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Measurement of lepton differential distributions and the top quark mass in \(t\bar{t}\) production in pp collisions at \(\sqrt{s}=8\) TeV with the ATLAS detector

  • M. Aaboud
  • G. Aad
  • B. Abbott
  • O. Abdinov
  • B. Abeloos
  • S. H. Abidi
  • O. S. AbouZeid
  • N. L. Abraham
  • H. Abramowicz
  • H. Abreu
  • R. Abreu
  • Y. Abulaiti
  • B. S. Acharya
  • S. Adachi
  • L. Adamczyk
  • J. Adelman
  • M. Adersberger
  • T. Adye
  • A. A. Affolder
  • Y. Afik
  • T. Agatonovic-Jovin
  • C. Agheorghiesei
  • J. A. Aguilar-Saavedra
  • S. P. Ahlen
  • F. Ahmadov
  • G. Aielli
  • S. Akatsuka
  • H. Akerstedt
  • T. P. A. Åkesson
  • E. Akilli
  • A. V. Akimov
  • G. L. Alberghi
  • J. Albert
  • P. Albicocco
  • M. J. Alconada Verzini
  • S. C. Alderweireldt
  • M. Aleksa
  • I. N. Aleksandrov
  • C. Alexa
  • G. Alexander
  • T. Alexopoulos
  • M. Alhroob
  • B. Ali
  • M. Aliev
  • G. Alimonti
  • J. Alison
  • S. P. Alkire
  • B. M. M. Allbrooke
  • B. W. Allen
  • P. P. Allport
  • A. Aloisio
  • A. Alonso
  • F. Alonso
  • C. Alpigiani
  • A. A. Alshehri
  • M. I. Alstaty
  • B. Alvarez Gonzalez
  • D. Álvarez Piqueras
  • M. G. Alviggi
  • B. T. Amadio
  • Y. Amaral Coutinho
  • C. Amelung
  • D. Amidei
  • S. P. Amor Dos Santos
  • S. Amoroso
  • G. Amundsen
  • C. Anastopoulos
  • L. S. Ancu
  • N. Andari
  • T. Andeen
  • C. F. Anders
  • J. K. Anders
  • K. J. Anderson
  • A. Andreazza
  • V. Andrei
  • S. Angelidakis
  • I. Angelozzi
  • A. Angerami
  • A. V. Anisenkov
  • N. Anjos
  • A. Annovi
  • C. Antel
  • M. Antonelli
  • A. Antonov
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  • F. Anulli
  • M. Aoki
  • L. Aperio Bella
  • G. Arabidze
  • Y. Arai
  • J. P. Araque
  • V. Araujo Ferraz
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  • R. E. Ardell
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  • J-F. Arguin
  • S. Argyropoulos
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  • A. J. Armbruster
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  • H. Arnold
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  • A. Ashkenazi
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  • M. Atkinson
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  • J. E. Black
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  • C. Blocker
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  • U. Blumenschein
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  • D. Calvet
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  • B. Dutta
  • D. Duvnjak
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  • M. El Kacimi
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  • A. Ereditato
  • M. Ernst
  • S. Errede
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  • B. Esposito
  • O. Estrada Pastor
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  • R. J. Falla
  • J. Faltova
  • Y. Fang
  • M. Fanti
  • A. Farbin
  • A. Farilla
  • C. Farina
  • E. M. Farina
  • T. Farooque
  • S. Farrell
  • S. M. Farrington
  • P. Farthouat
  • F. Fassi
  • P. Fassnacht
  • D. Fassouliotis
  • M. Faucci Giannelli
  • A. Favareto
  • W. J. Fawcett
  • L. Fayard
  • O. L. Fedin
  • W. Fedorko
  • S. Feigl
  • L. Feligioni
  • C. Feng
  • E. J. Feng
  • M. J. Fenton
  • A. B. Fenyuk
  • L. Feremenga
  • P. Fernandez Martinez
  • J. Ferrando
  • A. Ferrari
  • P. Ferrari
  • R. Ferrari
  • D. E. Ferreira de Lima
  • A. Ferrer
  • D. Ferrere
  • C. Ferretti
  • F. Fiedler
  • A. Filipčič
  • M. Filipuzzi
  • F. Filthaut
  • M. Fincke-Keeler
  • K. D. Finelli
  • M. C. N. Fiolhais
  • L. Fiorini
  • A. Fischer
  • C. Fischer
  • J. Fischer
  • W. C. Fisher
  • N. Flaschel
  • I. Fleck
  • P. Fleischmann
  • R. R. M. Fletcher
  • T. Flick
  • B. M. Flierl
  • L. R. Flores Castillo
  • M. J. Flowerdew
  • G. T. Forcolin
  • A. Formica
  • F. A. Förster
  • A. Forti
  • A. G. Foster
  • D. Fournier
  • H. Fox
  • S. Fracchia
  • P. Francavilla
  • M. Franchini
  • S. Franchino
  • D. Francis
  • L. Franconi
  • M. Franklin
  • M. Frate
  • M. Fraternali
  • D. Freeborn
  • S. M. Fressard-Batraneanu
  • B. Freund
  • D. Froidevaux
  • J. A. Frost
  • C. Fukunaga
  • T. Fusayasu
  • J. Fuster
  • O. Gabizon
  • A. Gabrielli
  • A. Gabrielli
  • G. P. Gach
  • S. Gadatsch
  • S. Gadomski
  • G. Gagliardi
  • L. G. Gagnon
  • C. Galea
  • B. Galhardo
  • E. J. Gallas
  • B. J. Gallop
  • P. Gallus
  • G. Galster
  • K. K. Gan
  • S. Ganguly
  • Y. Gao
  • Y. S. Gao
  • F. M. Garay Walls
  • C. García
  • J. E. García Navarro
  • J. A. García Pascual
  • M. Garcia-Sciveres
  • R. W. Gardner
  • N. Garelli
  • V. Garonne
  • A. Gascon Bravo
  • K. Gasnikova
  • C. Gatti
  • A. Gaudiello
  • G. Gaudio
  • I. L. Gavrilenko
  • C. Gay
  • G. Gaycken
  • E. N. Gazis
  • C. N. P. Gee
  • J. Geisen
  • M. Geisen
  • M. P. Geisler
  • K. Gellerstedt
  • C. Gemme
  • M. H. Genest
  • C. Geng
  • S. Gentile
  • C. Gentsos
  • S. George
  • D. Gerbaudo
  • G. Geßner
  • S. Ghasemi
  • M. Ghneimat
  • B. Giacobbe
  • S. Giagu
  • N. Giangiacomi
  • P. Giannetti
  • S. M. Gibson
  • M. Gignac
  • M. Gilchriese
  • D. Gillberg
  • G. Gilles
  • D. M. Gingrich
  • M. P. Giordani
  • F. M. Giorgi
  • P. F. Giraud
  • P. Giromini
  • G. Giugliarelli
  • D. Giugni
  • F. Giuli
  • C. Giuliani
  • M. Giulini
  • B. K. Gjelsten
  • S. Gkaitatzis
  • I. Gkialas
  • E. L. Gkougkousis
  • P. Gkountoumis
  • L. K. Gladilin
  • C. Glasman
  • J. Glatzer
  • P. C. F. Glaysher
  • A. Glazov
  • M. Goblirsch-Kolb
  • J. Godlewski
  • S. Goldfarb
  • T. Golling
  • D. Golubkov
  • A. Gomes
  • R. Gonçalo
  • R. Goncalves Gama
  • J. Goncalves Pinto Firmino Da Costa
  • G. Gonella
  • L. Gonella
  • A. Gongadze
  • J. L. Gonski
  • S. González de la Hoz
  • S. Gonzalez-Sevilla
  • L. Goossens
  • P. A. Gorbounov
  • H. A. Gordon
  • I. Gorelov
  • B. Gorini
  • E. Gorini
  • A. Gorišek
  • A. T. Goshaw
  • C. Gössling
  • M. I. Gostkin
  • C. A. Gottardo
  • C. R. Goudet
  • D. Goujdami
  • A. G. Goussiou
  • N. Govender
  • E. Gozani
  • I. Grabowska-Bold
  • P. O. J. Gradin
  • J. Gramling
  • E. Gramstad
  • S. Grancagnolo
  • V. Gratchev
  • P. M. Gravila
  • C. Gray
  • H. M. Gray
  • Z. D. Greenwood
  • C. Grefe
  • K. Gregersen
  • I. M. Gregor
  • P. Grenier
  • K. Grevtsov
  • J. Griffiths
  • A. A. Grillo
  • K. Grimm
  • S. Grinstein
  • Ph. Gris
  • J.-F. Grivaz
  • S. Groh
  • E. Gross
  • J. Grosse-Knetter
  • G. C. Grossi
  • Z. J. Grout
  • A. Grummer
  • L. Guan
  • W. Guan
  • J. Guenther
  • F. Guescini
  • D. Guest
  • O. Gueta
  • B. Gui
  • E. Guido
  • T. Guillemin
  • S. Guindon
  • U. Gul
  • C. Gumpert
  • J. Guo
  • W. Guo
  • Y. Guo
  • R. Gupta
  • S. Gurbuz
  • G. Gustavino
  • B. J. Gutelman
  • P. Gutierrez
  • N. G. Gutierrez Ortiz
  • C. Gutschow
  • C. Guyot
  • M. P. Guzik
  • C. Gwenlan
  • C. B. Gwilliam
  • A. Haas
  • C. Haber
  • H. K. Hadavand
  • N. Haddad
  • A. Hadef
  • S. Hageböck
  • M. Hagihara
  • H. Hakobyan
  • M. Haleem
  • J. Haley
  • G. Halladjian
  • G. D. Hallewell
  • K. Hamacher
  • P. Hamal
  • K. Hamano
  • A. Hamilton
  • G. N. Hamity
  • P. G. Hamnett
  • L. Han
  • S. Han
  • K. Hanagaki
  • K. Hanawa
  • M. Hance
  • D. M. Handl
  • B. Haney
  • P. Hanke
  • J. B. Hansen
  • J. D. Hansen
  • M. C. Hansen
  • P. H. Hansen
  • K. Hara
  • A. S. Hard
  • T. Harenberg
  • F. Hariri
  • S. Harkusha
  • P. F. Harrison
  • N. M. Hartmann
  • Y. Hasegawa
  • A. Hasib
  • S. Hassani
  • S. Haug
  • R. Hauser
  • L. Hauswald
  • L. B. Havener
  • M. Havranek
  • C. M. Hawkes
  • R. J. Hawkings
  • D. Hayakawa
  • D. Hayden
  • C. P. Hays
  • J. M. Hays
  • H. S. Hayward
  • S. J. Haywood
  • S. J. Head
  • T. Heck
  • V. Hedberg
  • L. Heelan
  • S. Heer
  • K. K. Heidegger
  • S. Heim
  • T. Heim
  • B. Heinemann
  • J. J. Heinrich
  • L. Heinrich
  • C. Heinz
  • J. Hejbal
  • L. Helary
  • A. Held
  • S. Hellman
  • C. Helsens
  • R. C. W. Henderson
  • Y. Heng
  • S. Henkelmann
  • A. M. Henriques Correia
  • S. Henrot-Versille
  • G. H. Herbert
  • H. Herde
  • V. Herget
  • Y. Hernández Jiménez
  • H. Herr
  • G. Herten
  • R. Hertenberger
  • L. Hervas
  • T. C. Herwig
  • G. G. Hesketh
  • N. P. Hessey
  • J. W. Hetherly
  • S. Higashino
  • E. Higón-Rodriguez
  • K. Hildebrand
  • E. Hill
  • J. C. Hill
  • K. H. Hiller
  • S. J. Hillier
  • M. Hils
  • I. Hinchliffe
  • M. Hirose
  • D. Hirschbuehl
  • B. Hiti
  • O. Hladik
  • D. R. Hlaluku
  • X. Hoad
  • J. Hobbs
  • N. Hod
  • M. C. Hodgkinson
  • P. Hodgson
  • A. Hoecker
  • M. R. Hoeferkamp
  • F. Hoenig
  • D. Hohn
  • T. R. Holmes
  • M. Homann
  • S. Honda
  • T. Honda
  • T. M. Hong
  • B. H. Hooberman
  • W. H. Hopkins
  • Y. Horii
  • A. J. Horton
  • J-Y. Hostachy
  • A. Hostiuc
  • S. Hou
  • A. Hoummada
  • J. Howarth
  • J. Hoya
  • M. Hrabovsky
  • J. Hrdinka
  • I. Hristova
  • J. Hrivnac
  • T. Hryn’ova
  • A. Hrynevich
  • P. J. Hsu
  • S.-C. Hsu
  • Q. Hu
  • S. Hu
  • Y. Huang
  • Z. Hubacek
  • F. Hubaut
  • F. Huegging
  • T. B. Huffman
  • E. W. Hughes
  • M. Huhtinen
  • R. F. H. Hunter
  • P. Huo
  • N. Huseynov
  • J. Huston
  • J. Huth
  • R. Hyneman
  • G. Iacobucci
  • G. Iakovidis
  • I. Ibragimov
  • L. Iconomidou-Fayard
  • Z. Idrissi
  • P. Iengo
  • O. Igonkina
  • T. Iizawa
  • Y. Ikegami
  • M. Ikeno
  • Y. Ilchenko
  • D. Iliadis
  • N. Ilic
  • F. Iltzsche
  • G. Introzzi
  • P. Ioannou
  • M. Iodice
  • K. Iordanidou
  • V. Ippolito
  • M. F. Isacson
  • N. Ishijima
  • M. Ishino
  • M. Ishitsuka
  • C. Issever
  • S. Istin
  • F. Ito
  • J. M. Iturbe Ponce
  • R. Iuppa
  • H. Iwasaki
  • J. M. Izen
  • V. Izzo
  • S. Jabbar
  • P. Jackson
  • R. M. Jacobs
  • V. Jain
  • K. B. Jakobi
  • K. Jakobs
  • S. Jakobsen
  • T. Jakoubek
  • D. O. Jamin
  • D. K. Jana
  • R. Jansky
  • J. Janssen
  • M. Janus
  • P. A. Janus
  • G. Jarlskog
  • N. Javadov
  • T. Javůrek
  • M. Javurkova
  • F. Jeanneau
  • L. Jeanty
  • J. Jejelava
  • A. Jelinskas
  • P. Jenni
  • C. Jeske
  • S. Jézéquel
  • H. Ji
  • J. Jia
  • H. Jiang
  • Y. Jiang
  • Z. Jiang
  • S. Jiggins
  • J. Jimenez Pena
  • S. Jin
  • A. Jinaru
  • O. Jinnouchi
  • H. Jivan
  • P. Johansson
  • K. A. Johns
  • C. A. Johnson
  • W. J. Johnson
  • K. Jon-And
  • R. W. L. Jones
  • S. D. Jones
  • S. Jones
  • T. J. Jones
  • J. Jongmanns
  • P. M. Jorge
  • J. Jovicevic
  • X. Ju
  • A. Juste Rozas
  • M. K. Köhler
  • A. Kaczmarska
  • M. Kado
  • H. Kagan
  • M. Kagan
  • S. J. Kahn
  • T. Kaji
  • E. Kajomovitz
  • C. W. Kalderon
  • A. Kaluza
  • S. Kama
  • A. Kamenshchikov
  • N. Kanaya
  • L. Kanjir
  • V. A. Kantserov
  • J. Kanzaki
  • B. Kaplan
  • L. S. Kaplan
  • D. Kar
  • K. Karakostas
  • N. Karastathis
  • M. J. Kareem
  • E. Karentzos
  • S. N. Karpov
  • Z. M. Karpova
  • K. Karthik
  • V. Kartvelishvili
  • A. N. Karyukhin
  • K. Kasahara
  • L. Kashif
  • R. D. Kass
  • A. Kastanas
  • Y. Kataoka
  • C. Kato
  • A. Katre
  • J. Katzy
  • K. Kawade
  • K. Kawagoe
  • T. Kawamoto
  • G. Kawamura
  • E. F. Kay
  • V. F. Kazanin
  • R. Keeler
  • R. Kehoe
  • J. S. Keller
  • E. Kellermann
  • J. J. Kempster
  • J Kendrick
  • H. Keoshkerian
  • O. Kepka
  • B. P. Kerševan
  • S. Kersten
  • R. A. Keyes
  • M. Khader
  • F. Khalil-zada
  • A. Khanov
  • A. G. Kharlamov
  • T. Kharlamova
  • A. Khodinov
  • T. J. Khoo
  • V. Khovanskiy
  • E. Khramov
  • J. Khubua
  • S. Kido
  • C. R. Kilby
  • H. Y. Kim
  • S. H. Kim
  • Y. K. Kim
  • N. Kimura
  • O. M. Kind
  • B. T. King
  • D. Kirchmeier
  • J. Kirk
  • A. E. Kiryunin
  • T. Kishimoto
  • D. Kisielewska
  • V. Kitali
  • O. Kivernyk
  • E. Kladiva
  • T. Klapdor-Kleingrothaus
  • M. H. Klein
  • M. Klein
  • U. Klein
  • K. Kleinknecht
  • P. Klimek
  • A. Klimentov
  • R. Klingenberg
  • T. Klingl
  • T. Klioutchnikova
  • F. F. Klitzner
  • E.-E. Kluge
  • P. Kluit
  • S. Kluth
  • E. Kneringer
  • E. B. F. G. Knoops
  • A. Knue
  • A. Kobayashi
  • D. Kobayashi
  • T. Kobayashi
  • M. Kobel
  • M. Kocian
  • P. Kodys
  • T. Koffas
  • E. Koffeman
  • N. M. Köhler
  • T. Koi
  • M. Kolb
  • I. Koletsou
  • A. A. Komar
  • T. Kondo
  • N. Kondrashova
  • K. Köneke
  • A. C. König
  • T. Kono
  • R. Konoplich
  • N. Konstantinidis
  • B. Konya
  • R. Kopeliansky
  • S. Koperny
  • A. K. Kopp
  • K. Korcyl
  • K. Kordas
  • A. Korn
  • A. A. Korol
  • I. Korolkov
  • E. V. Korolkova
  • O. Kortner
  • S. Kortner
  • T. Kosek
  • V. V. Kostyukhin
  • A. Kotwal
  • A. Koulouris
  • A. Kourkoumeli-Charalampidi
  • C. Kourkoumelis
  • E. Kourlitis
  • V. Kouskoura
  • A. B. Kowalewska
  • R. Kowalewski
  • T. Z. Kowalski
  • C. Kozakai
  • W. Kozanecki
  • A. S. Kozhin
  • V. A. Kramarenko
  • G. Kramberger
  • D. Krasnopevtsev
  • M. W. Krasny
  • A. Krasznahorkay
  • D. Krauss
  • J. A. Kremer
  • J. Kretzschmar
  • K. Kreutzfeldt
  • P. Krieger
  • K. Krizka
  • K. Kroeninger
  • H. Kroha
  • J. Kroll
  • J. Kroll
  • J. Kroseberg
  • J. Krstic
  • U. Kruchonak
  • H. Krüger
  • N. Krumnack
  • M. C. Kruse
  • T. Kubota
  • H. Kucuk
  • S. Kuday
  • J. T. Kuechler
  • S. Kuehn
  • A. Kugel
  • F. Kuger
  • T. Kuhl
  • V. Kukhtin
  • R. Kukla
  • Y. Kulchitsky
  • S. Kuleshov
  • Y. P. Kulinich
  • M. Kuna
  • T. Kunigo
  • A. Kupco
  • T. Kupfer
  • O. Kuprash
  • H. Kurashige
  • L. L. Kurchaninov
  • Y. A. Kurochkin
  • M. G. Kurth
  • E. S. Kuwertz
  • M. Kuze
  • J. Kvita
  • T. Kwan
  • D. Kyriazopoulos
  • A. La Rosa
  • J. L. La Rosa Navarro
  • L. La Rotonda
  • F. La Ruffa
  • C. Lacasta
  • F. Lacava
  • J. Lacey
  • D. P. J. Lack
  • H. Lacker
  • D. Lacour
  • E. Ladygin
  • R. Lafaye
  • B. Laforge
  • T. Lagouri
  • S. Lai
  • S. Lammers
  • W. Lampl
  • E. Lançon
  • U. Landgraf
  • M. P. J. Landon
  • M. C. Lanfermann
  • V. S. Lang
  • J. C. Lange
  • R. J. Langenberg
  • A. J. Lankford
  • F. Lanni
  • K. Lantzsch
  • A. Lanza
  • A. Lapertosa
  • S. Laplace
  • J. F. Laporte
  • T. Lari
  • F. Lasagni Manghi
  • M. Lassnig
  • T. S. Lau
  • P. Laurelli
  • W. Lavrijsen
  • A. T. Law
  • P. Laycock
  • T. Lazovich
  • M. Lazzaroni
  • B. Le
  • O. Le Dortz
  • E. Le Guirriec
  • E. P. Le Quilleuc
  • M. LeBlanc
  • T. LeCompte
  • F. Ledroit-Guillon
  • C. A. Lee
  • G. R. Lee
  • S. C. Lee
  • L. Lee
  • B. Lefebvre
  • G. Lefebvre
  • M. Lefebvre
  • F. Legger
  • C. Leggett
  • G. Lehmann Miotto
  • X. Lei
  • W. A. Leight
  • M. A. L. Leite
  • R. Leitner
  • D. Lellouch
  • B. Lemmer
  • K. J. C. Leney
  • T. Lenz
  • B. Lenzi
  • R. Leone
  • S. Leone
  • C. Leonidopoulos
  • G. Lerner
  • C. Leroy
  • R. Les
  • A. A. J. Lesage
  • C. G. Lester
  • M. Levchenko
  • J. Levêque
  • D. Levin
  • L. J. Levinson
  • M. Levy
  • D. Lewis
  • B. Li
  • C. Li
  • H. Li
  • L. Li
  • Q. Li
  • Q. Li
  • S. Li
  • X. Li
  • Y. Li
  • Z. Liang
  • B. Liberti
  • A. Liblong
  • K. Lie
  • J. Liebal
  • W. Liebig
  • A. Limosani
  • C. Y. Lin
  • K. Lin
  • S. C. Lin
  • T. H. Lin
  • R. A. Linck
  • B. E. Lindquist
  • A. E. Lionti
  • E. Lipeles
  • A. Lipniacka
  • M. Lisovyi
  • T. M. Liss
  • A. Lister
  • A. M. Litke
  • B. Liu
  • H. Liu
  • H. Liu
  • J. K. K. Liu
  • J. Liu
  • J. B. Liu
  • K. Liu
  • L. Liu
  • M. Liu
  • Y. L. Liu
  • Y. Liu
  • M. Livan
  • A. Lleres
  • J. Llorente Merino
  • S. L. Lloyd
  • C. Y. Lo
  • F. Lo Sterzo
  • E. M. Lobodzinska
  • P. Loch
  • F. K. Loebinger
  • A. Loesle
  • K. M. Loew
  • T. Lohse
  • K. Lohwasser
  • M. Lokajicek
  • B. A. Long
  • J. D. Long
  • R. E. Long
  • L. Longo
  • K. A. Looper
  • J. A. Lopez
  • I. Lopez Paz
  • A. Lopez Solis
  • J. Lorenz
  • N. Lorenzo Martinez
  • M. Losada
  • P. J. Lösel
  • X. Lou
  • A. Lounis
  • J. Love
  • P. A. Love
  • H. Lu
  • N. Lu
  • Y. J. Lu
  • H. J. Lubatti
  • C. Luci
  • A. Lucotte
  • C. Luedtke
  • F. Luehring
  • W. Lukas
  • L. Luminari
  • O. Lundberg
  • B. Lund-Jensen
  • M. S. Lutz
  • P. M. Luzi
  • D. Lynn
  • R. Lysak
  • E. Lytken
  • F. Lyu
  • V. Lyubushkin
  • H. Ma
  • L. L. Ma
  • Y. Ma
  • G. Maccarrone
  • A. Macchiolo
  • C. M. Macdonald
  • B. Maček
  • J. Machado Miguens
  • D. Madaffari
  • R. Madar
  • W. F. Mader
  • A. Madsen
  • N. Madysa
  • J. Maeda
  • S. Maeland
  • T. Maeno
  • A. S. Maevskiy
  • V. Magerl
  • C. Maiani
  • C. Maidantchik
  • T. Maier
  • A. Maio
  • O. Majersky
  • S. Majewski
  • Y. Makida
  • N. Makovec
  • B. Malaescu
  • Pa. Malecki
  • V. P. Maleev
  • F. Malek
  • U. Mallik
  • D. Malon
  • C. Malone
  • S. Maltezos
  • S. Malyukov
  • J. Mamuzic
  • G. Mancini
  • I. Mandić
  • J. Maneira
  • L. Manhaes de Andrade Filho
  • J. Manjarres Ramos
  • K. H. Mankinen
  • A. Mann
  • A. Manousos
  • B. Mansoulie
  • J. D. Mansour
  • R. Mantifel
  • M. Mantoani
  • S. Manzoni
  • L. Mapelli
  • G. Marceca
  • L. March
  • L. Marchese
  • G. Marchiori
  • M. Marcisovsky
  • C. A. Marin Tobon
  • M. Marjanovic
  • D. E. Marley
  • F. Marroquim
  • S. P. Marsden
  • Z. Marshall
  • M.U.F. Martensson
  • S. Marti-Garcia
  • C. B. Martin
  • T. A. Martin
  • V. J. Martin
  • B. Martin dit Latour
  • M. Martinez
  • V. I. Martinez Outschoorn
  • S. Martin-Haugh
  • V. S. Martoiu
  • A. C. Martyniuk
  • A. Marzin
  • L. Masetti
  • T. Mashimo
  • R. Mashinistov
  • J. Masik
  • A. L. Maslennikov
  • L. H. Mason
  • L. Massa
  • P. Mastrandrea
  • A. Mastroberardino
  • T. Masubuchi
  • P. Mättig
  • J. Maurer
  • S. J. Maxfield
  • D. A. Maximov
  • R. Mazini
  • I. Maznas
  • S. M. Mazza
  • N. C. Mc Fadden
  • G. Mc Goldrick
  • S. P. Mc Kee
  • A. McCarn
  • R. L. McCarthy
  • T. G. McCarthy
  • L. I. McClymont
  • E. F. McDonald
  • J. A. Mcfayden
  • G. Mchedlidze
  • S. J. McMahon
  • P. C. McNamara
  • C. J. McNicol
  • R. A. McPherson
  • S. Meehan
  • T. J. Megy
  • S. Mehlhase
  • A. Mehta
  • T. Meideck
  • K. Meier
  • B. Meirose
  • D. Melini
  • B. R. Mellado Garcia
  • J. D. Mellenthin
  • M. Melo
  • F. Meloni
  • A. Melzer
  • S. B. Menary
  • L. Meng
  • X. T. Meng
  • A. Mengarelli
  • S. Menke
  • E. Meoni
  • S. Mergelmeyer
  • C. Merlassino
  • P. Mermod
  • L. Merola
  • C. Meroni
  • F. S. Merritt
  • A. Messina
  • J. Metcalfe
  • A. S. Mete
  • C. Meyer
  • J-P. Meyer
  • J. Meyer
  • H. Meyer Zu Theenhausen
  • F. Miano
  • R. P. Middleton
  • S. Miglioranzi
  • L. Mijović
  • G. Mikenberg
  • M. Mikestikova
  • M. Mikuž
  • M. Milesi
  • A. Milic
  • D. A. Millar
  • D. W. Miller
  • C. Mills
  • A. Milov
  • D. A. Milstead
  • A. A. Minaenko
  • Y. Minami
  • I. A. Minashvili
  • A. I. Mincer
  • B. Mindur
  • M. Mineev
  • Y. Minegishi
  • Y. Ming
  • L. M. Mir
  • A. Mirto
  • K. P. Mistry
  • T. Mitani
  • J. Mitrevski
  • V. A. Mitsou
  • A. Miucci
  • P. S. Miyagawa
  • A. Mizukami
  • J. U. Mjörnmark
  • T. Mkrtchyan
  • M. Mlynarikova
  • T. Moa
  • K. Mochizuki
  • P. Mogg
  • S. Mohapatra
  • S. Molander
  • R. Moles-Valls
  • M. C. Mondragon
  • K. Mönig
  • J. Monk
  • E. Monnier
  • A. Montalbano
  • J. Montejo Berlingen
  • F. Monticelli
  • S. Monzani
  • R. W. Moore
  • N. Morange
  • D. Moreno
  • M. Moreno Llácer
  • P. Morettini
  • S. Morgenstern
  • D. Mori
  • T. Mori
  • M. Morii
  • M. Morinaga
  • V. Morisbak
  • A. K. Morley
  • G. Mornacchi
  • J. D. Morris
  • L. Morvaj
  • P. Moschovakos
  • M. Mosidze
  • H. J. Moss
  • J. Moss
  • K. Motohashi
  • R. Mount
  • E. Mountricha
  • E. J. W. Moyse
  • S. Muanza
  • F. Mueller
  • J. Mueller
  • R. S. P. Mueller
  • D. Muenstermann
  • P. Mullen
  • G. A. Mullier
  • F. J. Munoz Sanchez
  • W. J. Murray
  • H. Musheghyan
  • M. Muškinja
  • A. G. Myagkov
  • M. Myska
  • B. P. Nachman
  • O. Nackenhorst
  • K. Nagai
  • R. Nagai
  • K. Nagano
  • Y. Nagasaka
  • K. Nagata
  • M. Nagel
  • E. Nagy
  • A. M. Nairz
  • Y. Nakahama
  • K. Nakamura
  • T. Nakamura
  • I. Nakano
  • R. F. Naranjo Garcia
  • R. Narayan
  • D. I. Narrias Villar
  • I. Naryshkin
  • T. Naumann
  • G. Navarro
  • R. Nayyar
  • H. A. Neal
  • P. Yu. Nechaeva
  • T. J. Neep
  • A. Negri
  • M. Negrini
  • S. Nektarijevic
  • C. Nellist
  • A. Nelson
  • M. E. Nelson
  • S. Nemecek
  • P. Nemethy
  • M. Nessi
  • M. S. Neubauer
  • M. Neumann
  • P. R. Newman
  • T. Y. Ng
  • Y. S. Ng
  • T. Nguyen Manh
  • R. B. Nickerson
  • R. Nicolaidou
  • J. Nielsen
  • N. Nikiforou
  • V. Nikolaenko
  • I. Nikolic-Audit
  • K. Nikolopoulos
  • J. K. Nilsen
  • P. Nilsson
  • Y. Ninomiya
  • A. Nisati
  • N. Nishu
  • R. Nisius
  • I. Nitsche
  • T. Nitta
  • T. Nobe
  • Y. Noguchi
  • M. Nomachi
  • I. Nomidis
  • M. A. Nomura
  • T. Nooney
  • M. Nordberg
  • N. Norjoharuddeen
  • O. Novgorodova
  • M. Nozaki
  • L. Nozka
  • K. Ntekas
  • E. Nurse
  • F. Nuti
  • K. O’connor
  • D. C. O’Neil
  • A. A. O’Rourke
  • V. O’Shea
  • F. G. Oakham
  • H. Oberlack
  • T. Obermann
  • J. Ocariz
  • A. Ochi
  • I. Ochoa
  • J. P. Ochoa-Ricoux
  • S. Oda
  • S. Odaka
  • A. Oh
  • S. H. Oh
  • C. C. Ohm
  • H. Ohman
  • H. Oide
  • H. Okawa
  • Y. Okumura
  • T. Okuyama
  • A. Olariu
  • L. F. Oleiro Seabra
  • S. A. Olivares Pino
  • D. Oliveira Damazio
  • A. Olszewski
  • J. Olszowska
  • A. Onofre
  • K. Onogi
  • P. U. E. Onyisi
  • H. Oppen
  • M. J. Oreglia
  • Y. Oren
  • D. Orestano
  • N. Orlando
  • R. S. Orr
  • B. Osculati
  • R. Ospanov
  • G. Otero y Garzon
  • H. Otono
  • M. Ouchrif
  • F. Ould-Saada
  • A. Ouraou
  • K. P. Oussoren
  • Q. Ouyang
  • M. Owen
  • R. E. Owen
  • V. E. Ozcan
  • N. Ozturk
  • K. Pachal
  • A. Pacheco Pages
  • L. Pacheco Rodriguez
  • C. Padilla Aranda
  • S. Pagan Griso
  • M. Paganini
  • F. Paige
  • G. Palacino
  • S. Palazzo
  • S. Palestini
  • M. Palka
  • D. Pallin
  • E. St. Panagiotopoulou
  • I. Panagoulias
  • C. E. Pandini
  • J. G. Panduro Vazquez
  • P. Pani
  • S. Panitkin
  • D. Pantea
  • L. Paolozzi
  • Th. D. Papadopoulou
  • K. Papageorgiou
  • A. Paramonov
  • D. Paredes Hernandez
  • A. J. Parker
  • M. A. Parker
  • K. A. Parker
  • F. Parodi
  • J. A. Parsons
  • U. Parzefall
  • V. R. Pascuzzi
  • J. M. Pasner
  • E. Pasqualucci
  • S. Passaggio
  • Fr. Pastore
  • S. Pataraia
  • J. R. Pater
  • T. Pauly
  • B. Pearson
  • S. Pedraza Lopez
  • R. Pedro
  • S. V. Peleganchuk
  • O. Penc
  • C. Peng
  • H. Peng
  • J. Penwell
  • B. S. Peralva
  • M. M. Perego
  • D. V. Perepelitsa
  • F. Peri
  • L. Perini
  • H. Pernegger
  • S. Perrella
  • R. Peschke
  • V. D. Peshekhonov
  • K. Peters
  • R. F. Y. Peters
  • B. A. Petersen
  • T. C. Petersen
  • E. Petit
  • A. Petridis
  • C. Petridou
  • P. Petroff
  • E. Petrolo
  • M. Petrov
  • F. Petrucci
  • N. E. Pettersson
  • A. Peyaud
  • R. Pezoa
  • F. H. Phillips
  • P. W. Phillips
  • G. Piacquadio
  • E. Pianori
  • A. Picazio
  • M. A. Pickering
  • R. Piegaia
  • J. E. Pilcher
  • A. D. Pilkington
  • M. Pinamonti
  • J. L. Pinfold
  • H. Pirumov
  • M. Pitt
  • L. Plazak
  • M.-A. Pleier
  • V. Pleskot
  • E. Plotnikova
  • D. Pluth
  • P. Podberezko
  • R. Poettgen
  • R. Poggi
  • L. Poggioli
  • I. Pogrebnyak
  • D. Pohl
  • I. Pokharel
  • G. Polesello
  • A. Poley
  • A. Policicchio
  • R. Polifka
  • A. Polini
  • C. S. Pollard
  • V. Polychronakos
  • K. Pommès
  • D. Ponomarenko
  • L. Pontecorvo
  • G. A. Popeneciu
  • D. M. Portillo Quintero
  • S. Pospisil
  • K. Potamianos
  • I. N. Potrap
  • C. J. Potter
  • H. Potti
  • T. Poulsen
  • J. Poveda
  • M. E. Pozo Astigarraga
  • P. Pralavorio
  • A. Pranko
  • S. Prell
  • D. Price
  • M. Primavera
  • S. Prince
  • N. Proklova
  • K. Prokofiev
  • F. Prokoshin
  • S. Protopopescu
  • J. Proudfoot
  • M. Przybycien
  • A. Puri
  • P. Puzo
  • J. Qian
  • G. Qin
  • Y. Qin
  • A. Quadt
  • M. Queitsch-Maitland
  • D. Quilty
  • S. Raddum
  • V. Radeka
  • V. Radescu
  • S. K. Radhakrishnan
  • P. Radloff
  • P. Rados
  • F. Ragusa
  • G. Rahal
  • J. A. Raine
  • S. Rajagopalan
  • C. Rangel-Smith
  • T. Rashid
  • S. Raspopov
  • M. G. Ratti
  • D. M. Rauch
  • F. Rauscher
  • S. Rave
  • I. Ravinovich
  • J. H. Rawling
  • M. Raymond
  • A. L. Read
  • N. P. Readioff
  • M. Reale
  • D. M. Rebuzzi
  • A. Redelbach
  • G. Redlinger
  • R. Reece
  • R. G. Reed
  • K. Reeves
  • L. Rehnisch
  • J. Reichert
  • A. Reiss
  • C. Rembser
  • H. Ren
  • M. Rescigno
  • S. Resconi
  • E. D. Resseguie
  • S. Rettie
  • E. Reynolds
  • O. L. Rezanova
  • P. Reznicek
  • R. Rezvani
  • R. Richter
  • S. Richter
  • E. Richter-Was
  • O. Ricken
  • M. Ridel
  • P. Rieck
  • C. J. Riegel
  • J. Rieger
  • O. Rifki
  • M. Rijssenbeek
  • A. Rimoldi
  • M. Rimoldi
  • L. Rinaldi
  • G. Ripellino
  • B. Ristić
  • E. Ritsch
  • I. Riu
  • F. Rizatdinova
  • E. Rizvi
  • C. Rizzi
  • R. T. Roberts
  • S. H. Robertson
  • A. Robichaud-Veronneau
  • D. Robinson
  • J. E. M. Robinson
  • A. Robson
  • E. Rocco
  • C. Roda
  • Y. Rodina
  • S. Rodriguez Bosca
  • A. Rodriguez Perez
  • D. Rodriguez Rodriguez
  • S. Roe
  • C. S. Rogan
  • O. Røhne
  • J. Roloff
  • A. Romaniouk
  • M. Romano
  • S. M. Romano Saez
  • E. Romero Adam
  • N. Rompotis
  • M. Ronzani
  • L. Roos
  • S. Rosati
  • K. Rosbach
  • P. Rose
  • N.-A. Rosien
  • E. Rossi
  • L. P. Rossi
  • J. H. N. Rosten
  • R. Rosten
  • M. Rotaru
  • J. Rothberg
  • D. Rousseau
  • A. Rozanov
  • Y. Rozen
  • X. Ruan
  • F. Rubbo
  • F. Rühr
  • A. Ruiz-Martinez
  • Z. Rurikova
  • N. A. Rusakovich
  • H. L. Russell
  • J. P. Rutherfoord
  • N. Ruthmann
  • E. M. Rüttinger
  • Y. F. Ryabov
  • M. Rybar
  • G. Rybkin
  • S. Ryu
  • A. Ryzhov
  • G. F. Rzehorz
  • A. F. Saavedra
  • G. Sabato
  • S. Sacerdoti
  • H.F-W. Sadrozinski
  • R. Sadykov
  • F. Safai Tehrani
  • P. Saha
  • M. Sahinsoy
  • M. Saimpert
  • M. Saito
  • T. Saito
  • H. Sakamoto
  • Y. Sakurai
  • G. Salamanna
  • J. E. Salazar Loyola
  • D. Salek
  • P. H. Sales De Bruin
  • D. Salihagic
  • A. Salnikov
  • J. Salt
  • D. Salvatore
  • F. Salvatore
  • A. Salvucci
  • A. Salzburger
  • D. Sammel
  • D. Sampsonidis
  • D. Sampsonidou
  • J. Sánchez
  • V. Sanchez Martinez
  • A. Sanchez Pineda
  • H. Sandaker
  • R. L. Sandbach
  • C. O. Sander
  • M. Sandhoff
  • C. Sandoval
  • D. P. C. Sankey
  • M. Sannino
  • Y. Sano
  • A. Sansoni
  • C. Santoni
  • H. Santos
  • I. Santoyo Castillo
  • A. Sapronov
  • J. G. Saraiva
  • B. Sarrazin
  • O. Sasaki
  • K. Sato
  • E. Sauvan
  • G. Savage
  • P. Savard
  • N. Savic
  • C. Sawyer
  • L. Sawyer
  • J. Saxon
  • C. Sbarra
  • A. Sbrizzi
  • T. Scanlon
  • D. A. Scannicchio
  • J. Schaarschmidt
  • P. Schacht
  • B. M. Schachtner
  • D. Schaefer
  • L. Schaefer
  • R. Schaefer
  • J. Schaeffer
  • S. Schaepe
  • S. Schaetzel
  • U. Schäfer
  • A. C. Schaffer
  • D. Schaile
  • R. D. Schamberger
  • V. A. Schegelsky
  • D. Scheirich
  • M. Schernau
  • C. Schiavi
  • S. Schier
  • L. K. Schildgen
  • C. Schillo
  • M. Schioppa
  • S. Schlenker
  • K. R. Schmidt-Sommerfeld
  • K. Schmieden
  • C. Schmitt
  • S. Schmitt
  • S. Schmitz
  • U. Schnoor
  • L. Schoeffel
  • A. Schoening
  • B. D. Schoenrock
  • E. Schopf
  • M. Schott
  • J. F. P. Schouwenberg
  • J. Schovancova
  • S. Schramm
  • N. Schuh
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  • ATLAS Collaboration
Open Access
Regular Article - Experimental Physics

Abstract

This paper presents single lepton and dilepton kinematic distributions measured in dileptonic \(t\bar{t}\) events produced in 20.2\(\hbox {fb}^{-1}\) of \(\sqrt{s}=8\) TeV pp collisions recorded by the ATLAS experiment at the LHC. Both absolute and normalised differential cross-sections are measured, using events with an opposite-charge \(e\mu \) pair and one or two b-tagged jets. The cross-sections are measured in a fiducial region corresponding to the detector acceptance for leptons, and are compared to the predictions from a variety of Monte Carlo event generators, as well as fixed-order QCD calculations, exploring the sensitivity of the cross-sections to the gluon parton distribution function. Some of the distributions are also sensitive to the top quark pole mass; a combined fit of NLO fixed-order predictions to all the measured distributions yields a top quark mass value of \({m_t^{\mathrm {pole}}}=173.2\pm 0.9\pm 0.8\pm 1.2\) GeV, where the three uncertainties arise from data statistics, experimental systematics, and theoretical sources.

1 Introduction

The top quark is the heaviest known fundamental particle, with a mass (\(m_t\)) that is much larger than any of the other quarks, and close to the scale of electroweak symmetry breaking. The study of its production and decay properties in proton–proton (pp) collisions forms an important part of the ATLAS physics program at the CERN Large Hadron Collider (LHC). Due to its large mass and production cross-section, top quark production is also a significant background to many searches for physics beyond the Standard Model, making precise predictions of absolute rates and differential distributions for top quark production a vital tool in fully exploiting the discovery potential of the LHC.

At the LHC, top quarks are primarily produced as quark-antiquark pairs (\(t\bar{t}\)). The inclusive \(t\bar{t}\) production cross-section \(\sigma _{t\bar{t}}\) has been calculated at full next-to-next-to-leading-order (NNLO) accuracy in the strong coupling constant \(\alpha _{\text {S}}\), including the resummation of next-to-next-to-leading logarithmic (NNLL) soft gluon terms [1, 2, 3, 4, 5]. The resulting prediction at a centre-of-mass energy \(\sqrt{s}=8\) TeV is \({\sigma _{t\bar{t}}}=252.9\pm 11.7^{+6,4}_{-8.6}\) pb for a top quark mass of 172.5 GeV, calculated using the top++ 2.0 program [6]. The first uncertainty is due to parton distribution function (PDF) and \(\alpha _{\text {S}}\) uncertainties, calculated using the PDF4LHC prescription [7] with the MSTW2008 68% [8, 9], CT10 NNLO [10, 11] and NNPDF 2.3 5f FFN [12] PDF sets, and the second to quantum chromodynamics (QCD) scale variations. This prediction, which has a relative precision of 5.5%, agrees with measurements from ATLAS and CMS at \(\sqrt{s}=8\) TeV [13, 14, 15] which have reached a precision of 3–4%. Measurements in LHC pp collisions at \(\sqrt{s}=7\) TeV [13, 15] and more recently at \(\sqrt{s}=13\) TeV [16, 17] are also in good agreement with the corresponding NNLO + NNLL predictions.

Going beyond the inclusive production cross-section, measurements of \(t\bar{t}\) production as a function of the top quark and \(t\bar{t}\) system kinematics properties allow the predictions of QCD calculations and Monte Carlo event-generator programs to be probed in more detail. These comparisons are typically more sensitive at the level of normalised differential cross-sections, i.e. shape comparisons, where both experimental and theoretical uncertainties are reduced. Measurements by ATLAS [18, 19, 20, 21] and CMS [22, 23, 24] have generally demonstrated good agreement with the predictions of leading-order (LO) multi-leg and next-to-leading-order (NLO) event generators and calculations, though the top quark \(p_{\text {T}}\) spectrum is measured to be softer than the predictions by both experiments; this distribution appears to be sensitive to the additional corrections contributing at NNLO [25]. Measurements of jet activity in \(t\bar{t}\) events [26, 27, 28, 29] are also sensitive to gluon radiation and hence the \(t\bar{t}\) production dynamics, without the need to fully reconstruct the kinematics of the \(t\bar{t}\) system. However, all these measurements require sophisticated unfolding procedures to correct for the detector acceptance and resolution. This leads to significant systematic uncertainties, especially due to modelling of the showers and hadronisation of the quarks produced in the top quark decays, and the measurement of the resulting jets in the detector.

In the Standard Model (SM), the top quark decays almost exclusively to a W boson and a b quark, and the final state topologies in \(t\bar{t}\) production are governed by the decay modes of the W bosons. The channel where one W boson decays to an electron (\(W\rightarrow e\nu \)) and the other to a muon (\(W\rightarrow \mu \nu \)), giving rise to the \(e^+\mu ^-\nu \bar{\nu }b\bar{b} \) final state,1 is particularly clean and was exploited to make the most precise ATLAS measurements of \(\sigma _{t\bar{t}}\) [13, 17]. The leptons carry information about the underlying top quark kinematics, are free of the uncertainties related to the hadronic part of the final state, and are precisely measured in the detector. Measurements of the \(t\bar{t}\) differential cross-section as a function of the lepton kinematics therefore have the potential to provide a complementary view of \(t\bar{t}\) production and decay dynamics to that provided by the complete reconstruction of the \(t\bar{t}\) final state.

This paper reports such a measurement of the absolute and normalised differential cross-sections for \(t\bar{t} \rightarrow e\mu \nu \bar{\nu }b\bar{b} \) produced in pp collisions at \(\sqrt{s}=8\) TeV, as a function of the kinematics of the single leptons and of the dilepton system. Eight differential cross-section distributions are measured: the transverse momentum \(p_{\mathrm T}^{\ell }\) and absolute pseudorapidity \(|\eta ^{\ell }|\) of the single leptons (identical for electrons and muons), the \(p_{\text {T}}\), invariant mass and absolute rapidity of the dilepton system (\(p_{\mathrm T}^{e\mu }\), \(m^{e\mu }\) and \(|y^{e\mu }|\)), the azimuthal angle in the transverse plane \(\Delta \phi ^{e\mu }\) between the two leptons, the scalar sum \(p_{\mathrm T}^{e}+p_{\mathrm T}^{\mu }\) of the \(p_{\text {T}}\) of the two leptons, and the sum \(E^{e}+E^{\mu }\) of the energies of the two leptons.2 The measurements are corrected to particle level and reported in a fiducial volume where both leptons have \(p_{\text {T}} >25\) GeV and \(|\eta |<2.5\), avoiding extrapolations into regions of leptonic phase space which are not measured. The particle-level definition includes the contribution of events where one or both W bosons decay to electrons or muons via leptonic decays of \(\tau \)-leptons (\(t\rightarrow W\rightarrow \tau \rightarrow e/\mu \)), but an alternative set of results is provided where the contributions of \(\tau \)-leptons are removed with a correction derived from simulation. The definition of the fiducial volume does not make any requirement on the presence of jets from the hadronic decay products of the \(t\bar{t}\) system. The measurements are made using events with an opposite-charge \(e\mu \) pair and one or two b-tagged jets, and extrapolated to the fiducial volume (without jet requirements), using an extension of the double-tagging technique used in the inclusive \(t\bar{t}\) cross-section measurement [13]. This approach minimises the systematic uncertainties due to the use of jets and b-tagging in the experimental event selection. Since the lepton kinematics are precisely measured in the ATLAS detector, a simple bin-by-bin correction technique is adequate to correct for efficiency and resolution effects, without the need for a full unfolding procedure.

The results are compared to the predictions of various NLO and LO multi-leg \(t\bar{t}\) event generators, and to fixed-order perturbative QCD predictions from the MCFM [30] program, which is used to explore the sensitivity to PDFs and QCD scale uncertainties. These comparisons are complementary to previous ATLAS analyses exploring how well \(t\bar{t}\) event generators can describe the jet activity [27] and production of extra heavy-flavour jets [31] in the \(\sqrt{s}=8\) TeV \(t\bar{t}\) dilepton sample.

Some of the cross-section distributions are sensitive to the top quark mass, as suggested in Ref. [32], and mass measurements are made by comparing the measured distributions to predictions from both NLO plus parton shower event generators and fixed-order QCD calculations. The former are similar to traditional measurements where the top quark mass is reconstructed from its decay products [33, 34, 35, 36], but rely only on the leptonic decay products of the \(t\bar{t}\) system and are less sensitive to experimental uncertainties related to the hadronic part of the final state. The measurements based on fixed-order QCD predictions in a well-defined renormalisation scheme correspond more directly to a measurement of the top quark pole mass \(m_t^{\mathrm {pole}}\), the mass definition corresponding to that of a free particle, which may differ from that measured in direct reconstruction of the decay products by \(O(1\,\mathrm{GeV})\) [37, 38, 39]. Previous determinations of \(m_t^{\mathrm {pole}}\) from inclusive and differential \(t\bar{t}\) cross-section measurements are compatible with the top quark mass measured from direct reconstruction, with uncertainties of 2–3 GeV [13, 15, 40, 41].

The data and Monte Carlo simulation samples used in this analysis are described in Sect. 2, followed by the event reconstruction and selection in Sect. 3, definition and determination of the fiducial differential cross-sections in Sect. 4 and systematic uncertainties in Sect. 5. Results and comparisons with predictions are given in Sect. 6. The ability of the data to constrain the gluon PDF is investigated in Sect. 7 and the determination of the top quark mass is discussed in Sect. 8. Finally, conclusions are given in Sect. 9.
Table 1

Summary of simulated event samples used for \(t\bar{t}\) signal and background modelling, giving the matrix-element event generator, PDF set, parton shower and associated tune parameter set. More details, including generator version numbers and references, are given in the text

Process

Matrix-element

PDF

Parton shower

Tune

Comments

\(t\bar{t}\)

Powheg

CT10

Pythia6

P2011C

\({h_{\mathrm {damp}}}={m_t}\)

Powheg

CT10

Herwig+Jimmy

AUET2

\({h_{\mathrm {damp}}}=\infty \)

MC@NLO

CT10

Herwig+Jimmy

AUET2

 

Alpgen

CTEQ6L1

Herwig+Jimmy

AUET2

incl. \(t\bar{t}\) \(b\bar{b}\), \(t\bar{t}\) \(c\bar{c}\)

Powheg

CT10

Pythia6

P2012 radHi

\({h_{\mathrm {damp}}}=2{m_t}\), \(\frac{1}{2}\mu _{F,R}\)

Powheg

CT10

Pythia6

P2012 radLo

\({h_{\mathrm {damp}}}={m_t}\), \(2\mu _{F,R}\)

Wt

Powheg

CT10

Pythia6

P2011C

diagram removal

ZW+jets

Alpgen

CTEQ6L1

Pythia6

P2011C

incl. \(Zb\bar{b} \)

WW, WZ, ZZ

Alpgen

CTEQ6L1

Herwig

AUET2

 

\(t\bar{t}\) +WZ

MadGraph

CTEQ6L1

Pythia6

P2011C

 

\(W\gamma \)+jets

Sherpa

CT10

Sherpa

default

 

t-channel top

AcerMC

CTEQ6L1

Pythia6

AUET2B

 

2 Data and simulated samples

The ATLAS detector [42] at the LHC covers nearly the entire solid angle around the collision point, and consists of an inner tracking detector surrounded by a thin superconducting solenoid magnet producing a 2 T axial magnetic field, electromagnetic and hadronic calorimeters, and an external muon spectrometer incorporating three large toroidal magnet assemblies. The analysis was performed on a sample of proton–proton collision data at \(\sqrt{s}=8\) TeV recorded by the ATLAS detector in 2012, corresponding to an integrated luminosity of 20.2 \(\hbox {fb}^{-1}\). Events were required to pass a single-electron or single-muon trigger, with thresholds set to be fully efficient for leptons with \(p_{\text {T}} >25\) GeV passing offline selections. Each triggered event also includes the signals from on average 20 additional inelastic pp collisions in the same bunch crossing, referred to as pileup.

Monte Carlo simulated event samples were used to develop the analysis procedures, to compare with data, and to evaluate signal efficiencies and background contributions. An overview of the samples used for signal and background modelling is shown in Table 1, and further details are given below. Samples were processed using either the full ATLAS detector simulation [43] based on GEANT4 [44], or a faster simulation making use of parameterised showers in the calorimeters [45]. The effects of pileup were simulated by generating additional inelastic pp collisions with Pythia8 [46] using the A2 parameter set (tune) [47] and overlaying them on the primary simulated events. These combined events were then processed using the same reconstruction and analysis chain as the data. Small corrections were applied to the lepton trigger and selection efficiencies better to model the performance measured in data.

The baseline simulated \(t\bar{t}\) sample was produced using the NLO matrix element event generator Powheg-Box v1.0 (referred to hereafter as Powheg) [48, 49, 50, 51] using the CT10 PDFs [10], interfaced to Pythia6 (version 6.426) [52] with the CTEQ6L1 PDF set [53] and the Perugia 2011C (P2011C) tune [54] for parton shower, hadronisation and underlying event modelling. This setup provides an NLO QCD prediction of the \(t\bar{t}\) production process, a leading-order prediction for the top quark decays, and an approximate treatment of the spin correlations between the quark and antiquark. The Powheg parameter \(h_{\mathrm {damp}}\), used in the damping function that limits the resummation of higher-order effects incorporated into the Sudakov form factor, was set to \(m_t\). This value was found to give a better modelling of the \(t\bar{t}\) system \(p_{\text {T}}\) at \(\sqrt{s}=7\) TeV [55] than the setting of \({h_{\mathrm {damp}}}=\infty \) used for the baseline \(t\bar{t}\) sample in Ref. [13], which corresponds to no damping.

Alternative \(t\bar{t}\) simulation samples used to evaluate systematic uncertainties were generated with Powheg interfaced to Herwig (version 6.520) [56, 57] with the ATLAS AUET2 tune [58] and Jimmy (version 4.31) [59] for underlying event modelling, with MC@NLO (version 4.01) [60, 61] interfaced to Herwig + Jimmy, and with the leading-order ‘multi-leg’ event generator Alpgen (version 2.13) [62], also interfaced to Herwig + Jimmy. The Alpgen samples used leading-order matrix elements for \(t\bar{t}\) production accompanied by up to three additional light partons, and dedicated matrix elements for \(t\bar{t}\) plus \(b\bar{b}\) or \(c\bar{c}\) production, together with the MLM parton-jet matching scheme [63] to account for double-counting of configurations generated by both the parton shower and matrix-element calculation. The effects of additional radiation in \(t\bar{t}\) events were further studied using two additional Powheg + Pythia6 samples, one using the Perugia 2012 radHi tune [54], with \(h_{\mathrm {damp}}\) set to \(2{m_t}\) and factorisation and renormalisation scales \(\mu _F\) and \(\mu _R\) reduced from their event generator defaults by a factor of two, giving more parton shower radiation; and one with the Perugia 2012 radLo tune [54], \(\mu _F\) and \(\mu _R\) increased by a factor of two and \({h_{\mathrm {damp}}}={m_t}\), giving less parton shower radiation. The parameters of these samples were chosen to span the uncertainties in jet observables measured by ATLAS in \(t\bar{t}\) events at \(\sqrt{s}=7\) TeV [26, 55, 64]. The top quark mass was set to 172.5 GeV in all these samples, consistent with recent measurements by ATLAS [35] and CMS [36]. They were all normalised to the NNLO + NNLL cross-section prediction discussed in Sect. 1 when comparing simulation with data. Further \(t\bar{t}\) simulation samples with different event generator setups were used for comparisons with the measured differential cross-sections as discussed in Sect. 6.2, and in the extraction of the top quark mass as discussed in Sect. 8.

Backgrounds to the \(t\bar{t}\) event selection are classified into two types: those with two real prompt leptons from W or Z boson decays (including those produced via leptonic \(\tau \) decays), and those where one of the reconstructed lepton candidates is misidentified, i.e. a non-prompt lepton from the decay of a bottom or charm hadron, an electron from a photon conversion, hadronic jet activity misidentified as an electron, or a muon produced from the decay in flight of a pion or kaon. The first category is dominated by the associated production of a W boson and a single top quark, Wt, that is simulated using Powheg + Pythia6 with the CT10 PDFs and the P2011C tune. The ‘diagram removal’ scheme was used to handle the interference between the \(t\bar{t}\) and Wt final states that occurs at NLO [65, 66]. Smaller backgrounds result from \(Z\rightarrow \tau \tau (\rightarrow e\mu )\)+jets, modelled using Alpgen + Pythia6 including leading-order matrix elements for \(Zb\bar{b} \) production, and diboson (WW, WZ and ZZ) production in association with jets, modelled with Alpgen + Herwig + Jimmy. The Wt background was normalised to the approximate NNLO cross-section of \(22.4\pm 1.5\) pb, determined as in Ref. [67]. The inclusive Z cross-section was set to the NNLO prediction from FEWZ [68], but the normalisation of the \(Z\rightarrow \tau \tau \) background with b-tagged jets was determined with the help of data control samples as discussed in Sect. 4.2. The small diboson background was normalised to the NLO QCD inclusive cross-section predictions calculated with MCFM [69], using the Alpgen + Herwig prediction for the fraction of diboson events with extra jets. Production of \(t\bar{t}\) in association with a W or Z boson, which contributes to the control sample with two same-charge leptons, was simulated with MadGraph [70] interfaced to Pythia6 with CTEQ6L1 PDFs, and normalised to NLO cross-section predictions [71, 72].

Backgrounds with one real and one misidentified lepton arise from \(t\bar{t}\) events with one hadronically-decaying W; W+jets production, modelled as described above for Z+jets; \(W\gamma \)+jets, modelled with Sherpa 1.4.1 [73] with CT10 PDFs; and t-channel single top production, modelled with AcerMC [74] with the AUET2B tune [75] and CTEQ6L1 PDFs interfaced to Pythia6. The normalisations of these backgrounds in the opposite-charge \(e\mu \) samples were determined with the help of the corresponding same-charge \(e\mu \) samples in data. Other backgrounds, including processes with two misidentified leptons, are negligible after the event selections used in this analysis.

3 Event reconstruction and selection

The analysis makes use of reconstructed electrons, muons, and b-tagged jets, selected exactly as described in Ref. [13]. In brief, electron candidates [76] were required to satisfy \(E_{\text {T}} >25\) GeV and \(|\eta |<2.47\), and to not lie within the transition region \(1.37<|\eta |<1.52\) between the barrel and endcap electromagnetic calorimeters. Muon candidates [77] were required to satisfy \(p_{\text {T}} >25\) GeV and \(|\eta |<2.5\). In order to reduce background from non-prompt leptons, electrons were required to be isolated from nearby hadronic activity using both calorimeter and tracking information, and muons were required to be isolated using tracking information alone. Jets were reconstructed using the anti-\(k_t\) algorithm [78, 79] with radius parameter \(R=0.4\) using calorimeter energy clusters calibrated with the local cluster weighting method [80]. Jets were further calibrated using information from both simulation and data [81, 82], and required to satisfy \(p_{\text {T}} >25\) GeV and \(|\eta |<2.5\). Jets satisfying \(p_{\text {T}} <50\) GeV and \(|\eta |<2.4\) were additionally required to pass pileup rejection criteria based on their associated tracks [82]. To further suppress non-isolated leptons likely to originate from heavy-flavour decays within jets, electron and muon candidates within \(\Delta R<0.4\) of selected jets were discarded. Finally, jets likely to contain b-hadrons were b-tagged using the MV1 algorithm [83], a multivariate discriminant making use of track impact parameters and reconstructed secondary vertices. A tagging working point corresponding to a 70% efficiency for tagging b-quark jets from top decays in \(t\bar{t}\) events was used, giving a rejection factor of about 140 against light-quark and gluon jets, and about five against jets originating from charm quarks.
Table 2

Observed numbers of opposite-sign \(e\mu \) events with one and two b-tagged jets (\(N_1\) and \(N_2\)) together with the estimates of backgrounds and associated total uncertainties described in Sect. 5

Event counts

\(N_1\)

\(N_2\)

Data

21666

11739

Wt single top

\( 2080\pm 210\)

\( 350\pm 120\)

\(Z(\rightarrow \tau \tau \rightarrow e\mu )\)+jets

\( 210\pm 40\)

\( 7\pm 2\)

Diboson

\( 120\pm 30\)

\( 3\pm 1\)

Misidentified leptons

\( 220\pm 80\)

\( 78\pm 50\)

Total background

\( 2630\pm 230\)

\( 440\pm 130\)

As in Ref. [13], events were required to have at least one reconstructed primary vertex3 and to have no jets with \(p_{\text {T}} >20\) GeV failing jet quality requirements [81]. Events having muons compatible with cosmic-ray interactions or losing substantial energy following bremsstrahlung in the calorimeter material were rejected. A preselection requiring exactly one electron and one muon selected as described above was then applied, requiring at least one selected lepton to be matched to a corresponding electron or muon trigger signature. Events with an opposite-charge-sign \(e\mu \) pair formed the main analysis sample, with events having a same-sign pair being used to estimate the background from misidentified leptons.

A total of 66,453 data events passed the opposite-sign \(e\mu \) preselection. Events were then further sub-divided according to the number of b-tagged jets, irrespective of the number of untagged jets, and events having one or two b-tagged jets were retained for further analysis. The numbers of one and two b-tagged jet events selected in data are shown in Table 2, compared with expected non-\(t\bar{t}\) contributions from Wt and dibosons evaluated from simulation, and \(Z(\rightarrow \tau \tau \rightarrow e\mu )\)+jets and misidentified leptons evaluated from data and simulation, as discussed in detail in Sects. 4.2 and 5 below.4 In simulation, the one b-tagged sample is about 88% pure and the two b-tagged sample 96% pure in \(t\bar{t}\) events, with the largest backgrounds coming from Wt production in both cases. The distribution of the number of b-tagged jets in preselected opposite-sign \(e\mu \) events is shown in Fig. 1a, compared to the predictions from simulation using Powheg + Pythia6 (PY6), MC@NLO + Herwig (HW) and Alpgen + Herwig \(t\bar{t}\) samples, normalising the total simulation prediction in each case using the integrated luminosity of the data sample. The distributions of the \(p_{\text {T}}\) of b-tagged jets, and the reconstructed electron and muon \(p_{\text {T}}\) and \(|\eta |\) in events with at least one b-tagged jet are shown in Fig. 1b–f, with the total simulation prediction normalised to the same number of events as the data to facilitate shape comparisons. The distributions of the reconstructed dilepton variables \(p_{\mathrm T}^{e\mu }\), \(m^{e\mu }\), \(|y^{e\mu }|\), \(\Delta \phi ^{e\mu }\), \(p_{\mathrm T}^{e}+p_{\mathrm T}^{\mu }\) and \(E^{e}+E^{\mu }\) are shown in Fig. 2, with the simulation normalised as for Fig. 1b–f. In general the data are well described by the predictions using the different \(t\bar{t}\) models, but a few differences are visible. The lepton \(p_{\text {T}}\) spectra are softer in data than in simulation, the lepton \(|\eta ^{\ell }|\) and dilepton \(|y^{e\mu }|\) distributions are more central than the Powheg + Pythia6 and MC@NLO + Herwig predictions, and the \(\Delta \phi ^{e\mu }\) distribution is slightly flatter in data than in all the predictions.
Fig. 1

Distributions of a the number of b-tagged jets in preselected opposite-sign \(e\mu \) events; and b the \(p_{\text {T}}\) of b-tagged jets, c the \(p_{\text {T}}\) of the electron, d the \(|\eta |\) of the electron, e the \(p_{\text {T}}\) of the muon and f the \(|\eta |\) of the muon, in events with an opposite-sign \(e\mu \) pair and at least one b-tagged jet. The reconstruction-level data are compared to the expectation from simulation, broken down into contributions from \(t\bar{t}\)  (Powheg + Pythia6), single top, Z+jets, dibosons, and events with misidentified electrons or muons. The simulation prediction is normalised to the same integrated luminosity as the data in a and to the same number of entries as the data in bf. The lower parts of the figure show the ratios of simulation to data, using various \(t\bar{t}\) signal samples and with the cyan band indicating the data statistical uncertainty. The last bin includes the overflow in panels b, c and e

Fig. 2

Distributions of a the dilepton \(p_{\mathrm T}^{e\mu }\), b invariant mass \(m^{e\mu }\), c rapidity \(|y^{e\mu }|\), d azimuthal angle difference \(\Delta \phi ^{e\mu }\), e lepton \(p_{\text {T}}\) sum \(p_{\mathrm T}^{e}+p_{\mathrm T}^{\mu }\) and f lepton energy sum \(E^{e}+E^{\mu }\), in events with an opposite-sign \(e\mu \) pair and at least one b-tagged jet. The reconstruction-level data are compared to the expectation from simulation, broken down into contributions from \(t\bar{t}\)  (Powheg + Pythia6), single top, Z+jets, dibosons, and events with misidentified electrons or muons, normalised to the same number of entries as the data. The lower parts of the figure show the ratios of simulation to data, using various \(t\bar{t}\) signal samples and with the cyan band indicating the data statistical uncertainty. The last bin includes the overflow in panels a, b, e and f

4 Fiducial cross-section determination

The cross-section measurements were made for a fiducial region, where the particle-level electron and muon were required to have opposite charge signs, to each come from W decays either directly or via \(W\rightarrow \tau \rightarrow e/\mu \) and to each satisfy \(p_{\text {T}} >25\) GeV and \(|\eta |<2.5\). The lepton four-momenta were taken after final-state radiation, and ‘dressed’ by including the four-momenta of any photons within a cone of size \(\Delta R=0.1\) around the lepton direction, excluding photons produced from hadronic decays or interactions with the detector material. The total cross-section within this fiducial volume corresponds to the fiducial cross-section measured in Ref. [13]. According to the predictions of the baseline Powheg + Pythia6 \(t\bar{t}\) simulation, it is about 44% of the total \(t\bar{t} \rightarrow e\mu \nu \bar{\nu }b\bar{b} \) cross-section without restrictions on the lepton acceptance and including contributions via \(W\rightarrow \tau \rightarrow e/\mu \).

4.1 Cross-section extraction

The differential cross-sections were measured using an extension of the technique used in Ref. [13], counting the number of leptons or events with one (\(N^i_1\)) or two (\(N^i_2\)) b-tagged jets where the lepton(s) fall in bin i of a differential distribution at reconstruction level. For the single-lepton distributions \(p_{\mathrm T}^{\ell }\) and \(|\eta ^{\ell }|\), there are two counts per event, in the two bins corresponding to the electron and muon. For the dilepton distributions, each event contributes a single count corresponding to the bin in which the appropriate dilepton variable falls. For each measured distribution, these counts satisfy the tagging equations:
$$\begin{aligned} \begin{array}{lll} {N^i_1}&{} = &{} L {\sigma ^i_{t\bar{t}}}\ {G^i_{e\mu }}2{\epsilon ^i_{b}}(1-{C^i_b}{\epsilon ^i_{b}}) + {N_1^{i,\mathrm {bkg}}}, \\ *[2mm] {N^i_2}&{} = &{} L {\sigma ^i_{t\bar{t}}}\ {G^i_{e\mu }}{C^i_b}({\epsilon ^i_{b}})^2 + {N_2^{i,\mathrm {bkg}}}, \end{array} \end{aligned}$$
(1)
where \(\sigma ^i_{t\bar{t}}\) is the absolute fiducial differential cross-section in bin i, and L is the integrated luminosity of the sample. The reconstruction efficiency \(G^i_{e\mu }\) represents the ratio of the number of reconstructed \(e\mu \) events (or leptons for \(p_{\mathrm T}^{\ell }\) and \(|\eta ^{\ell }|\)) falling in bin i at reconstruction level to the number of true \(e\mu \) events (or leptons) falling in the same bin at particle level, evaluated using \(t\bar{t}\) simulation without making any requirements on reconstructed or particle-level jets. It therefore corrects for both the lepton reconstruction efficiency and bin migration, where events corresponding to bin j at particle level appear in a different bin \(i\ne j\) at reconstruction level. The values of \(G^i_{e\mu }\) in simulation are typically in the range 0.5–0.6, with some dependence on lepton kinematics due to the varying reconstruction efficiencies with lepton \(|\eta |\) and \(p_{\text {T}}\), and the effect of isolation requirements when the leptons are close together in the detector.

The efficiency \(\epsilon ^i_{b}\) represents the combined probability for a jet from the quark q in the \(t\rightarrow Wq\) decay to fall within the detector acceptance, be reconstructed as a jet with \(p_{\text {T}} >25\) GeV and be tagged as a b-jet. Although this quark is almost always a b-quark, \(\epsilon ^i_{b}\) also accounts for the 0.2% of top quarks that decay to Ws or Wd. If the kinematics of the two b quarks produced in the top quark decays are uncorrelated, the probability to tag both is given by \({\epsilon ^i_{bb}}=({\epsilon ^i_{b}})^2\). In practice, small correlations are present, for example due to kinematic correlations between the b-jets from the top quark decays, or extra \(b\bar{b}\) or \(c\bar{c}\) pairs produced in association with the \(t\bar{t}\) system [13]. Their effects are corrected via the tagging correlation coefficient \({C^i_b}={\epsilon ^i_{bb}}/({\epsilon ^i_{b}})^2\), whose values are taken from \(t\bar{t}\) simulation. They depend slightly on the bin i of the dilepton system but are always within 1–2% of unity, even for the bins at the edges of the differential distributions. The correlation \(C^i_b\) also corrects for the small effects on \(N^i_1\), \(N^i_2\) and \(\epsilon ^i_{b}\) of the small fraction of \(t\bar{t}\) events which have additional b quarks produced in association with the \(t\bar{t}\) system, and the even smaller effects from mistagged light quark, charm or gluon jets in \(t\bar{t}\) events. This formalism involving \(\epsilon ^i_{b}\) and \(C^i_b\) allows the fraction of top quarks where the jet was not reconstructed to be inferred from the counts \(N^i_1\) and \(N^i_2\), minimising the exposure to systematic uncertainties from jet measurements and b-tagging, and allowing the fiducial cross-sections \(\sigma ^i_{t\bar{t}}\) to be defined with no requirements on the jets in the final state.

Backgrounds from sources other than \(t\bar{t} \rightarrow e\mu \nu \bar{\nu }b\bar{b} \) events also contribute to the counts \(N^i_1\) and \(N^i_2\), and are represented by the terms \(N_1^{i,\mathrm {bkg}}\) and \(N_2^{i,\mathrm {bkg}}\) in Eq. (1). These contributions were evaluated using a combination of simulation- and data-based methods as discussed in Sect. 4.2 below.

The tagging equations were solved numerically in each bin i of each differential distribution separately. The bin ranges for each distribution were chosen according to the experimental resolution, minimising the bin-to-bin migration by keeping the bin purities (the fractions of reconstructed events in bin i that originate from events which are also in bin i at particle level) above about 0.9. The resolution on the reconstructed kinematic quantities is dominated by the electron energy and muon momentum measurements, and the purities for the distributions which depend mainly on angular variables are higher, around 0.96 for \(|y^{e\mu }|\) and 0.99 for \(|\eta ^{\ell }|\) and \(\Delta \phi ^{e\mu }\). For these distributions, the bin ranges were chosen so as to give about ten bins for each distribution. The bin range choices for all distributions can be seen in Tables 3, 4, 5 and 6 in Sect. 6, and the last bin of the \(p_{\mathrm T}^{\ell }\), \(p_{\mathrm T}^{e\mu }\), \(m^{e\mu }\), \(p_{\mathrm T}^{e}+p_{\mathrm T}^{\mu }\) and \(E^{e}+E^{\mu }\) distributions includes overflow events falling above the last bin boundary, indicated by the ‘+’ sign after the upper bin limit.

The normalised fiducial differential cross-section distributions \(\varsigma ^i_{t\bar{t}}\) were calculated from the absolute cross-sections \(\sigma ^i_{t\bar{t}}\) determined from Eq. (1) as follows:
$$\begin{aligned} {\varsigma ^i_{t\bar{t}}}= \frac{{\sigma ^i_{t\bar{t}}}}{\Sigma _j\ {\sigma ^j_{t\bar{t}}}} = \frac{{\sigma ^i_{t\bar{t}}}}{{\sigma ^{t\bar{t}}_{\mathrm {fid}}}}, \end{aligned}$$
(2)
where \(\sigma ^{t\bar{t}}_{\mathrm {fid}}\) is the total cross-section summed over all bins of the fiducial region. The \(\varsigma ^i_{t\bar{t}}\) values are divided by the bin widths \(W_i\), to produce the cross-sections differential in the variable x (\(x={p_{\mathrm T}^{\ell }}\), \(|\eta ^{\ell }|\), etc.):
$$\begin{aligned} \frac{1}{\sigma }\left( \frac{{\mathrm d}\sigma }{{\mathrm d}x}\right) _i = \frac{{\varsigma ^i_{t\bar{t}}}}{W_i}\ . \end{aligned}$$
The normalisation condition in Eq. (2) induces a statistical correlation between the normalised measurements in each bin. The absolute dilepton cross-section measurements are not statistically correlated between bins, but kinematic correlations between the electron and muon in each event induce small statistical correlations between bins of the absolute single lepton \(p_{\mathrm T}^{\ell }\) and \(|\eta ^{\ell }|\) distributions, as discussed in Sect. 4.3 below.
The measured cross-sections include contributions where one or both leptons are produced via leptonic tau decays (\(t\rightarrow W\rightarrow \tau \rightarrow e/\mu \)), but the fixed-order predictions discussed in Sect. 6.3 only include the direct decays \(t\rightarrow W\rightarrow e/\mu \). To allow comparison with such predictions, a second set of cross-section results were derived with a bin-by-bin multiplicative correction \(f^i_{\bar{\tau }}\) to remove the \(\tau \) contributions:
$$\begin{aligned} {\sigma ^i_{t\bar{t}}}\,(\text{ no-- }\tau ) = {f^i_{\bar{\tau }}}{\sigma ^i_{t\bar{t}}}\ , \end{aligned}$$
(3)
and similarly for the normalised cross-sections \({\varsigma ^i_{t\bar{t}}}\,(\text{ no- }\tau )\). The corrections \(f^i_{\bar{\tau }}\) were evaluated from the baseline Powheg + Pythia6 \(t\bar{t}\) simulation and are typically close to 0.9, decreasing to 0.8–0.85 at low lepton \(p_{\text {T}}\).

4.2 Background estimates

The Wt single top and diboson backgrounds were estimated from simulation using the samples discussed in Sect. 2, whilst the Z+jets background (with \(Z\rightarrow \tau \tau \rightarrow e\mu 4\nu \)) and the contribution from events with one real and one misidentified lepton were estimated using both simulation and data as discussed below. The backgrounds in both the one and two b-tagged samples are dominated by Wt (see Table 2). The total background fraction (i.e. the predicted fraction of events in each bin which do not come from \(t\bar{t}\) with two real prompt leptons) varies significantly as a function of some of the differential variables, as shown in Fig. 3. This variation is taken into account by estimating the background contributions \(N_1^{i,\mathrm {bkg}}\) and \(N_2^{i,\mathrm {bkg}}\) separately in each bin of each differential distribution.
Fig. 3

Estimated background fractions in the one and two b-tagged samples as functions of each lepton and dilepton differential variable, estimated from simulation alone. The error bars correspond to the statistical uncertainties of the simulation samples, and are often smaller than the marker size

The production cross-sections for Z bosons accompanied by heavy-flavour jets are subject to large theoretical uncertainties. The background predictions from Alpgen + Pythia6 in each bin of each distribution were therefore normalised from data, by multiplying them by constant scale factors of \(1.4\pm 0.2\) for the one b-tagged jet sample and \(1.1\pm 0.3\) for the two b-tagged jet sample. These scale factors were derived from the comparison of data and simulated event yields for \(Z\rightarrow ee\) and \(Z\rightarrow \mu \mu \) plus one or two b-tagged jets, inclusively for all lepton pairs passing the kinematic selections for electrons and muons [13]. The uncertainties are dominated by the dependence of the scale factors on lepton kinematics, investigated by studying their variation with Z-boson \(p_{\text {T}}\), reconstructed from the ee or \(\mu \mu \) system.

The background from events with one real and one misidentified lepton was estimated using a combination of data and simulation in control regions with an electron and muon of the same charge [13]. Simulation studies showed that the samples with a same-sign \(e\mu \) pair and one or two b-tagged jets are dominated by events with a misidentified lepton, with rates and kinematic distributions similar to those in the opposite-sign sample. The distributions of the dilepton kinematic variables for same-sign events with at least one b-tagged jet in data are shown in Fig. 4, and compared with the predictions from simulation. The expected contributions are shown separately for events with two prompt leptons, events where the electron candidate originates from a converted photon radiated from an electron produced in a top quark decay, events with a converted photon from other sources, and events where the electron or muon originates from the decay of a bottom or charm hadron. The analogous distributions for the electron and muon \(p_{\text {T}}\) and \(|\eta |\) are shown in Ref. [13]. In general, the simulation models the rates and kinematic distributions of the same-sign events well. The modelling of misidentified leptons was further tested in control samples where either the electron or muon isolation requirements were relaxed in order to enhance the contributions from heavy-flavour decays, and similar levels of agreement were observed.

The contributions \(N_j^{i,\mathrm {mis{-}id}}\) of events with misidentified leptons to the opposite-sign samples with \(j=1\), 2 b-tagged jets were estimated in each bin i of each distribution using
$$\begin{aligned} \begin{array}{rll} {N_j^{i,\mathrm {mis{-}id}}}&{} = &{} R^i_j ({N_j^{i,\mathrm {data,SS}}}-{N_j^{i,\mathrm {prompt,SS}}}) , \\ *[1mm] R^i_j &{} = &{} \frac{{N_j^{i,\mathrm {mis{-}id,OS}}}}{{N_j^{i,\mathrm {mis{-}id,SS}}}}, \end{array} \end{aligned}$$
(4)
where \(N_j^{i,\mathrm {data,SS}}\) is the number of observed same-sign events in bin i with j b-tagged jets, \(N_j^{i,\mathrm {prompt,SS}}\) is the estimated number of events in this bin with two prompt leptons, and \(R^i_j\) is the ratio of the number of opposite- to same-sign events with misidentified leptons in bin i with j b-tagged jets. This formalism uses the observed data same-sign event rate in each bin to predict the corresponding opposite-sign contribution from misidentified leptons. It relies on simulation to predict the ratios of opposite- to same-sign rates and the prompt same-sign contribution, but not the absolute normalisation of misidentified leptons. The prompt-lepton contribution in Eq. (4) comes mainly from semileptonic \(t\bar{t}\) events with an additional W or Z boson, diboson events with two same-sign leptons, and \(t\bar{t} \rightarrow e\mu \nu \bar{\nu }b\bar{b} \) events where the electron charge was misreconstructed. These components were evaluated directly from simulation in each bin (ij), and an uncertainty of ± 50% was assigned [13]. The values of \(R^i_j\) were taken from simulation, separately for each differential distribution and \(j=1\) and 2 b-tagged jets, and averaged over several consecutive bins i in order to reduce statistical fluctuations. The values of \(R^i_1\) range from 0.8 to 1.5, and \(R^i_2\) from 1.2 to 2.0, as the predicted background composition changes across the kinematic distributions. As in Ref. [13], uncertainties of ± 0.25 and ± 0.5 were assigned to \(R^i_1\) and \(R^i_2\), based on the variation of \(R^i_j\) for different components of the misidentified lepton background, and taken to be correlated across all bins (ij).
Fig. 4

Distributions of a the dilepton \(p_{\mathrm T}^{e\mu }\), b invariant mass \(m^{e\mu }\), c rapidity \(|y^{e\mu }|\), d azimuthal angle difference \(\Delta \phi ^{e\mu }\), e lepton \(p_{\text {T}}\) sum \(p_{\mathrm T}^{e}+p_{\mathrm T}^{\mu }\) and f lepton energy sum \(E^{e}+E^{\mu }\), in events with a same-sign \(e\mu \) pair and at least one b-tagged jet. The simulation prediction is normalised to the same integrated luminosity as the data, and broken down into contributions where both leptons are prompt, or one is a misidentified lepton from a photon conversion originating from a top quark decay or from background, or from heavy-flavour decay. In the \(p_{\mathrm T}^{e\mu }\), \(m^{e\mu }\), \(p_{\mathrm T}^{e}+p_{\mathrm T}^{\mu }\) and \(E^{e}+E^{\mu }\) distributions, the last bin includes the overflows

Fig. 5

Results of pseudo-experiment studies on simulated events for the extraction of the normalised differential cross-section distributions for a \(p_{\mathrm T}^{\ell }\), b \(p_{\mathrm T}^{e\mu }\), c \(|\eta ^{\ell }|\) and d \(|y^{e\mu }|\), shown as relative deviations \((\sigma -\sigma _{\mathrm {ref}})/\sigma _{\mathrm {ref}} \) from the reference cross-section values in the baseline Powheg+Pythia6 CT10 sample with \({m_t}=172.5\) GeV. The black points show the mean deviations from the reference when fitting pseudo-data samples generated with the baseline simulation sample, with error bars indicating the uncertainties due to the limited number of simulated events. The cyan bands indicate the expected statistical uncertainties for a single sample corresponding to the data integrated luminosity. The open red points show the mean deviations from the reference values when fitting pseudo-experiments generated from alternative simulation samples with \({m_t}=165\) GeV (a, b) or with the HERAPDF 1.5 PDF (c, d), with error bars due to the limited size of these alternative samples. The red dotted lines show the true deviations from the reference in the alternative samples

4.3 Validation of the analysis procedure

The method for the differential cross-section determination was tested on simulated events in order to check for biases and determine the expected statistical uncertainties. Pseudo-data samples corresponding to the data integrated luminosity were produced by varying the event counts \(N^i_1\) and \(N^i_2\) in each bin i independently, according to Poisson distributions with mean values predicted from a chosen \(t\bar{t}\) simulation sample plus non-\(t\bar{t}\) backgrounds. The tagging equations Eq. (1) were then solved for each pseudo-experiment using the values of \(G^i_{e\mu }\), \(C^i_b\), \(N_1^{i,\mathrm {bkg}}\) and \(N_2^{i,\mathrm {bkg}}\) calculated with the baseline simulation samples. An initial set of 1000 pseudo-experiments was performed using the baseline simulation sample as a reference, and the mean and RMS width of the deviations of the result in each bin from the reference values were used to validate the analysis procedure. The black points in Fig. 5 show the mean deviation of the results (averaged over all pseudo-experiments) for four of the measured normalised distributions, with error bars corresponding to the uncertainty in the mean due to the finite size of the simulation samples (about 17 times the data integrated luminosity). The residual biases of the mean deviations away from the reference are compatible with zero and in all cases much smaller than the expected statistical uncertainties in data, measured by the RMS widths and shown by the cyan bands. Similar results were obtained for the other normalised differential cross-section distributions, and for the absolute distributions. The pull distributions (i.e. the distributions of deviations divided by the estimated statistical uncertainty from each pseudo-experiment) were also found to have widths within a few percent of unity. The \(\chi ^2\) values for the compatibility of each measured distribution with the reference were also calculated for each pseudo-experiment and the distribution of the corresponding p-values across all pseudo-experiments was found to be uniform between zero and one. These tests confirm that the analysis procedure is unbiased and correctly estimates the statistical uncertainties in each bin of each distribution.

Additional pseudo-experiments were performed to test the ability of the analysis procedure to reconstruct distributions different from the reference, taking the values of \(G^i_{e\mu }\), \(C^i_b\), \(N_1^{i,\mathrm {bkg}}\) and \(N_2^{i,\mathrm {bkg}}\) from the baseline samples. Tests were conducted using simulated Powheg + Pythia6 and MC@NLO + Herwig \(t\bar{t}\) samples with different top mass values, a Powheg + Pythia6 sample generated using the HERAPDF 1.5 [84, 85] PDF set instead of CT10, and a Powheg + Pythia6 sample reweighted to reproduce the top quark \(p_{\text {T}}\) distribution calculated at NNLO from Ref. [25]. In all cases, the analysis procedure recovered the true distributions from the alternative samples within the statistical precision of the test, demonstrating the adequacy of the bin-by-bin correction procedure without the need for iteration or a more sophisticated matrix-based unfolding technique. Some examples are shown by the red points and dotted lines in Fig. 5, for an alternative sample with \({m_t}=165\) GeV for \(p_{\mathrm T}^{\ell }\) and \(p_{\mathrm T}^{e\mu }\), and for HERAPDF 1.5 for \(|\eta ^{\ell }|\) and \(|y^{e\mu }|\), both simulation samples having about twice the statistics of the data. These figures also demonstrate the sensitivities of some of the measured distributions to \(m_t\) and different PDFs.

For the single-lepton distributions \(p_{\mathrm T}^{\ell }\) and \(|\eta ^{\ell }|\), which have two entries per event, the formalism of Eq. (1) and the pseudo-experiments generated by fluctuating each bin independently do not take into account correlations between the kinematics of the electron and muon in each event. This effect was checked by generating pseudo-data samples corresponding to the data integrated luminosity from individual simulated events, taken at random from a large \(t\bar{t}\) sample combining both full and fast simulation and corresponding to about 70 times the data integrated luminosity. The effect of neglecting the electron-muon correlations within an event was found to correspond to at most a 2% fractional overestimate of the absolute and 2% fractional underestimate of the normalised cross-section uncertainties. Hence, no corresponding corrections to the statistical uncertainties were made.

5 Systematic uncertainties

Systematic uncertainties in the measured cross-sections arise from uncertainties in the values of the input quantities \(G^i_{e\mu }\), \(C^i_b\), \(N_1^{i,\mathrm {bkg}}\), \(N_2^{i,\mathrm {bkg}}\) and L used in Eq. (1). Each source of systematic uncertainty was evaluated by coherently changing the values of all relevant input quantities and re-solving Eq. (1), thus taking into account correlations of the uncertainties in e.g. \(G^i_{e\mu }\) and \(C^i_b\). The uncertainties are divided into five groups (\(t\bar{t}\) modelling, leptons, jets/b-tagging, background and luminosity/beam energy uncertainties) and are discussed in Sects. 5.15.5. The resulting relative uncertainties in each measured differential cross-section value are shown in the results Tables 3, 4, 5 and 6, and the grouped systematic uncertainties for the normalised differential cross-sections are shown in Fig. 6, together with the statistical and total uncertainties.

Fig. 6

Relative uncertainties on the measured normalised differential cross-sections coming from data statistics, \(t\bar{t}\) modelling, leptons, jets and background, as a function of each lepton or dilepton differential variable. The total uncertainty is shown by the black lines, and also includes small contributions from the integrated luminosity and LHC beam energy uncertainties

5.1 \(t\bar{t}\) modelling

The uncertainties in \(G^i_{e\mu }\) and \(C^i_b\) (and \(f^i_{\bar{\tau }}\) for the \(\tau \)-corrected cross-sections) were evaluated using the various alternative \(t\bar{t}\) simulation samples detailed in Sect. 2.
  • \({\varvec{t}}\bar{{\varvec{t}}}\) generator: Event generator uncertainties were evaluated by comparing the baseline Powheg + Pythia6 \(t\bar{t}\) sample (with \({h_{\mathrm {damp}}}={m_t}\)) with alternative samples generated with MC@NLO interfaced to Herwig (thus changing both the NLO hard-scattering event generator and the parton shower, hadronisation and underlying event model), and with the LO multi-leg event generator Alpgen, also interfaced to Herwig. The bin-by-bin shifts in \(G^i_{e\mu }\) and \(C^i_b\) were fitted with polynomial functions in order to reduce statistical fluctuations caused by the limited size of the simulated samples, and the larger of the differences between the baseline and the two alternative samples was taken in each bin to define the generator uncertainty. As also found in the inclusive cross-section analysis [13], a substantial part of the differences in \(G^i_{e\mu }\) in the various samples arises from differences in the hadronic activity close to the leptons, which affects the efficiency of the lepton isolation requirements. These efficiencies were therefore measured in situ in \(t\bar{t}\) events selected in data as discussed in Sect. 5.2 below, and the simulation uncertainties on \(G^i_{e\mu }\) evaluated by considering the lepton reconstruction, identification and lepton-jet overlap requirements only. The resulting uncertainties on \(G^i_{e\mu }\) are typically 0.5–1% in most regions of the phase space, varying only slightly as a function of the lepton and dilepton kinematics. The same procedure was used to evaluate uncertainties in \(C^i_b\), and the predictions of the three simulation samples were found to agree at the 0.5–1% level, giving similar predictions for the variations of \(C^i_b\) across the bins of the various measured distributions. Alternative \(t\bar{t}\) samples generated with Powheg + Pythia6 and Powheg + Herwig (both with \({h_{\mathrm {damp}}}=\infty \)) were also considered, but the resulting differences in \(G^i_{e\mu }\) and \(C^i_b\) were found to be significantly less than those from the comparisons with MC@NLO + Herwig and thus no additional uncertainty was assigned. Variations in the predictions of \(f^i_{\bar{\tau }}\) from the three \(t\bar{t}\) samples were found to be at the 0.2% level, and were also taken into account for the \(\tau \)-corrected cross-section results.

  • Initial/final-state radiation: The effects on \(G^i_{e\mu }\)  \(C^i_b\) and \(f^i_{\bar{\tau }}\) of uncertainties in the modelling of additional radiation in \(t\bar{t}\) events were assessed as half the difference between Powheg + Pythia6 samples tuned to span the uncertainties in jet activity measured in \(\sqrt{s}=7\) TeV ATLAS data [26, 55, 64], as discussed in Sect. 2. The uncertainties were taken as half the difference between the upward and downward variations, and were substantially reduced by measuring the lepton isolation efficiencies from data, in the same way as for the \(t\bar{t}\) generator uncertainties discussed above.

  • Parton distribution functions: The uncertainties in \(G^i_{e\mu }\) due to limited knowledge of the proton PDFs were evaluated using the error sets of the CT10 [10], MSTW 2008 68% CL [8] and NNPDF 2.3 [12] NLO PDF sets, by reweighting the MC@NLO + Herwig \(t\bar{t}\) sample based on the x and \(Q^2\) values of the partons participating in the hard scattering in each event. The final uncertainty in each bin was calculated as half the envelope encompassing the predictions from all three PDF sets and their associated uncertainties, following the PDF4LHC prescription [7]. The resulting uncertainties on \(G^i_{e\mu }\) are typically around 0.3% except at the high ends of the distributions, and were taken to be fully correlated across all bins.

  • Top quark mass: The values of \(G^i_{e\mu }\) and the predicted levels of Wt background depend weakly on the assumed value of \(m_t\). These effects were evaluated with \(t\bar{t}\) and Wt samples simulated with \(m_t\) values of 170 and 175 GeV, and scaled to a nominal \(\pm 1\) GeV mass variation. The resulting effects are at the level of 0.1–0.2% on \(G^i_{e\mu }\), and are partially cancelled by the variations in the Wt background, whose cross-section decreases with increasing \(m_t\). The residual uncertainties are typically around 0.1% for the absolute cross-sections except at the extreme ends of the distributions, and smaller for the normalised cross-sections.

The total \(t\bar{t}\) modelling uncertainties in the normalised differential cross-sections also include the small uncertainties on \(G^i_{e\mu }\) and \(C^i_b\) from the limited size of the simulated \(t\bar{t}\) samples, and are shown by the green lines in Fig. 6. They are typically dominated by the \(t\bar{t}\) event generator comparisons.

5.2 Lepton identification and measurement

Uncertainties in the modelling of the detector response to electrons and muons affect both \(G^i_{e\mu }\) and the background estimates, with the largest uncertainties in the cross-section measurements coming via the former.
  • Lepton identification: The modelling of the electron and muon identification efficiencies, and the rate of electron charge misidentification, were studied using \(Z\rightarrow ee/\mu \mu \), \(J/\psi \rightarrow ee/\mu \mu \) and \(W\rightarrow e\nu \) events in data and simulation [76, 77], taking into account the systematic correlations across different regions of the lepton \(p_{\text {T}}\) and \(\eta \) spectrum. The uncertainties in \(G^i_{e\mu }\) are typically below 0.5% for electron and below 0.3% for muon efficiencies, with significant cancellations in the normalised differential cross-sections.

  • Lepton scales and resolution: The electron and muon energy/momentum scales and resolutions were determined using \(Z\rightarrow ee/\mu \mu \), \(Z\rightarrow (ee/\mu \mu )\gamma \), \(J/\psi \rightarrow ee/\mu \mu \) and \(\Upsilon \rightarrow \mu \mu \) decays [77, 86]. The largest uncertainty comes from the limited knowledge of the electron energy scale, which gives uncertainties varying from 0.2% to over 2% for the bins involving the highest energy electrons. The muon momentum scale uncertainties are small in comparison.

  • Lepton isolation: Building on the studies described in Ref. [13], the efficiencies of the lepton isolation requirements were measured in data, using the fractions of selected opposite-sign \(e\mu \) events with at least one b-tagged jet where either the electron or the muon fails the isolation requirement. After correcting for the contamination from events with a misidentified lepton, these fractions give the inefficiency of the isolation requirements on signal \(t\bar{t}\) events. The misidentified lepton backgrounds were measured both by using the same-sign \(e\mu \) control samples discussed in Sect. 4.2 above, and by using the distributions of lepton impact parameter significance \(|d_0|/\sigma _{d_0}\), where \(d_0\) is the distance of closest approach of the lepton track to the event primary vertex in the transverse plane, and \(\sigma _{d_0}\) its uncertainty. The isolation inefficiencies were measured as functions of lepton \(p_{\text {T}}\) separately for the barrel (\(|\eta |<1.5\)) and endcap regions of the detector. Consistent results were obtained using both misidentified lepton estimation methods, and showed that the baseline Powheg + Pythia6 \(t\bar{t}\) simulation sample overestimates the efficiencies of the lepton isolation requirements by up to 1% for electrons with \(p_{\text {T}}\) in the range 40–80 GeV, and by up to 2% for muons at low \(p_{\text {T}}\), decreasing rapidly to less than 0.5% for 40 GeV. The values of \(G^i_{e\mu }\) from the baseline simulation were corrected for these \(p_{\text {T}}\)-dependent shifts using a reweighting technique. The corresponding uncertainties are dominated by those on the misidentified lepton subtraction (including a comparison of the same-sign and \(|d_0|/\sigma _{d_0}\)-based methods) and amount to typically 0.5–1% for electrons and 0.2–0.5% for muons. The effect on the normalised cross-sections is about half that on the absolute measurements, taking into account systematic correlations across lepton \(p_{\text {T}}\) and \(|\eta |\) bins.

  • Lepton trigger: The efficiencies of the single-lepton triggers were measured in data using \(Z\rightarrow ee/\mu \mu \) events [87]. Since only one lepton trigger was required to accept the \(e\mu \) event, the trigger efficiency with respect to the offline event selection is about 99%, with a residual uncertainty of less than 0.2%.

The lepton-related uncertainties are shown by the blue dot-dashed lines in Fig. 6, and the largest uncertainties typically come from the electron energy scale and electron isolation uncertainties.

5.3 Jet measurement and b-tagging

Uncertainties in the selection and b-tagging of jets affect the background estimates \(N_1^{i,\mathrm {bkg}}\) and \(N_2^{i,\mathrm {bkg}}\), and to a lesser extent, the correlation \(C^i_b\). The jet uncertainties also have a very small effect on \(G^i_{e\mu }\), through the requirement that leptons be separated from selected jets by \(\Delta R>0.4\).
  • Jet-related uncertainties: The jet energy scale was varied according to the uncertainties derived from simulation and in situ calibration measurements [81], using a model with 22 orthogonal uncertainty components describing the evolution with jet \(p_{\text {T}}\) and \(|\eta |\). The effects of residual uncertainties in the modelling of the jet energy resolution [88] were assessed by smearing jet energies in simulation. The jet reconstruction efficiency was measured in data using track-based jets, and the effect of residual uncertainties assessed in simulation by randomly discarding jets. The modelling of the pileup rejection requirement applied to jets was studied using \(Z\rightarrow ee/\mu \mu \)+jets events [82].

  • \({\varvec{b}}\) -tagging uncertainties: The efficiencies for b-tagging jets in \(t\bar{t}\) signal events were extracted from the data, but simulation was used to predict the numbers of b-tagged jets in the Wt single top and diboson backgrounds. The corresponding uncertainties were assessed using studies of b-jets containing muons, charm jets containing \(D^{*+}\) mesons and inclusive jet events [83].

The jet- and b-tagging-related uncertainties are shown by the purple lines on Fig. 6, and are typically dominated by the effect of the jet energy scale on the level of Wt background.

5.4 Background modelling

As well as the detector-related uncertainties discussed above, the background estimates depend on uncertainties in modelling the Wt and diboson processes taken from simulation, and uncertainties in the procedures used for estimating the Z+jets and misidentified lepton backgrounds from data.
  • Single top modelling: Uncertainties in the modelling of the Wt background were assessed by comparing the predictions from the baseline Powheg + Pythia6 sample with those from MC@NLO + Herwig, and from two samples generated with AcerMC + Pythia6 utilising different tunes to vary the amount of additional radiation, in all cases normalising the total production cross-section to the approximate NNLO prediction based on Ref. [67]. The uncertainty in this prediction was evaluated to be 6.8%. The Wt background with two b-tagged jets is sensitive to the production of Wt with an additional b-jet, an NLO contribution which interferes with the \(t\bar{t}\) final state. The corresponding uncertainty was assessed by comparing the predictions of Powheg + Pythia6 with the diagram removal and diagram subtraction schemes for handling this interference [65, 66]. The latter predicts up to 25% less Wt background in the one b-tagged and 60% less in the two b-tagged channels at the extreme high ends of the lepton \(p_{\text {T}}\) and dilepton \(p_{\mathrm T}^{e\mu }\), \(m^{e\mu }\), \(p_{\mathrm T}^{e}+p_{\mathrm T}^{\mu }\) and \(E^{e}+E^{\mu }\) distributions, but only 1–2% and 20% differences for one and two b-tagged Wt events across the \(|\eta ^{\ell }|\), \(|y^{e\mu }|\) and \(\Delta \phi ^{e\mu }\) distributions, similar to the differences seen for the inclusive analysis [13]. The uncertainties due to the limited size of the Wt simulation samples are negligible in comparison to the modelling uncertainties.

  • Diboson modelling: The uncertainties in modelling the diboson background events (mainly WW) with one and two additional b-tagged jets were assessed by comparing the predictions from Alpgen + Herwig with those of Sherpa 1.4.3 [73] including the effects of massive b and c quarks. The resulting uncertainties in the diboson background are typically in the range 20–30%, substantially larger than the differences between recent predictions for the inclusive diboson cross-sections at NNLO in QCD [89] and the NLO predictions from MCFM used to normalise the simulated samples. The background from SM Higgs production with \(H\rightarrow WW\) and \(H\rightarrow \tau \tau \) is smaller than the uncertainties assigned for diboson modelling, and was neglected.

  • Z+jets extrapolation: The backgrounds from \(Z\rightarrow \tau \tau \rightarrow e\mu \) accompanied by one or two b-tagged jets were extrapolated from the analogous \(Z\rightarrow ee/\mu \mu \) event rates, with uncertainties of 20% for one and 30% for two additional b-tagged jets, as discussed in Sect. 4.2.

  • Misidentified leptons: Uncertainties in the numbers of events with misidentified leptons arise from the statistical uncertainties in the corresponding same-sign samples, together with systematic uncertainties in the opposite-to-same-sign ratios \(R^i_j\) and the estimated contributions of prompt same-sign events. The total uncertainties in the measured cross-sections are typically 0.2–0.5%, except at the extreme ends of distributions where the same-sign data statistical uncertainties are larger.

The background uncertainties are shown by the solid red lines on Fig. 6, and are dominated by Wt modelling uncertainties, in particular from the Wt-\(t\bar{t}\) interference at the high ends of some distributions.

5.5 Luminosity and beam energy

Uncertainties in the integrated luminosity and LHC beam energy give rise to additional uncertainties in the differential cross-section results.
  • Luminosity: The uncertainty in the integrated luminosity is 1.9%, derived from beam-separation scans performed in November 2012 [90]. The corresponding uncertainty in the absolute cross-section measurements is slightly larger, typically about 2.1%, as the Wt and diboson backgrounds were evaluated from simulation, thus becoming sensitive to the assumed integrated luminosity. The sensitivity varies with the background fractions, leaving a residual uncertainty of typically less than 0.1% in the normalised cross-section results.

  • Beam energy: The LHC beam energy during the 2012 pp run was determined to be within 0.1% of the nominal value of 4 TeV per beam, based on the LHC magnetic model together with measurements of the revolution frequency difference of proton and lead-ion beams [91]. Following the approach used in Ref. [13] with an earlier less precise determination of the LHC beam energy [92], an additional uncertainty corresponding to the change in cross-sections for a 0.1% change in \(\sqrt{s}\) was applied to the final results, allowing them to be interpreted as measurements at exactly \(\sqrt{s}=8\) TeV. The changes in each differential cross-section bin were calculated by scaling the differences seen in Powheg + Pythia6 samples generated at \(\sqrt{s}=8\) TeV and \(\sqrt{s}=7\) TeV. The resulting values were cross-checked with an explicit NLO fixed-order calculation using Sherpa 2.1 [73], making use of the Applgrid framework [93] to reweight an \(\sqrt{s}=8\) TeV prediction so as to change the \(\sqrt{s}\) value by \(\pm 0.66\)% which was then rescaled to correspond to a \(\sqrt{s}\) change of 0.1%. The changes in the absolute cross-sections are in the range 0.2–0.4%, and largely cancel in the normalised cross-sections.

These uncertainties are not shown separately in Fig. 6, but are included in the total uncertainties shown by the black lines, and given in Tables 3, 4, 5 and 6.

6 Results

The absolute differential cross-sections were determined by solving Eq. (1) separately for each bin i of each lepton and dilepton differential distribution, taking the effects of systematic uncertainties into account as discussed in Sect. 5. The normalised differential cross-sections were determined from the absolute results using Eq. (2). The values of \(\epsilon ^i_{b}\), i.e. the product of jet acceptance, reconstruction and b-tagging probabilities in each bin, were determined to be in the range 0.5–0.6, in agreement with the simulation prediction for each bin. The results were found to be stable when changing the minimum jet \(p_{\text {T}}\) requirement from 25 GeV up to 55 GeV, and when using b-tagging working points corresponding to b-jet efficiencies of 60–80%. The electron and muon \(p_{\text {T}}\) and \(|\eta |\) distributions were also measured separately, instead of combining them into lepton distributions with two entries per event, and found to be compatible. The bin-by-bin comparison of the electron and muon \(p_{\text {T}}\) (\(|\eta |\)) distributions has a \(\chi ^2\) per degree of freedom of 10.9/9 (12.5/8), in both cases taking into account statistical and uncorrelated systematic uncertainties.
Table 3

Absolute and normalised differential cross-sections as functions of \(p_{\mathrm T}^{\ell }\) (top) and \(|\eta ^{\ell }|\) (bottom). The columns show the bin ranges, measured cross-section and total uncertainty, relative statistical uncertainty, relative systematic uncertainties in various categories (see text), total relative uncertainty, and differential cross-section corrected to remove contributions via \(W\rightarrow \tau \rightarrow e/\mu \) decays. Relative uncertainties smaller than 0.05% are indicated by ‘0.0’. The last bin includes overflows where indicated by the ‘+’ sign

Absolute bin (GeV)

\(\mathrm {d}\sigma /\mathrm {d}{p_{\mathrm T}^{\ell }}\) (fb/GeV)

Stat. (%)

\(t\bar{t}\) mod. (%)

Lept. (%)

Jet/b (%)

Bkg. (%)

\(L/E_\mathrm {b}\) (%)

Total (%)

\(\mathrm {d}\sigma /\mathrm {d}{p_{\mathrm T}^{\ell }}\) (no \(\tau \)) (fb/GeV)

25–30

\( 154.8\pm 5.7\)

1.6

1.3

1.8

0.8

1.2

2.1

3.7

\( 127.2\pm 4.8\)

30–40

\( 146.1\pm 4.9\)

1.1

1.2

1.5

0.8

1.0

2.1

3.3

\( 124.6\pm 4.2\)

40–50

\( 118.8\pm 3.7\)

1.2

1.1

1.0

1.0

0.9

2.1

3.1

\( 104.3\pm 3.3\)

50–60

\( 93.5\pm 2.9\)

1.4

1.0

1.0

0.8

0.9

2.1

3.1

\( 83.4\pm 2.6\)

60–80

\( 60.0\pm 1.8\)

1.2

0.9

0.9

0.6

0.9

2.1

3.0

\( 54.1\pm 1.6\)

80–100

\( 32.4\pm 1.1\)

1.6

0.8

1.1

1.4

1.1

2.1

3.5

\( 29.4\pm 1.0\)

100–120

\( 16.23\pm 0.64\)

2.3

0.9

1.1

1.1

1.5

2.2

3.9

\( 14.75\pm 0.58\)

120–150

\( 7.61\pm 0.35\)

2.7

1.1

1.4

1.5

1.9

2.2

4.6

\( 6.91\pm 0.32\)

150–200

\( 2.41\pm 0.15\)

3.9

1.6

1.7

1.6

3.2

2.2

6.2

\( 2.17\pm 0.13\)

200–300+

\( 0.49\pm 0.06\)

6.7

3.5

2.3

2.9

7.5

2.4

11.5

\( 0.44\pm 0.05\)

Normalised bin (GeV)

\(\frac{1}{\sigma }\mathrm {d}\sigma /\mathrm {d}{p_{\mathrm T}^{\ell }}\) (\(10^{-2}/\)GeV)

Stat. (%)

\(t\bar{t}\) mod. (%)

Lept. (%)

Jet/b (%)

Bkg. (%)

\(L/E_\mathrm {b}\) (%)

Total (%)

\(\frac{1}{\sigma }\mathrm {d}\sigma /\mathrm {d}{p_{\mathrm T}^{\ell }}\) (no \(\tau \)) (\(10^{-2}/\)GeV)

25–30

\( 2.235\pm 0.045\)

1.5

0.4

0.9

0.6

0.8

0.0

2.0

\( 2.090\pm 0.042\)

30–40

\( 2.108\pm 0.029\)

1.0

0.3

0.7

0.3

0.5

0.0

1.4

\( 2.048\pm 0.029\)

40–50

\( 1.714\pm 0.023\)

1.1

0.2

0.5

0.4

0.4

0.0

1.3

\( 1.714\pm 0.023\)

50–60

\( 1.350\pm 0.019\)

1.3

0.2

0.4

0.3

0.3

0.0

1.4

\( 1.370\pm 0.020\)

60–80

\( 0.866\pm 0.011\)

1.1

0.3

0.4

0.4

0.3

0.0

1.3

\( 0.890\pm 0.011\)

80–100

\( 0.4673\pm 0.0093\)

1.5

0.4

0.7

0.8

0.5

0.0

2.0

\( 0.4831\pm 0.0096\)

100–120

\( 0.2343\pm 0.0063\)

2.3

0.5

0.8

0.6

1.0

0.0

2.7

\( 0.2424\pm 0.0065\)

120–150

\( 0.1098\pm 0.0040\)

2.7

0.6

1.2

1.3

1.5

0.1

3.6

\( 0.1135\pm 0.0041\)

150–200

\( 0.0348\pm 0.0018\)

3.9

0.9

1.6

1.2

2.8

0.1

5.3

\( 0.0357\pm 0.0019\)

200–300+

\( 0.0070\pm 0.0007\)

6.7

2.7

2.3

2.3

7.2

0.3

10.7

\( 0.0072\pm 0.0008\)

Absolute bin (unit \(\eta \))

\(\mathrm {d}\sigma /\mathrm {d}{|\eta ^{\ell }|}\) (fb/unit \(\eta \))

Stat. (%)

\(t\bar{t}\) mod. (%)

Lept. (%)

Jet/b (%)

Bkg. (%)

\(L/E_\mathrm {b}\) (%)

Total (%)

\(\mathrm {d}\sigma /\mathrm {d}{|\eta ^{\ell }|}\) (no \(\tau \)) (fb/unit \(\eta \))

0.00–0.25

\( 4590\pm 140\)

1.2

1.0

1.0

0.9

0.9

2.1

3.1

\( 4030\pm 130\)

0.25–0.50

\( 4440\pm 140\)

1.2

1.0

1.0

0.9

0.9

2.1

3.1

\( 3900\pm 120\)

0.50–0.75

\( 4230\pm 130\)

1.2

1.0

1.0

0.9

0.9

2.1

3.1

\( 3710\pm 120\)

0.75–1.00

\( 3660\pm 110\)

1.3

1.0

1.0

0.8

1.0

2.1

3.1

\( 3210\pm 100\)

1.00–1.25

\( 3100\pm 100\)

1.5

1.0

1.0

0.9

1.0

2.1

3.3

\( 2722\pm 89\)

1.25–1.50

\( 2470\pm 87\)

1.9

1.1

1.0

0.9

1.0

2.1

3.5

\( 2173\pm 77\)

1.50–1.75

\( 2035\pm 73\)

1.9

1.1

1.4

0.7

1.0

2.1

3.6

\( 1793\pm 65\)

1.75–2.00

\( 1431\pm 57\)

2.4

1.2

1.4

0.6

1.4

2.1

4.0

\( 1263\pm 50\)

2.00–2.50

\( 844\pm 34\)

2.2

1.3

1.4

0.7

1.4

2.1

4.0

\( 749\pm 30\)

Normalised bin (unit \(\eta \))

\(\frac{1}{\sigma }\mathrm {d}\sigma /\mathrm {d}{|\eta ^{\ell }|}\) (\(10^{-1}/\)unit \(\eta \))

Stat. (%)

\(t\bar{t}\) mod. (%)

Lept. (%)

Jet/b (%)

Bkg. (%)

\(L/E_\mathrm {b}\) (%)

Total (%)

\(\frac{1}{\sigma }\mathrm {d}\sigma /\mathrm {d}{|\eta ^{\ell }|}\) (no \(\tau \)) (\(10^{-1}/\)unit \(\eta \))

0.00–0.25

\( 6.646\pm 0.083\)

1.1

0.4

0.2

0.1

0.3

0.0

1.2

\( 6.632\pm 0.083\)

0.25–0.50

\( 6.428\pm 0.076\)

1.1

0.3

0.2

0.1

0.2

0.0

1.2

\( 6.416\pm 0.076\)

0.50–0.75

\( 6.117\pm 0.074\)

1.1

0.2

0.2

0.1

0.2

0.0

1.2

\( 6.103\pm 0.074\)

0.75–1.00

\( 5.297\pm 0.070\)

1.3

0.2

0.2

0.2

0.2

0.0

1.3

\( 5.286\pm 0.070\)

1.00–1.25

\( 4.482\pm 0.066\)

1.4

0.3

0.2

0.2

0.3

0.0

1.5

\( 4.484\pm 0.066\)

1.25–1.50

\( 3.574\pm 0.068\)

1.8

0.4

0.2

0.2

0.3

0.0

1.9

\( 3.579\pm 0.068\)

1.50–1.75

\( 2.944\pm 0.060\)

1.9

0.5

0.6

0.2

0.4

0.0

2.0

\( 2.954\pm 0.061\)

1.75–2.00

\( 2.070\pm 0.054\)

2.3

0.6

0.6

0.4

0.8

0.0

2.6

\( 2.080\pm 0.054\)

2.00–2.50

\( 1.221\pm 0.031\)

2.1

0.7

0.6

0.4

1.0

0.0

2.5

\( 1.233\pm 0.031\)

Table 4

Absolute and normalised differential cross-sections as functions of \(p_{\mathrm T}^{e\mu }\) (top) and \(m^{e\mu }\) (bottom). The columns show the bin ranges, measured cross-section and total uncertainty, relative statistical uncertainty, relative systematic uncertainties in various categories (see text), total relative uncertainty, and differential cross-section corrected to remove contributions via \(W\rightarrow \tau \rightarrow e/\mu \) decays. Relative uncertainties smaller than 0.05% are indicated by ‘0.0’. The last bin includes overflows where indicated by the ‘+’ sign

Absolute bin (GeV)

\(\mathrm {d}\sigma /\mathrm {d}{p_{\mathrm T}^{e\mu }}\) (fb/GeV)

Stat. (%)

\(t\bar{t}\) mod. (%)

Lept. (%)

Jet/b (%)

Bkg. (%)

\(L/E_\mathrm {b}\