@Article{ATLASCollaborationAad_etal2023,
author="ATLAS Collaboration (Aad, G. et al
and Amos, K. R.
and Aparisi Pozo, J. A.
and Bailey, A. J.
and Bouchhar, N.
and Cabrera Urban, S.
and Cantero, J.
and Cardillo, F.
and Castillo Gimenez, V.
and Chitishvili, M.
and Costa, M. J.
and Didenko
and Escobar, C.
and Fiorini, L.
and Fullana Torregrosa, E.
and Fuster, J.
and Garcia, C.
and Garcia Navarro, J. E.
and Gomez Delegido, A. J.
and Gonzalez de la Hoz, S.
and Gonzalvo Rodriguez, G. R.
and Guerrero Rojas, J. G. R.
and Lacasta, C.
and Lozano Bahilo, J. J.
and Marti-Garcia, S.
and Martinez Agullo, P.
and Miralles Lopez, M.
and Mitsou, V. A.
and Monsonis Romero, L.
and Moreno Llacer, M.
and Munoz Perez, D.
and Navarro-Gonzalez, J.
and Poveda, J.
and Prades Iba{\~{n}}ez, A.
and Rubio Jimenez, A.
and Ruiz-Martinez, A.
and Sabatini, P.
and Salt, J.
and Sanchez Sebastian, V.
and Sayago Galvan, I.
and Senthilkumar, V.
and Soldevila, U.
and Sanchez, J.
and Torro Pastor, E.
and Valero, A.
and Valls Ferrer, J. A.
and Varriale, L.
and Villaplana Perez, M.
and Vos, M.",
title="ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset",
journal="European Physical Journal C",
year="2023",
publisher="Springer",
volume="83",
number="7",
pages="681 - 37pp",
abstract="The flavour-tagging algorithms developed by the AvTLAS Collaboration and used to analyse its dataset of root s = 13 TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77{\%} b-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model t (t) over bar events; similarly, at a c-jet identification efficiency of 30{\%}, a light-jet (b-jet) rejection factor of 70 (9) is obtained.",
optnote="WOS:001062397400001",
optnote="exported from refbase (https://references.ific.uv.es/refbase/show.php?record=5675), last updated on Mon, 09 Oct 2023 18:53:32 +0000",
issn="1434-6044",
doi="10.1140/epjc/s10052-023-11699-1",
opturl="https://arxiv.org/abs/2211.16345",
opturl="https://doi.org/10.1140/epjc/s10052-023-11699-1",
language="English"
}