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

0521088 - FZÚ 2020 RIV DE eng J - Článek v odborném periodiku
Aaboud, M. - Aad, G. - Abbott, B. - Chudoba, Jiří - Hejbal, Jiří - Hladík, Ondřej - Jačka, Petr - Jakoubek, Tomáš - Kepka, Oldřich - Kroll, Jiří - Kupčo, Alexander - Lokajíček, Miloš - Lysák, Roman - Marčišovský, Michal - Mikeštíková, Marcela - Němeček, Stanislav - Penc, Ondřej - Šícho, Petr - Staroba, Pavel - Svatoš, Michal - Taševský, Marek … celkem 2921 autorů
Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC.
European Physical Journal C. Roč. 79, č. 5 (2019), s. 1-54, č. článku 375. ISSN 1434-6044. E-ISSN 1434-6052
Výzkumná infrastruktura: CERN-CZ - 90058
Institucionální podpora: RVO:68378271
Klíčová slova: ATLAS * CERN LHC Coll * deconstruction * shape analysis: jet * constituent * structure * shower * dijet * topology
Obor OECD: Particles and field physics
Impakt faktor: 4.389, rok: 2019
Způsob publikování: Open access

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.

Trvalý link: http://hdl.handle.net/11104/0305754