Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC Aaboud, M. Aguilar Saavedra, Juan Antonio Atlas Collaboration Top-quark Boson 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. Aset 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 ¯t and γ + jet and 36.7 fb−1 for the dijet event topologies. 2019-10-14T07:19:32Z 2019-10-14T07:19:32Z 2019-04-30 journal article Abraham, N. L., Allbrooke, B. M. M., Asquith, L., Cerri, A., Jones, S. D., Shaw, K., ... & Trovato, F. (2019). Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC. European Physical Journal C-Particles and Fields, 79(5), a375. http://hdl.handle.net/10481/57322 10.1140/epjc/s10052-019-6847-8 eng http://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España EUROPEAN PHYSICAL JOURNAL C