Standard

Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC. / The ATLAS collaboration ; Балдин, Евгений Михайлович; Бобровников, Виктор Сергеевич et al.

In: European Physical Journal C, Vol. 79, No. 5, 375, 01.05.2019.

Research output: Contribution to journal › Article › peer-review

Harvard

The ATLAS collaboration, Балдин, ЕМ, Бобровников, ВС, Харламов, АГ, Бузыкаев, АР, Харламов, АГ, Масленников, АЛ, Пелеганчук, СВ, Талышев, АА, Тихонов, ЮА & Bogdanchikov, AG 2019, 'Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC', European Physical Journal C, vol. 79, no. 5, 375. https://doi.org/10.1140/epjc/s10052-019-6847-8

APA

The ATLAS collaboration, Балдин, Е. М., Бобровников, В. С., Харламов, А. Г., Бузыкаев, А. Р., Харламов, А. Г., Масленников, А. Л., Пелеганчук, С. В., Талышев, А. А., Тихонов, Ю. А., & Bogdanchikov, A. G. (2019). Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC. European Physical Journal C, 79(5), [375]. https://doi.org/10.1140/epjc/s10052-019-6847-8

Vancouver

The ATLAS collaboration, Балдин ЕМ, Бобровников ВС, Харламов АГ, Бузыкаев АР, Харламов АГ et al. Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC. European Physical Journal C. 2019 May 1;79(5):375. doi: 10.1140/epjc/s10052-019-6847-8

Author

The ATLAS collaboration ; Балдин, Евгений Михайлович ; Бобровников, Виктор Сергеевич et al. / Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC. In: European Physical Journal C. 2019 ; Vol. 79, No. 5.

BibTeX

@article{17efe0f19b9249b0845384e65bb9592a,
title = "Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC",
abstract = " The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at s = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb - 1 for the tt¯ and γ+ jet and 36.7 fb - 1 for the dijet event topologies. ",
author = "{The ATLAS collaboration} and M. Aaboud and G. Aad and B. Abbott and O. Abdinov and B. Abeloos and Abhayasinghe, {D. K.} and Abidi, {S. H.} and AbouZeid, {O. S.} and Abraham, {N. L.} and H. Abramowicz and H. Abreu and Y. Abulaiti and Acharya, {B. S.} and S. Adachi and L. Adam and L. Adamczyk and J. Adelman and M. Adersberger and A. Adiguzel and T. Adye and Affolder, {A. A.} and Y. Afik and C. Agheorghiesei and Aguilar-Saavedra, {J. A.} and F. Ahmadov and G. Aielli and S. Akatsuka and {\AA}kesson, {T. P.A.} and E. Akilli and Akimov, {A. V.} and Alberghi, {G. L.} and J. Albert and P. Albicocco and Alconada Verzini, {M. J.} and S. Alderweireldt and M. Aleksa and Aleksandrov, {I. N.} and C. Alexa and T. Alexopoulos and M. Alhroob and B. Ali and G. Alimonti and Anisenkov, {A. V.} and Kazanin, {V. F.} and T. Kharlamova and Maximov, {D. A.} and P. Podberezko and Rezanova, {O. L.} and Soukharev, {A. M.} and V. Zhulanov and Балдин, {Евгений Михайлович} and Бобровников, {Виктор Сергеевич} and Харламов, {Алексей Георгиевич} and Бузыкаев, {Алексей Рафаилович} and Харламов, {Алексей Георгиевич} and Масленников, {Алексей Леонидович} and Пелеганчук, {Сергей Владимирович} and Талышев, {Алексей Александрович} and Тихонов, {Юрий Анатольевич} and Bogdanchikov, {A. G.}",
note = "Publisher Copyright: {\textcopyright} 2019, CERN for the benefit of the ATLAS collaboration.",
year = "2019",
month = may,
day = "1",
doi = "10.1140/epjc/s10052-019-6847-8",
language = "English",
volume = "79",
journal = "European Physical Journal C",
issn = "1434-6044",
publisher = "Springer Nature",
number = "5",

}

RIS

TY - JOUR

T1 - Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC

AU - The ATLAS collaboration

AU - Aaboud, M.

AU - Aad, G.

AU - Abbott, B.

AU - Abdinov, O.

AU - Abeloos, B.

AU - Abhayasinghe, D. K.

AU - Abidi, S. H.

AU - AbouZeid, O. S.

AU - Abraham, N. L.

AU - Abramowicz, H.

AU - Abreu, H.

AU - Abulaiti, Y.

AU - Acharya, B. S.

AU - Adachi, S.

AU - Adam, L.

AU - Adamczyk, L.

AU - Adelman, J.

AU - Adersberger, M.

AU - Adiguzel, A.

AU - Adye, T.

AU - Affolder, A. A.

AU - Afik, Y.

AU - Agheorghiesei, C.

AU - Aguilar-Saavedra, J. A.

AU - Ahmadov, F.

AU - Aielli, G.

AU - Akatsuka, S.

AU - Åkesson, T. P.A.

AU - Akilli, E.

AU - Akimov, A. V.

AU - Alberghi, G. L.

AU - Albert, J.

AU - Albicocco, P.

AU - Alconada Verzini, M. J.

AU - Alderweireldt, S.

AU - Aleksa, M.

AU - Aleksandrov, I. N.

AU - Alexa, C.

AU - Alexopoulos, T.

AU - Alhroob, M.

AU - Ali, B.

AU - Alimonti, G.

AU - Anisenkov, A. V.

AU - Kazanin, V. F.

AU - Kharlamova, T.

AU - Maximov, D. A.

AU - Podberezko, P.

AU - Rezanova, O. L.

AU - Soukharev, A. M.

AU - Zhulanov, V.

AU - Балдин, Евгений Михайлович

AU - Бобровников, Виктор Сергеевич

AU - Харламов, Алексей Георгиевич

AU - Бузыкаев, Алексей Рафаилович

AU - Харламов, Алексей Георгиевич

AU - Масленников, Алексей Леонидович

AU - Пелеганчук, Сергей Владимирович

AU - Талышев, Алексей Александрович

AU - Тихонов, Юрий Анатольевич

AU - Bogdanchikov, A. G.

N1 - Publisher Copyright: © 2019, CERN for the benefit of the ATLAS collaboration.

PY - 2019/5/1

Y1 - 2019/5/1

N2 - The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at s = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb - 1 for the tt¯ and γ+ jet and 36.7 fb - 1 for the dijet event topologies.

AB - The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at s = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb - 1 for the tt¯ and γ+ jet and 36.7 fb - 1 for the dijet event topologies.

UR - http://www.scopus.com/inward/record.url?scp=85065123030&partnerID=8YFLogxK

U2 - 10.1140/epjc/s10052-019-6847-8

DO - 10.1140/epjc/s10052-019-6847-8

M3 - Article

AN - SCOPUS:85065123030

VL - 79

JO - European Physical Journal C

JF - European Physical Journal C

SN - 1434-6044

IS - 5

M1 - 375

ER -

ID: 20156255