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

, ; Aaboud, M; Åkesson, Torsten LU ; Bocchetta, Simona LU ; Corrigan, Eric LU ; Doglioni, Caterina LU ; Gregersen, Kristian LU ; Brottmann Hansen, Eva LU ; Hedberg, Vincent LU and Jarlskog, Göran LU , et al. (2019) In European Physical Journal C 79(5).
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... (More)
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. © 2019, CERN for the benefit of the ATLAS collaboration. (Less)
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European Physical Journal C
volume
79
issue
5
publisher
Springer Berlin Heidelberg
external identifiers
  • scopus:85065123030
ISSN
1434-6044
DOI
10.1140/epjc/s10052-019-6847-8
language
English
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yes
id
c4e83bd9-baec-43cd-8aca-2652cf55fc07
date added to LUP
2019-05-14 15:08:14
date last changed
2019-06-16 05:15:20
@article{c4e83bd9-baec-43cd-8aca-2652cf55fc07,
  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. © 2019, CERN for the benefit of the ATLAS collaboration.},
  articleno    = {375},
  author       = {,  and Aaboud, M and Åkesson, Torsten and Bocchetta, Simona and Corrigan, Eric and Doglioni, Caterina and Gregersen, Kristian and Brottmann Hansen, Eva and Hedberg, Vincent and Jarlskog, Göran and Kalderon, Charles and Kellermann, Edgar and Konya, Balazs and Lytken, Else and Mankinen, Katja and Mjörnmark, Ulf and Mullier, Geoffrey and Pöttgen, Ruth and Poulsen, Trine and Smirnova, Oxana and Zwalinski, L},
  issn         = {1434-6044},
  language     = {eng},
  number       = {5},
  publisher    = {Springer Berlin Heidelberg},
  series       = {European Physical Journal C},
  title        = {Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC},
  url          = {http://dx.doi.org/10.1140/epjc/s10052-019-6847-8},
  volume       = {79},
  year         = {2019},
}