The European Physical Journal C > 2019 > 79 > 5 > 1-54
Performance of top-quark and $$\varvec{W}$$ W -boson tagging with ATLAS in Run 2 of the LHC
Source
Abstract
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at $$\sqrt{s}$$ 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$$^{-1}$$ -1 for the $$t\bar{t}$$ tt¯ and $$\gamma +\text {jet}$$ γ+jet and 36.7 fb$$^{-1}$$ -1 for the dijet event topologies.
Identifiers
journal ISSN : | 1434-6044 |
journal e-ISSN : | 1434-6052 |
DOI | 10.1140/epjc/s10052-019-6847-8 |