@Article{ATLASCollaborationAaboud_etal2019,
author="ATLAS Collaboration (Aaboud, M. et al
and Alvarez Piqueras, D.
and Aparisi Pozo, J. A.
and Bailey, A. J.
and Barranco Navarro, L.
and Cabrera Urban, S.
and Castillo, F. L.
and Castillo Gimenez, V.
and Cerda Alberich, L.
and Costa, M. J.
and Escobar, C.
and Estrada Pastor, O.
and Ferrer, A.
and Fiorini, L.
and Fullana Torregrosa, E.
and Fuster, J.
and Garcia, C.
and Garcia Navarro, J. E.
and Gonzalez de la Hoz, S.
and Gonzalvo Rodriguez, G. R.
and Higon-Rodriguez, E.
and Jimenez Pena, J.
and Lacasta, C.
and Lozano Bahilo, J. J.
and Madaffari, D.
and Mamuzic, J.
and Marti-Garcia, S.
and Melini, D.
and Mi{\~{n}}ano, M.
and Mitsou, V. A.
and Rodriguez Bosca, S.
and Rodriguez Rodriguez, D.
and Ruiz-Martinez, A.
and Salt, J.
and Santra, A.
and Soldevila, U.
and Sanchez, J.
and Valero, A.
and Valls Ferrer, J. A.
and Vos, M.",
title="Performance of top-quark and W-boson tagging with ATLAS in Run 2 of the LHC",
journal="European Physical Journal C",
year="2019",
publisher="Springer",
volume="79",
number="5",
pages="375--54pp",
abstract="The performance of identification algorithms (taggers) for hadronically decaying top quarks and W bosons in pp collisions at = 13TeV 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 36.1fb-1 for the tt and +jet and 36.7-1 for the dijet event topologies.",
optnote="WOS:000466407600007",
optnote="exported from refbase (https://references.ific.uv.es/refbase/show.php?record=4073), last updated on Wed, 17 Jul 2019 10:01:50 +0000",
issn="1434-6044",
doi="10.1140/epjc/s10052-019-6847-8",
opturl="https://arxiv.org/abs/1808.07858",
opturl="https://doi.org/10.1140/epjc/s10052-019-6847-8",
language="English"
}