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

Aaboud, M, Aad, G, Abbott, B, Abdinov, O, Abeloos, B, Abhayasinghe, DK, Abidi, SH, AbouZeid, OS, Abraham, NL, Abramowicz, H
et al (show 2911 more authors) (2019) Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC. EUROPEAN PHYSICAL JOURNAL C, 79 (5). 375-.

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The performance of taggers for hadronically decaying top quarks and $W$ bosons in $pp$ collisions at $\sqrt{s}$ = 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 $t\bar{t}$ and $\gamma+$jet and 36.7 fb$^{-1}$ for the dijet event topologies.

Item Type: Article
Additional Information: 79 pages in total, author list starting page 63, 39 figures, 6 tables, submitted to The European Physical Journal C. All figures including auxiliary figures are available at
Uncontrolled Keywords: hep-ex, hep-ex
Depositing User: Symplectic Admin
Date Deposited: 10 Sep 2018 15:24
Last Modified: 19 Jan 2023 01:20
DOI: 10.1140/epjc/s10052-019-6847-8
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