jets. The effect of multiple interactions per proton bunch crossing (pileup) is accounted for using the jet area method[81, 82]. Subsequent calibrations are applied to the reconstructed jet to improve the energy resolution[83, 84]. The residual contamination by pileup jets is further suppressed using a multivariate discriminant that estimates the compatibility of the jet with the PV, as detailed in Ref.[85].Signal jets must satisfy p T > 30 GeV and |η| < 2.8. Signal jets within |η| < 2.5 are identified as candidates for containing b-hadrons (b-tagged) using the MV2c10 algorithm [86, 87]. This b-tagging algorithm provides an overall efficiency of 77% for jets containing b-hadrons in simulated tt events, with rejection factors of 6 and 134 on charm and light-jets, respectively [88]. Electron candidates are reconstructed by matching an isolated energy cluster in the electromagnetic calorimeter to at least one ID track. Preselected electrons are identified with the likelihood-based Loose criterion described in Ref. [89] with additional requirements on the number of hits in the innermost pixel layer to discriminate against photon conversions. Furthermore, preselected electrons are required to satisfy p T > 7 GeV and |η| < 2.47. Muon candidates are formed by a combined re-fitting of tracks reconstructed in the ID and the MS subsystems. Preselected muons are required to have p T > 6 GeV and |η| < 2.5, and satisfy the Medium identification criteria in Ref. [90].

Figure 2 :
2Illustration of the control and validation region configuration corresponding to the 9J SR. The control regions that are used for the background estimation in the signal region are indicated by red lines, while the blue lines indicate control regions that are used for the background estimation in the validation regions and the validation regions themselves. The definitions for all regions are given in

Figure 3 :Figure 4 :
34Comparison of the observed and expected event yields in the 2J validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each m eff bin are presented. Comparison of the observed and expected event yields in the 4J low-x validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each m eff bin are presented.

Figure 5 :
5Comparison of the observed and expected event yields in the 4J high-x validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each m eff bin are presented.

Figure 6 :Figure 7 :
67Comparison of the observed and expected event yields in the 6J validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each m eff bin are presented. Comparison of the observed and expected event yields in the 9J validation and signal regions. Uncertainties in the background estimates include both the statistical (in the simulated event yields) and systematic uncertainties. Both the integrated regions and the regions for each m eff bin are presented.

Figure 8 :
8Normalization factors µ top and µ W of the top and W + jets backgrounds in the m eff bins of the 2J, 4J high-x, 4J low-x, and 6J SRs obtained with the background-only fit. The error bars correspond to the uncertainties as derived in the fit.

Figure 9 :Figure 10 :Figure 11 :
91011Comparison of estimated Standard Model background event yield from tt processes with dileptonic decays in the 2J, 4J high-x, 4J low-x, and 6J SR using the nominal semi-data-driven background estimation technique and the alternative object-replacement technique described in Section 6. The error bands include both the statistical and systematic uncertainties. The m eff distribution in 2J (top left), 4J low-x (top right), 4J high-x (bottom left) and 6J (bottom right) b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples. The m eff distribution in 2J (top left), 4J low-x (top right), 4J high-x (bottom left) and 6J (bottom right) b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

Figure 12 :
12The m eff distribution in the 9J signal region after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.

[ 73 ]
73S. Agostinelli et al., GEANT4: A Simulation toolkit, Nucl. Instrum. Meth. A 506 (2003) 250. [74] ATLAS Collaboration, The simulation principle and performance of the ATLAS fast calorimeter simulation FastCaloSim, ATL-PHYS-PUB-2010-013 (2010), : https://cds.cern.ch/record/1300517. [75] ATLAS Collaboration, Summary of ATLAS Pythia 8 tunes, ATL-PHYS-PUB-2012-003 (2012), : https://cds.cern.ch/record/1474107.

[ 76 ]
76A. D. Martin, W. J. Stirling, R. S. Thorne and G. Watt, Parton distributions for the LHC, Eur. Phys. J. C 63 (2009) 189, arXiv: 0901.0002 [hep-ph].[77] ATLAS Collaboration, Luminosity determination in pp collisions at √ s = 8 TeV using the ATLAS detector at the LHC, Eur. Phys. J. C 76 (2016) 653, arXiv: 1608.03953 [hep-ex].

[ 78 ]
78M. Cacciari, G. P. Salam and G. Soyez, The anti-k t jet clustering algorithm, JHEP 04 (2008) 063, arXiv: 0802.1189 [hep-ph].

[ 83 ]
83ATLAS Collaboration, Jet Calibration and Systematic Uncertainties for Jets Reconstructed in the ATLAS Detector at √ s = 13 TeV, ATL-PHYS-PUB-2015-015 (2015), : https://cds.cern.ch/record/2037613.

[ 84 ]
84ATLAS Collaboration, Jet energy scale measurements and their systematic uncertainties in proton-proton collisions at √ s = 13 TeV with the ATLAS detector, (2017), arXiv: 1703.09665 [hep-ex]. [85] ATLAS Collaboration, Tagging and suppression of pileup jets with the ATLAS detector, ATLAS-CONF-2014-018 (2014), : https://cds.cern.ch/record/1700870. [86] ATLAS Collaboration, Expected performance of the ATLAS b-tagging algorithms in Run-2, ATL-PHYS-PUB-2015-022 (2015), : https://cds.cern.ch/record/2037697. [87] ATLAS Collaboration, Commissioning of the ATLAS b-tagging algorithms using tt events in early Run-2 data, ATL-PHYS-PUB-2015-039 (2015), : https://cds.cern.ch/record/2047871. [88] ATLAS Collaboration, Optimisation of the ATLAS b-tagging performance for the 2016 LHC Run, ATL-PHYS-PUB-2016-012 (2016), : https://cds.cern.ch/record/2160731. [89] ATLAS Collaboration, Electron efficiency measurements with the ATLAS detector using the 2015 LHC proton-proton collision data, ATLAS-CONF-2016-024 (2016), : https://cds.cern.ch/record/2157687. [90] ATLAS Collaboration, Muon reconstruction performance of the ATLAS detector in proton-proton collision data at √ s =13 TeV, Eur. Phys. J. C 76 (2016) 292, arXiv: 1603.05598 [hep-ex].

[ 91 ]
91ATLAS Collaboration, Selection of jets produced in 13 TeV proton-proton collisions with the ATLAS detector, ATLAS-CONF-2015-029 (2015), : https://cds.cern.ch/record/2037702. [92] ATLAS Collaboration, Expected performance of missing transverse momentum reconstruction for the ATLAS detector at √ s = 13 TeV, ATL-PHYS-PUB-2015-023 (2015), : https://cds.cern.ch/record/2037700.

[ 93 ]
93ATLAS Collaboration, Performance of missing transverse momentum reconstruction for the ATLAS detector in the first proton-proton collisions at √ s= 13 TeV, ATL-PHYS-PUB-2015-027 (2015), : https://cds.cern.ch/record/2037904.

Table 1 :
1Simulated signal and background event samples: the corresponding event generator, parton shower, crosssection normalization, PDF set and underlying-event tune are shown.Physics process
Generator
Parton shower
Cross-section
PDF set
Tune

Signal
MG5_ MC@NLO 2.2.2 P
8.186
NLO+NLL
NNPDF2.3 LO
ATLAS A14

tt
P
-B v2
P
6.428 NNLO+NNLL
CT10 NLO
P
2012
Single-top
t-channel
P
-B v1
P
6.428
NLO
CT10f4 NLO
P
2012
s-channel
P
-B v2
P
6.428
NLO
CT10 NLO
P
2012
Wt-channel
P
-B v2
P
6.428
NLO+NNLL
CT10 NLO
P
2012
W(→ ν) + jets
S
2.2.1
S
NNLO
NNPDF3.0 NNLO S
default
Z/γ  *  (→ ) + jets S
2.2.1
S
NNLO
NNPDF3.0 NNLO S
default

WW, W Z and Z Z
S
2.1.1 /
S
NLO
CT10 NLO /
S
default
S
2.2.1
NNPDF3.0 NNLO
tt + W/Z/WW
MG5_ MC@NLO 2.2.2 P
8.186
NLO
NNPDF2.3 LO
ATLAS A14

Table 2 :
2Overview of the selection criteria for the signal regions used for gluino/squark one-step models.SR
2J
4J high-x
4J low-x
6J

Table 5 :
5Overview of the control and validation region selection criteria corresponding to the 4J high-x SR. The top and W+jets control regions are denoted by TR and WR, respectively.4J high-x WR / TR VR Aplanarity VR m T VR Hybrid

Table 6 :
6Overview of the control and validation region selection criteria corresponding to the 4J low-x SR. The top and W+jets control regions are denoted by TR and WR, respectively.4J low-x
WR / TR
VR Aplanarity VR Hybrid

Table 7 :
7Overview of the control and validation region selection criteria corresponding to the 6J SR. The top and W+jets control regions are denoted by TR and WR, respectively.6J
WR / TR VR Aplanarity
VR m T

Table 8 (
8control and validation regions).

Table 10 :
10Breakdown of the dominant systematic uncertainties in the background estimates in the 4J low-x and 6J SRs. The individual uncertainties can be correlated and do not necessarily add up in quadrature to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background.

Table 12 :
12Event yields and background-only fit results for the 2J and 4J high-x SRs. Each column corresponds to a bin in m eff

Table 13 :
13Event yields and background-only fit results for the 4J low-x and 6J SRs. Each column corresponds to a bin in m eff[GeV]. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. The uncertainties in this table are symmetrized for propagation purposes but truncated at zero to remain within the physical boundaries.4J low-x b-tag
All m eff bins
[1300,1650]
[1650,2000]
> 2000 [GeV]

Observed events
31
19
6
6

Fitted bkg events
31 ± 6
20 ± 5
6.6 ± 2.3
4.4 ± 1.6

Fitted tt events
19 ± 5
13 ± 4
4.3 ± 1.6
2.1 ± 1.0
Fitted W+jets events
2.4 ± 1.1
1.6 ± 1.1
0.40 ± 0.20
0.40 ± 0.20
Fitted Z+jets events
0.10 ± 0.05
0.037 ± 0.033
0.017 ± 0.014
0.042 ± 0.030
Fitted single-top events
6.5 ± 3.4
3.5 ± 2.8
1.5 ± 1.5
1.5 ± 1.1
Fitted diboson events
1.2 ± 0.9
0.7 ± 0.4
0.20 ± 0.20
0.30 ± 0.30
Fitted ttV events
1.41 ± 0.14
1.03 ± 0.12
0.24 ± 0.05
0.14 ± 0.04
4J low-x b-veto
All m eff bins
[1300,1650]
[1650,2000]
> 2000 [GeV]

Observed events
19
7
7
5

Fitted bkg events
16 ± 4
10.0 ± 3.0
3.5 ± 1.1
2.7 ± 1.1

Fitted tt events
2.3 ± 0.8
1.6 ± 0.6
0.40 ± 0.20
0.30 ± 0.20
Fitted W+jets events
7.5 ± 2.6
4.6 ± 2.3
1.9 ± 0.8
1.0 ± 0.5
Fitted Z+jets events
0.18 ± 0.09
0.06 +0.06

−0.06

0.05 ± 0.04
0.070 ± 0.032
Fitted single-top events
1.2 ± 0.7
0.5 ± 0.4
0.20 ± 0.20
0.5 ± 0.4
Fitted diboson events
4.9 ± 3.3
3.2 ± 1.9
1.0 ± 0.7
0.7 +0.9

−0.7

Fitted ttV events
0.125 ± 0.031
0.099 ± 0.023
0.014 ± 0.008
0.012 +0.014

−0.012

6J b-tag
All m eff bins
[700,1233]
[1233,1767]
[1767,2300]
> 2300 [GeV]

Observed events
31
6
16
9
0

Fitted bkg events
27 ± 4
8.5 ± 2.0
12.1 ± 2.7
4.1 ± 1.0
2.0 ± 0.5

Fitted tt events
19 ± 4
6.1 ± 1.8
9.1 ± 2.5
2.6 ± 0.8
1.1 ± 0.4
Fitted W+jets events
0.75 ± 0.29
0.20 ± 0.20
0.30 ± 0.10
0.20 ± 0.10
0.10 ± 0.10
Fitted Z+jets events
0.07 ± 0.06
...
0.025 +0.026

−0.025

0.029 +0.035

−0.029

0.014 ± 0.009
Fitted single-top events
3.1 ± 1.1
0.7 ± 0.5
1.3 ± 0.8
0.6 ± 0.4
0.40 ± 0.30
Fitted diboson events
0.8 ± 0.7
0.20 ± 0.20
0.30 ± 0.20
0.20 ± 0.20
0.10 ± 0.10
Fitted ttV events
2.9 ± 0.5
1.20 ± 0.20
1.10 ± 0.30
0.50 ± 0.10
0.2 ± 0.0
6J b-veto
All m eff bins
[700,1233]
[1233,1767]
[1767,2300]
> 2300 [GeV]

Observed events
6
3
2
1
0

Fitted bkg events
7.3 ± 2.0
2.1 ± 1.1
3.4 ± 0.8
1.2 ± 0.5
0.60 ± 0.30

Fitted tt events
1.6 ± 0.5
0.50 ± 0.20
0.80 ± 0.30
0.20 ± 0.10
0.069 ± 0.031
Fitted W+jets events
2.4 ± 0.9
0.6 +0.8

−0.6

1.1 ± 0.4
0.50 ± 0.30
0.20 ± 0.10
Fitted Z+jets events
0.29 ± 0.13
0.1 ± 0.0
0.20 ± 0.10
0.026 ± 0.015
0.038 ± 0.032
Fitted single-top events 0.48 ± 0.21
0.10 ± 0.10
0.20 ± 0.10
0.10 ± 0.10
0.10 ± 0.10
Fitted diboson events
2.4 ± 1.9
0.7 ± 0.7
1.1 ± 0.7
0.4 ± 0.4
0.20 ± 0.20
Fitted ttV events
0.13 ± 0.04 0.023 ± 0.021 0.089 ± 0.021 0.015 ± 0.010 0.0059 ± 0.0021

Table 14 :
14Event yields and background-only fit results for the 9J SR. Each column corresponds to a bin in m eff[GeV]. Uncertainties in the fitted background estimates combine statistical (in the simulated event yields) and systematic uncertainties. The uncertainties in this table are symmetrized for propagation purposes but truncated at zero to remain within the physical boundaries.9J
All m eff bins
[1000,1500]
> 1500 [GeV]

Observed events
10
6
4

Fitted bkg events
7 ± 4
4.0 ± 2.6
3.1 ± 1.6

Fitted W+jets events
0.028 +0.057

−0.028

0.006 +0.018

−0.006

0.022 +0.043

−0.022

Fitted tt events
6 ± 4
3.6 ± 2.5
2.3 ± 1.6
Fitted single-top events
0.7 ± 0.6
0.18 +0.27

−0.18

0.5 ± 0.4
Fitted tt + V events
0.30 ± 0.17
0.14 ± 0.09
0.16 ± 0.09
Fitted diboson events
0.15 +0.16

−0.15

0.029 +0.041

−0.029

0.12 ± 0.12
Fitted Z+jets events
0.008 +0.011

−0.008

...
0.008 +0.011

−0.008

1 fb −1 . No significant excess over the Standard Model background prediction is observed. Exclusion limits are set at 95% CL on generic new phenomena beyond the Standard Model and on sparticle masses in a number of specific SUSY scenarios. The exclusion limits extend up to 2.1 TeV in gluino mass and 1.25 TeV in squark mass thus significantly improving on the sensitivity of previous searches in this final state. [19] J. Alwall, P. Schuster and N. Toro, Simplified Models for a First Characterization of New Physics at the LHC, Phys. Rev. D 79 (2009) 075020, arXiv: 0810.3921 [hep-ph]. [20] D. Alves et al., Simplified Models for LHC New Physics Searches, J. Phys. G 39 (2012) 105005, arXiv: 1105.2838 [hep-ph]. [21] ATLAS Collaboration, Search for squarks and gluinos in events with isolated leptons, jets and missing transverse momentum at √ s = 8 TeV with the ATLAS detector, JHEP 04 (2015) 116, arXiv: 1501.03555 [hep-ex]. [22] ATLAS Collaboration, Search for gluinos in events with an isolated lepton, jets and missing transverse momentum at √ s = 13 TeV with the ATLAS detector, Eur. Phys. J. C 76 (2016) 565, arXiv: 1605.04285 [hep-ex]. [23] CMS Collaboration, Search for new physics in events with same-sign dileptons and jets in pp collisions at √ s = 8 TeV, JHEP 01 (2014) 163, [Erratum: JHEP 01 (2015) 014], arXiv: 1311.6736 [hep-ex]. [24] CMS Collaboration, Search for new physics in the multijet and missing transverse momentum final state in proton-proton collisions at √ s= 8 TeV, JHEP 06 (2014) 055, arXiv: 1402.4770 [hep-ex]. [25] CMS Collaboration, Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at √ s = 13 TeV, Phys. Rev. D 95 (2017) 012011, arXiv: 1609.09386 [hep-ex]. [26] CMS Collaboration, Search for physics beyond the standard model in events with two leptons of same sign, missing transverse momentum, and jets in proton-proton collisions at √ s=13 TeV, (2017), arXiv: 1704.07323 [hep-ex]. [27] CMS Collaboration, Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV, (2017), arXiv: 1704.07781 [hep-ex]. [28] ATLAS Collaboration, Summary of the searches for squarks and gluinos using √ s = 8 TeV pp collisions with the ATLAS experiment at the LHC, JHEP 10 (2015) 054, arXiv: 1507.05525 [hep-ex]. [29] ATLAS Collaboration, Search for squarks and gluinos in final states with jets and missing transverse momentum at √ s = 13 TeV with the ATLAS detector, Eur. Phys. J. C 76 (2016) 392, arXiv: 1605.03814 [hep-ex]. [30] ATLAS Collaboration, Search for new phenomena in final states with large jet multiplicities and missing transverse momentum with ATLAS using √ s = 13 TeV proton-proton collisions, Phys. Lett. B 757 (2016) 334, arXiv: 1602.06194 [hep-ex]. [31] ATLAS Collaboration, Search for supersymmetry in final states with two same-sign or three leptons and jets using 36 fb −1 of √ s = 13 TeV pp collision data with the ATLAS detector, (2017), arXiv: 1706.03731 [hep-ex]. [32] ATLAS Collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, JINST 3 (2008) S08003. [33] ATLAS Collaboration, ATLAS Insertable B-Layer Technical Design Report, ATLAS-TDR-19 (2010), : https://cds.cern.ch/record/1291633, ATLAS Insertable B-Layer Technical Design Report Addendum, ATLAS-TDR-19-ADD-1, 2012, URL: https://cds.cern.ch/record/1451888. [67] R. Gavin, Y. Li, F. Petriello and S. Quackenbush, FEWZ 2.0: A code for hadronic Z production at next-to-next-to-leading order, Comput. Phys. Commun. 182 (2011) 2388, arXiv: 1011.3540 [hep-ph]. [68] ATLAS Collaboration, Multi-Boson Simulation for 13 TeV ATLAS Analyses, ATL-PHYS-PUB-2016-002 (2016), : https://cds.cern.ch/record/2119986. [69] ATLAS Collaboration, Modelling of the ttH and ttV (V = W, Z) processes for √ s = 13 TeV ATLAS analyses, ATL-PHYS-PUB-2016-005 (2016), : https://cds.cern.ch/record/2120826. [70] A. Lazopoulos, T. McElmurry, K. Melnikov and F. Petriello, Next-to-leading order QCD corrections to tt Z production at the LHC, Phys. Lett. B 666 (2008) 62, arXiv: 0804.2220 [hep-ph]. [71] J. M. Campbell and R. K. Ellis, ttW ± production and decay at NLO, JHEP 07 (2012) 052, arXiv: 1204.5678 [hep-ph]. [72] ATLAS Collaboration, The ATLAS Simulation Infrastructure, Eur. Phys. J. C 70 (2010) 823, arXiv: 1005.4568 [physics.ins-det].

and G. Soyez, FastJet User Manual, Eur. Phys. J. C 72 (2012) 1896, arXiv: 1111.6097 [hep-ph]. [80] ATLAS Collaboration, Properties of Jets and Inputs to Jet Reconstruction and Calibration with the ATLAS Detector Using Proton-Proton Collisions at √ s = 13 TeV, ATL-PHYS-PUB-2015-036 (2015), : https://cds.cern.ch/record/2044564. [81] M. Cacciari and G. P. Salam, Pileup subtraction using jet areas, Phys. Lett. B 659 (2008) 119, arXiv: 0707.1378 [hep-ph]. [82] ATLAS Collaboration, Performance of pile-up mitigation techniques for jets in pp collisions at √ s = 8 TeV using the ATLAS detector, Eur. Phys. J. C 76 (2016) 581, arXiv: 1510.03823 [hep-ex].

Rev. D 85 (2012) 034007, arXiv: 1112.2567 [hep-ph]. [95] S. Jadach, J. H. Kuhn and Z. Was, TAUOLA: A Library of Monte Carlo programs to simulate decays of polarized tau leptons, Comput. Phys. Commun. 64 (1991) 275. [96] M. Bahr et al., Herwig++ Physics and Manual, Eur. Phys. J. C 58 (2008) 639, arXiv: 0803.0883 [hep-ph]. [97] ATLAS collaboration, Measurement of W ± and Z-boson production cross sections in pp collisions at √ s = 13 TeV with the ATLAS detector, Phys. Lett. B 759 (2016) 601, arXiv: 1603.09222 [hep-ex]. [98] G. Cowan, K. Cranmer, E. Gross and O. Vitells, Asymptotic formulae for likelihood-based tests of new physics, Eur. Phys. J. C 71 (2011) 1554, arXiv: 1007.1727 [physics.data-an].The ATLAS Collaboration
M. Curatolo 50 J. Poveda 32 S. Shirabe 73
AcknowledgmentsWe thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently.
Extension of the Algebra of Poincare Group Generators and Violation of p Invariance. Yu A Golfand, E P Likhtman, Pisma Zh. Eksp. Teor. Fiz. 13JETP Lett.Yu. A. Golfand and E. P. Likhtman, Extension of the Algebra of Poincare Group Generators and Violation of p Invariance, JETP Lett. 13 (1971) 323, [Pisma Zh. Eksp. Teor. Fiz. 13 (1971) 452].

Is the Neutrino a Goldstone Particle?. D V Volkov, V P Akulov, 10.1016/0370-2693(73)90490-5Phys. Lett. B. 46109D. V. Volkov and V. P. Akulov, Is the Neutrino a Goldstone Particle?, Phys. Lett. B 46 (1973) 109.

Supergauge Transformations in Four-Dimensions. J Wess, B Zumino, 10.1016/0550-3213(74)90355-1Nucl. Phys. B. 7039J. Wess and B. Zumino, Supergauge Transformations in Four-Dimensions, Nucl. Phys. B 70 (1974) 39.

Supergauge Invariant Extension of Quantum Electrodynamics. J Wess, B Zumino, 10.1016/0550-3213(74)90112-6Nucl. Phys. B. 781J. Wess and B. Zumino, Supergauge Invariant Extension of Quantum Electrodynamics, Nucl. Phys. B 78 (1974) 1.

Supergauge Invariant Yang-Mills Theories. S Ferrara, B Zumino, 10.1016/0550-3213(74)90559-8Nucl. Phys. B. 79413S. Ferrara and B. Zumino, Supergauge Invariant Yang-Mills Theories, Nucl. Phys. B 79 (1974) 413.

Supersymmetry and Nonabelian Gauges. A Salam, J A Strathdee, 10.1016/0370-2693(74)90226-3Phys. Lett. B. 51353A. Salam and J. A. Strathdee, Supersymmetry and Nonabelian Gauges, Phys. Lett. B 51 (1974) 353.

Supersymmetry and Weak, Electromagnetic and Strong Interactions. P Fayet, 10.1016/0370-2693(76)90319-1Phys. Lett. B. 64159P. Fayet, Supersymmetry and Weak, Electromagnetic and Strong Interactions, Phys. Lett. B 64 (1976) 159.

Spontaneously Broken Supersymmetric Theories of Weak, Electromagnetic and Strong Interactions. P Fayet, 10.1016/0370-2693(77)90852-8Phys. Lett. B. 69489P. Fayet, Spontaneously Broken Supersymmetric Theories of Weak, Electromagnetic and Strong Interactions, Phys. Lett. B 69 (1977) 489.

Naturalness in Supersymmetric GUTS. N Sakai, 10.1007/BF01573998Z. Phys. C. 11153N. Sakai, Naturalness in Supersymmetric GUTS, Z. Phys. C 11 (1981) 153.

Supersymmetry and the Scale of Unification. S Dimopoulos, S Raby, F Wilczek, 10.1103/PhysRevD.24.1681Phys. Rev. D. 241681S. Dimopoulos, S. Raby and F. Wilczek, Supersymmetry and the Scale of Unification, Phys. Rev. D 24 (1981) 1681.

Low-Energy Predictions in Supersymmetric Grand Unified Theories. L E Ibañez, G G Ross, 10.1016/0370-2693(81)91200-4Phys. Lett. B. 105439L. E. Ibañez and G. G. Ross, Low-Energy Predictions in Supersymmetric Grand Unified Theories, Phys. Lett. B 105 (1981) 439.

Softly Broken Supersymmetry and SU(5). S Dimopoulos, H Georgi, 10.1016/0550-3213(81)90522-8Nucl. Phys. B. 193150S. Dimopoulos and H. Georgi, Softly Broken Supersymmetry and SU(5), Nucl. Phys. B 193 (1981) 150.

Phenomenology of the Production, Decay, and Detection of New Hadronic States Associated with Supersymmetry. G R Farrar, P Fayet, 10.1016/0370-2693(78)90858-4Phys. Lett. B. 76575G. R. Farrar and P. Fayet, Phenomenology of the Production, Decay, and Detection of New Hadronic States Associated with Supersymmetry, Phys. Lett. B 76 (1978) 575.

Constraint on the Photino Mass from Cosmology. H Goldberg, 10.1103/PhysRevLett.50.1419Phys. Rev. Lett. 5099905Phys. Rev. Lett.H. Goldberg, Constraint on the Photino Mass from Cosmology, Phys. Rev. Lett. 50 (1983) 1419, [Erratum: Phys. Rev. Lett. 103 (2009) 099905].

Supersymmetric Relics from the Big Bang. J R Ellis, J S Hagelin, D V Nanopoulos, K A Olive, M Srednicki, 10.1016/0550-3213(84)90461-9Nucl. Phys. B. 238453J. R. Ellis, J. S. Hagelin, D. V. Nanopoulos, K. A. Olive and M. Srednicki, Supersymmetric Relics from the Big Bang, Nucl. Phys. B 238 (1984) 453.

The Minimal supersymmetric standard model: Group summary report. A Djouadi, arXiv:hep-ph/9901246A. Djouadi et al., The Minimal supersymmetric standard model: Group summary report, (1998), arXiv: hep-ph/9901246.

Supersymmetry Without Prejudice. C F Berger, J S Gainer, J L Hewett, T G Rizzo, 10.1088/1126-6708/2009/02/023arXiv:0812.0980JHEP. 0223hep-phC. F. Berger, J. S. Gainer, J. L. Hewett and T. G. Rizzo, Supersymmetry Without Prejudice, JHEP 02 (2009) 023, arXiv: 0812.0980 [hep-ph].

Searching for Directly Decaying Gluinos at the Tevatron. J Alwall, M.-P Le, M Lisanti, J G Wacker, 10.1016/j.physletb.2008.06.065arXiv:0803.0019Phys. Lett. B. 66634hep-phJ. Alwall, M.-P. Le, M. Lisanti and J. G. Wacker, Searching for Directly Decaying Gluinos at the Tevatron, Phys. Lett. B 666 (2008) 34, arXiv: 0803.0019 [hep-ph].

Performance of the ATLAS Trigger System in 2015. 10.1140/epjc/s10052-017-4852-3arXiv:1611.09661Eur. Phys. J. C. 77317hep-exATLAS Collaboration, Performance of the ATLAS Trigger System in 2015, Eur. Phys. J. C 77 (2017) 317, arXiv: 1611.09661 [hep-ex].

Summary of the ATLAS experiment's sensitivity to supersymmetry after LHC Run 1 -interpreted in the phenomenological MSSM. 10.1007/JHEP10(2015)134arXiv:1508.06608JHEP. 10134hep-exATLAS Collaboration, Summary of the ATLAS experiment's sensitivity to supersymmetry after LHC Run 1 -interpreted in the phenomenological MSSM, JHEP 10 (2015) 134, arXiv: 1508.06608 [hep-ex].

SOFTSUSY: a program for calculating supersymmetric spectra. B C Allanach, 10.1016/S0010-4655(01)00460-XarXiv:hep-ph/0104145Comput. Phys. Commun. 143305B. C. Allanach, SOFTSUSY: a program for calculating supersymmetric spectra, Comput. Phys. Commun. 143 (2002) 305, arXiv: hep-ph/0104145.

Decays of supersymmetric particles: The Program SUSY-HIT (SUspect-SdecaY-Hdecay-InTerface). A Djouadi, M Mühlleitner, M Spira, arXiv:hep-ph/0609292Acta Phys. Polon. B. 38635A. Djouadi, M. Mühlleitner and M. Spira, Decays of supersymmetric particles: The Program SUSY-HIT (SUspect-SdecaY-Hdecay-InTerface), Acta Phys. Polon. B 38 (2007) 635, arXiv: hep-ph/0609292.

The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations. J , 10.1007/JHEP07(2014)079arXiv:1405.0301JHEP. 0779hep-phJ. Alwall et al., The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations, JHEP 07 (2014) 079, arXiv: 1405.0301 [hep-ph].

A Brief Introduction to PYTHIA 8.1. T Sjöstrand, S Mrenna, P Z Skands, 10.1016/j.cpc.2008.01.036arXiv:0710.3820Comput. Phys. Commun. 178852hep-phT. Sjöstrand, S. Mrenna and P. Z. Skands, A Brief Introduction to PYTHIA 8.1, Comput. Phys. Commun. 178 (2008) 852, arXiv: 0710.3820 [hep-ph].

Matching Tree-Level Matrix Elements with Interleaved Showers. L Lönnblad, S Prestel, 10.1007/JHEP03(2012)019arXiv:1109.4829JHEP. 0319hep-phL. Lönnblad and S. Prestel, Matching Tree-Level Matrix Elements with Interleaved Showers, JHEP 03 (2012) 019, arXiv: 1109.4829 [hep-ph].

ATL-PHYS-PUB-2014-021ATLAS Pythia 8 tunes to 7 TeV data. ATLAS Collaboration, ATLAS Pythia 8 tunes to 7 TeV data, ATL-PHYS-PUB-2014-021 (2014), : https://cdsweb.cern.ch/record/1966419.

Parton distributions with LHC data. R D Ball, 10.1016/j.nuclphysb.2012.10.003arXiv:1207.1303Nucl. Phys. B. 867244hep-phR. D. Ball et al., Parton distributions with LHC data, Nucl. Phys. B 867 (2013) 244, arXiv: 1207.1303 [hep-ph].

The EvtGen particle decay simulation package. D J Lange, 10.1016/S0168-9002(01)00089-4Nucl. Instrum. Meth. A. 462152D. J. Lange, The EvtGen particle decay simulation package, Nucl. Instrum. Meth. A 462 (2001) 152.

Squark and gluino production at hadron colliders. W Beenakker, R Hopker, M Spira, P Zerwas, 10.1016/S0550-3213(97)00084-9arXiv:hep-ph/9610490Nucl. Phys. B. 49251W. Beenakker, R. Hopker, M. Spira and P. Zerwas, Squark and gluino production at hadron colliders, Nucl. Phys. B 492 (1997) 51, arXiv: hep-ph/9610490.

Threshold resummation for squark-antisquark and gluino-pair production at the LHC. A Kulesza, L Motyka, 10.1103/PhysRevLett.102.111802arXiv:0807.2405Phys. Rev. Lett. 102111802hep-phA. Kulesza and L. Motyka, Threshold resummation for squark-antisquark and gluino-pair production at the LHC, Phys. Rev. Lett. 102 (2009) 111802, arXiv: 0807.2405 [hep-ph].

Soft gluon resummation for the production of gluino-gluino and squark-antisquark pairs at the LHC. A Kulesza, L Motyka, 10.1103/PhysRevD.80.095004arXiv:0905.4749Phys. Rev. D. 8095004hep-phA. Kulesza and L. Motyka, Soft gluon resummation for the production of gluino-gluino and squark-antisquark pairs at the LHC, Phys. Rev. D 80 (2009) 095004, arXiv: 0905.4749 [hep-ph].

Soft-gluon resummation for squark and gluino hadroproduction. W Beenakker, 10.1088/1126-6708/2009/12/041arXiv:0909.4418JHEP. 1241hep-phW. Beenakker et al., Soft-gluon resummation for squark and gluino hadroproduction, JHEP 12 (2009) 041, arXiv: 0909.4418 [hep-ph].

Squark and gluino hadroproduction. W Beenakker, 10.1142/S0217751X11053560arXiv:1105.1110Int. J. Mod. Phys. A. 262637hep-phW. Beenakker et al., Squark and gluino hadroproduction, Int. J. Mod. Phys. A 26 (2011) 2637, arXiv: 1105.1110 [hep-ph].

Squark and gluino production cross sections in pp collisions at √ s = 13, 14, 33 and 100 TeV. C Borschensky, 10.1140/epjc/s10052-014-3174-yarXiv:1407.5066Eur. Phys. J. C. 743174hep-phC. Borschensky et al., Squark and gluino production cross sections in pp collisions at √ s = 13, 14, 33 and 100 TeV, Eur. Phys. J. C 74 (2014) 3174, arXiv: 1407.5066 [hep-ph].

Simulation of top quark production for the ATLAS experiment at √ s = 13 TeV. ATL-PHYS-PUB-2016-004ATLAS Collaboration, Simulation of top quark production for the ATLAS experiment at √ s = 13 TeV, ATL-PHYS-PUB-2016-004 (2016), : https://cds.cern.ch/record/2120417.

A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX. S Alioli, P Nason, C Oleari, E Re, 10.1007/JHEP06(2010)043arXiv:1002.2581JHEP. 0643hep-phS. Alioli, P. Nason, C. Oleari and E. Re, A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX, JHEP 06 (2010) 043, arXiv: 1002.2581 [hep-ph].

New parton distributions for collider physics. H.-L Lai, 10.1103/PhysRevD.82.074024arXiv:1007.2241Phys. Rev. D. 8274024hep-phH.-L. Lai et al., New parton distributions for collider physics, Phys. Rev. D 82 (2010) 074024, arXiv: 1007.2241 [hep-ph].

Automatic spin-entangled decays of heavy resonances in Monte Carlo simulations. P Artoisenet, R Frederix, O Mattelaer, R Rietkerk, 10.1007/JHEP03(2013)015arXiv:1212.3460JHEP. 0315hep-phP. Artoisenet, R. Frederix, O. Mattelaer and R. Rietkerk, Automatic spin-entangled decays of heavy resonances in Monte Carlo simulations, JHEP 03 (2013) 015, arXiv: 1212.3460 [hep-ph].

PYTHIA 6.4 Physics and Manual. T Sjöstrand, S Mrenna, P Z Skands, 10.1088/1126-6708/2006/05/026arXiv:hep-ph/0603175JHEP. 0526T. Sjöstrand, S. Mrenna and P. Z. Skands, PYTHIA 6.4 Physics and Manual, JHEP 05 (2006) 026, arXiv: hep-ph/0603175.

New generation of parton distributions with uncertainties from global QCD analysis. J Pumplin, 10.1088/1126-6708/2002/07/012arXiv:hep-ph/0201195JHEP. 0712J. Pumplin et al., New generation of parton distributions with uncertainties from global QCD analysis, JHEP 07 (2002) 012, arXiv: hep-ph/0201195.

Tuning Monte Carlo Generators: The Perugia Tunes. P Z Skands, 10.1103/PhysRevD.82.074018arXiv:1005.3457Phys. Rev. D. 8274018hep-phP. Z. Skands, Tuning Monte Carlo Generators: The Perugia Tunes, Phys. Rev. D 82 (2010) 074018, arXiv: 1005.3457 [hep-ph].

Top++: A Program for the Calculation of the Top-Pair Cross-Section at Hadron Colliders. M Czakon, A Mitov, 10.1016/j.cpc.2014.06.021arXiv:1112.5675Comput. Phys. Commun. 1852930hep-phM. Czakon and A. Mitov, Top++: A Program for the Calculation of the Top-Pair Cross-Section at Hadron Colliders, Comput. Phys. Commun. 185 (2014) 2930, arXiv: 1112.5675 [hep-ph].

Two-loop soft anomalous dimensions for single top quark associated production with a W-or H. N Kidonakis, 10.1103/PhysRevD.82.054018arXiv:1005.4451Phys. Rev. D. 8254018hep-phN. Kidonakis, Two-loop soft anomalous dimensions for single top quark associated production with a W-or H-, Phys. Rev. D 82 (2010) 054018, arXiv: 1005.4451 [hep-ph].

HATHOR for single top-quark production: Updated predictions and uncertainty estimates for single top-quark production in hadronic collisions. P Kant, 10.1016/j.cpc.2015.02.001arXiv:1406.4403Comput. Phys. Commun. 19174hep-phP. Kant et al., HATHOR for single top-quark production: Updated predictions and uncertainty estimates for single top-quark production in hadronic collisions, Comput. Phys. Commun. 191 (2015) 74, arXiv: 1406.4403 [hep-ph].

Monte Carlo Generators for the Production of a W or Z/γ * Boson in Association with Jets at ATLAS in Run 2. ATL-PHYS-PUB-2016-003ATLAS Collaboration, Monte Carlo Generators for the Production of a W or Z/γ * Boson in Association with Jets at ATLAS in Run 2, ATL-PHYS-PUB-2016-003 (2016), : https://cds.cern.ch/record/2120133.

Event generation with SHERPA 1.1. T Gleisberg, S Höche, F Krauss, M Schönherr, S Schumann, 10.1088/1126-6708/2009/02/007arXiv:0811.4622JHEP. 027hep-phT. Gleisberg, S. Höche, F. Krauss, M. Schönherr, S. Schumann et al., Event generation with SHERPA 1.1, JHEP 02 (2009) 007, arXiv: 0811.4622 [hep-ph].

Comix, a new matrix element generator. T Gleisberg, S Höche, 10.1088/1126-6708/2008/12/039arXiv:0808.3674JHEP. 1239hep-phT. Gleisberg and S. Höche, Comix, a new matrix element generator, JHEP 12 (2008) 039, arXiv: 0808.3674 [hep-ph].

Scattering Amplitudes with Open Loops. F Cascioli, P Maierhofer, S Pozzorini, 10.1103/PhysRevLett.108.111601arXiv:1111.5206Phys. Rev. Lett. 108111601hep-phF. Cascioli, P. Maierhofer and S. Pozzorini, Scattering Amplitudes with Open Loops, Phys. Rev. Lett. 108 (2012) 111601, arXiv: 1111.5206 [hep-ph].

A Parton shower algorithm based on Catani-Seymour dipole factorisation. S Schumann, F Krauss, 10.1088/1126-6708/2008/03/038arXiv:0709.1027JHEP. 0338hep-phS. Schumann and F. Krauss, A Parton shower algorithm based on Catani-Seymour dipole factorisation, JHEP 03 (2008) 038, arXiv: 0709.1027 [hep-ph].

QCD matrix elements + parton showers: The NLO case. S Höche, F Krauss, M Schönherr, F Siegert, 10.1007/JHEP04(2013)027arXiv:1207.5030JHEP. 0427hep-phS. Höche, F. Krauss, M. Schönherr and F. Siegert, QCD matrix elements + parton showers: The NLO case, JHEP 04 (2013) 027, arXiv: 1207.5030 [hep-ph].

Parton distributions for the LHC Run II. R D Ball, 10.1007/JHEP04(2015)040arXiv:1410.8849JHEP. 0440hep-phR. D. Ball et al., Parton distributions for the LHC Run II, JHEP 04 (2015) 040, arXiv: 1410.8849 [hep-ph].

HistFitter software framework for statistical data analysis. M Baak, 10.1140/epjc/s10052-015-3327-7arXiv:1410.1280Eur. Phys. J. C. 75153hep-exM. Baak et al., HistFitter software framework for statistical data analysis, Eur. Phys. J. C 75 (2015) 153, arXiv: 1410.1280 [hep-ex].

Presentation of search results: The CL(s) technique. A L Read, 10.1088/0954-3899/28/10/313J. Phys. G. 282693A. L. Read, Presentation of search results: The CL(s) technique, J. Phys. G 28 (2002) 2693.

ATL-GEN-PUB-2016-002ATLAS Computing Acknowledgements. ATLAS Collaboration, ATLAS Computing Acknowledgements 2016-2017, ATL-GEN-PUB-2016-002, : https://cds.cern.ch/record/2202407.

10 Physics Department. Athens, Greece; Baku, AzerbaijanDepartment of Physics, The University of Texas at Arlington, Arlington TX, United States of America 9 Physics Department, National and Kapodistrian University of Athens ; National Technical University of Athens, Zografou, Greece 11 Department of Physics, The University of Texas at Austin, Austin TX, United States of America 12 Institute of Physics, Azerbaijan Academy of SciencesDepartment of Physics, The University of Texas at Arlington, Arlington TX, United States of America 9 Physics Department, National and Kapodistrian University of Athens, Athens, Greece 10 Physics Department, National Technical University of Athens, Zografou, Greece 11 Department of Physics, The University of Texas at Austin, Austin TX, United States of America 12 Institute of Physics, Azerbaijan Academy of Sciences, Baku, Azerbaijan

16 Physics Division. Belgrade; Bergen, Norway; Berlin, GermanyInstitut de Física d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Barcelona, Spain 14 Institute of Physics, University of Belgrade ; Serbia 15 Department for Physics and Technology, University of Bergen ; Lawrence Berkeley National Laboratory and University of California, Berkeley CA, United States of America 17 Department of Physics, Humboldt UniversityInstitut de Física d'Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Barcelona, Spain 14 Institute of Physics, University of Belgrade, Belgrade, Serbia 15 Department for Physics and Technology, University of Bergen, Bergen, Norway 16 Physics Division, Lawrence Berkeley National Laboratory and University of California, Berkeley CA, United States of America 17 Department of Physics, Humboldt University, Berlin, Germany

. United States of America. 28Universidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (b) Electrical Circuits Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora; (c) Federal University of Sao Joao del Rei (UFSJ ; Universidade de Sao Paulo ; Brazil 27 Physics Department, Brookhaven National Laboratoryd) Instituto de FisicaUniversidade Federal do Rio De Janeiro COPPE/EE/IF, Rio de Janeiro; (b) Electrical Circuits Department, Federal University of Juiz de Fora (UFJF), Juiz de Fora; (c) Federal University of Sao Joao del Rei (UFSJ), Sao Joao del Rei; (d) Instituto de Fisica, Universidade de Sao Paulo, Sao Paulo, Brazil 27 Physics Department, Brookhaven National Laboratory, Upton NY, United States of America 28 (a) DESY, Hamburg and Zeuthen, Germany

Sezione di Genova; (b) Dipartimento di Fisica. 53Geneva, Switzerland; Genova, ItalyDepartement de Physique Nucleaire et Corpusculaire, Université de Genève ; Università di GenovaDepartement de Physique Nucleaire et Corpusculaire, Université de Genève, Geneva, Switzerland 53 (a) INFN Sezione di Genova; (b) Dipartimento di Fisica, Università di Genova, Genova, Italy

E Andronikashvili, Georgia 55 II Physikalisches Institut. Tbilisi; Giessen, Germany; Göttingen, Germany5658Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University ; Justus-Liebig-Universität Giessen ; University of Glasgow, Glasgow, United Kingdom 57 II Physikalisches Institut, Georg-August-UniversitätE. Andronikashvili Institute of Physics, Iv. Javakhishvili Tbilisi State University, Tbilisi; (b) High Energy Physics Institute, Tbilisi State University, Tbilisi, Georgia 55 II Physikalisches Institut, Justus-Liebig-Universität Giessen, Giessen, Germany 56 SUPA -School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom 57 II Physikalisches Institut, Georg-August-Universität, Göttingen, Germany 58

. United States of America. 60Laboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes ; CNRS/IN2P3 ; France 59 Laboratory for Particle Physics and Cosmology, Harvard UniversityLaboratoire de Physique Subatomique et de Cosmologie, Université Grenoble-Alpes, CNRS/IN2P3, Grenoble, France 59 Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge MA, United States of America 60 (a)

61 Faculty of Applied Information Science. Kirchhoff-Institut Für Physik, 62Heidelberg, Germany; Hiroshima, JapanRuprecht-Karls-Universität Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg ; Hiroshima Institute of TechnologyKirchhoff-Institut für Physik, Ruprecht-Karls-Universität Heidelberg, Heidelberg; (b) Physikalisches Institut, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany 61 Faculty of Applied Information Science, Hiroshima Institute of Technology, Hiroshima, Japan 62 (a)

84 Fysiska institutionen. Laboratoire de Physique Nucléaire et de Hautes Energies, UPMC and Université Paris-Diderot and CNRS/IN2P3. Paris, France; Lund, Sweden85Laboratoire de Physique Nucléaire et de Hautes Energies, UPMC and Université Paris-Diderot and CNRS/IN2P3, Paris, France 84 Fysiska institutionen, Lunds universitet, Lund, Sweden 85

Sezione di Milano; (b) Dipartimento di Fisica. United States of America. 94Department of Physics and Astronomy, Michigan State University, East Lansing MI ; Università di MilanoDepartment of Physics and Astronomy, Michigan State University, East Lansing MI, United States of America 94 (a) INFN Sezione di Milano; (b) Dipartimento di Fisica, Università di Milano, Milano, Italy

Stepanov Institute of Physics. B I , Minsk, Republic of BelarusNational Academy of Sciences of BelarusB.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Republic of Belarus 96

Lebedev Physical Institute of the Russian Academy of Sciences. P , 99 Institute for Theoretical and Experimental Physics (ITEP). Moscow, Russia; Moscow, Russia; Moscow, Russia100 National Research Nuclear University MEPhIP.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia 99 Institute for Theoretical and Experimental Physics (ITEP), Moscow, Russia 100 National Research Nuclear University MEPhI, Moscow, Russia

. D V Skobeltsyn, 102Moscow, Russia; München, GermanyInstitute of Nuclear Physics, M.V. Lomonosov Moscow State University ; Fakultät für Physik, Ludwig-Maximilians-Universität MünchenD.V. Skobeltsyn Institute of Nuclear Physics, M.V. Lomonosov Moscow State University, Moscow, Russia 102 Fakultät für Physik, Ludwig-Maximilians-Universität München, München, Germany

. Applied Science. Max-Planck-Institut für PhysikWerner-Heisenberg-InstitutMax-Planck-Institut für Physik (Werner-Heisenberg-Institut), München, Germany 104 Nagasaki Institute of Applied Science, Nagasaki, Japan

Sezione di Napoli; (b) Dipartimento di Fisica. 106Nagoya, Japan; St. Petersburg, RussiaGraduate School of Science and Kobayashi-Maskawa Institute, Nagoya University ; Università di Napoli, Napoli, Italy 107 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United States of America National Research Centre "Kurchatov Institute" B.P.Konstantinov Petersburg Nuclear Physics InstituteGraduate School of Science and Kobayashi-Maskawa Institute, Nagoya University, Nagoya, Japan 106 (a) INFN Sezione di Napoli; (b) Dipartimento di Fisica, Università di Napoli, Napoli, Italy 107 Department of Physics and Astronomy, University of New Mexico, Albuquerque NM, United States of America National Research Centre "Kurchatov Institute" B.P.Konstantinov Petersburg Nuclear Physics Institute, St. Petersburg, Russia

E Infn Sezione Di Pisa ; B) Dipartimento Di Fisica, Fermi, 127 Department of Physics and Astronomy. Pisa, Italy; Pittsburgh PA128Università di Pisa ; University of PittsburghaINFN Sezione di Pisa; (b) Dipartimento di Fisica E. Fermi, Università di Pisa, Pisa, Italy 127 Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh PA, United States of America 128 (a)

. Ciências, CoimbraUniversidade de Lisboa, Lisboa; (c) Department of Physics, University of CoimbraCiências, Universidade de Lisboa, Lisboa; (c) Department of Physics, University of Coimbra, Coimbra;

Universidade do Minho, Braga; ( f ) Departamento de Fisica Teorica y del Cosmos, Universidad de Granada, Granada; (g) Dep Fisica and CEFITEC of Faculdade de Ciencias e Tecnologia. 131Praha, Czech Republic; Praha, Czech RepublicCentro de Física Nuclear da Universidade de Lisboa, Lisboa; (e) Departamento de Fisica ; Universidade Nova de Lisboa, Caparica, Portugal 129 Institute of Physics, Academy of Sciences of the Czech Republic ; Czech Technical University in PragueCentro de Física Nuclear da Universidade de Lisboa, Lisboa; (e) Departamento de Fisica, Universidade do Minho, Braga; ( f ) Departamento de Fisica Teorica y del Cosmos, Universidad de Granada, Granada; (g) Dep Fisica and CEFITEC of Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal 129 Institute of Physics, Academy of Sciences of the Czech Republic, Praha, Czech Republic 130 Czech Technical University in Prague, Praha, Czech Republic 131

. Faculty of Mathematics and Physics. 132Charles UniversityCharles University, Faculty of Mathematics and Physics, Prague, Czech Republic 132

Sezione di Roma; (b) Dipartimento di Fisica. NRC KI, Russia 133 Particle Physics Department. Didcot, United Kingdom; Roma, Italy134State Research Center Institute for High Energy Physics (Protvino ; Rutherford Appleton Laboratory ; Sapienza Università di RomaState Research Center Institute for High Energy Physics (Protvino), NRC KI, Russia 133 Particle Physics Department, Rutherford Appleton Laboratory, Didcot, United Kingdom 134 (a) INFN Sezione di Roma; (b) Dipartimento di Fisica, Sapienza Università di Roma, Roma, Italy

Sezione di Roma Tre; (b) Dipartimento di Matematica e Fisica. INFN Sezione di Roma Tor Vergata(b) Dipartimento di Fisica, Università di Roma Tor Vergata136Roma, Italy; Roma, ItalyUniversità Roma TreINFN Sezione di Roma Tor Vergata; (b) Dipartimento di Fisica, Università di Roma Tor Vergata, Roma, Italy 136 (a) INFN Sezione di Roma Tre; (b) Dipartimento di Matematica e Fisica, Università Roma Tre, Roma, Italy 137 (a)

Casablanca; (b) Centre National de l'Energie des Sciences Techniques Nucleaires, Rabat; (c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech; (d) Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda; (e) Faculté des sciences. Rabat, MoroccoFaculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies -Université Hassan II, ; Université Mohammed VFaculté des Sciences Ain Chock, Réseau Universitaire de Physique des Hautes Energies - Université Hassan II, Casablanca; (b) Centre National de l'Energie des Sciences Techniques Nucleaires, Rabat; (c) Faculté des Sciences Semlalia, Université Cadi Ayyad, LPHEA-Marrakech; (d) Faculté des Sciences, Université Mohamed Premier and LPTPM, Oujda; (e) Faculté des sciences, Université Mohammed V, Rabat, Morocco

Dsm/Irfu, CEA Saclay (Commissariat à l'Energie Atomique et aux Energies Alternatives). Gif-sur-Yvette, France139Institut de Recherches sur les Lois Fondamentales de l'UniversDSM/IRFU (Institut de Recherches sur les Lois Fondamentales de l'Univers), CEA Saclay (Commissariat à l'Energie Atomique et aux Energies Alternatives), Gif-sur-Yvette, France 139