TY - JOUR AU - ATLAS Collaboration (Aad, G. et al AU - Amos, K. R. AU - Aparisi Pozo, J. A. AU - Bailey, A. J. AU - Bouchhar, N. AU - Cabrera Urban, S. AU - Cantero, J. AU - Cardillo, F. AU - Castillo Gimenez, V. AU - Chitishvili, M. AU - Costa, M. J. AU - Didenko AU - Escobar, C. AU - Fiorini, L. AU - Fullana Torregrosa, E. AU - Fuster, J. AU - Garcia, C. AU - Garcia Navarro, J. E. AU - Gomez Delegido, A. J. AU - Gonzalez de la Hoz, S. AU - Gonzalvo Rodriguez, G. R. AU - Guerrero Rojas, J. G. R. AU - Lacasta, C. AU - Lozano Bahilo, J. J. AU - Marti-Garcia, S. AU - Martinez Agullo, P. AU - Miralles Lopez, M. AU - Mitsou, V. A. AU - Monsonis Romero, L. AU - Moreno Llacer, M. AU - Munoz Perez, D. AU - Navarro-Gonzalez, J. AU - Poveda, J. AU - Prades IbaƱez, A. AU - Rubio Jimenez, A. AU - Ruiz-Martinez, A. AU - Sabatini, P. AU - Salt, J. AU - Sanchez Sebastian, V. AU - Sayago Galvan, I. AU - Senthilkumar, V. AU - Soldevila, U. AU - Sanchez, J. AU - Torro Pastor, E. AU - Valero, A. AU - Valls Ferrer, J. A. AU - Varriale, L. AU - Villaplana Perez, M. AU - Vos, M. PY - 2023 DA - 2023// TI - ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset T2 - Eur. Phys. J. C JO - European Physical Journal C SP - 681 - 37pp VL - 83 IS - 7 PB - Springer AB - 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. SN - 1434-6044 UR - https://arxiv.org/abs/2211.16345 UR - https://doi.org/10.1140/epjc/s10052-023-11699-1 DO - 10.1140/epjc/s10052-023-11699-1 LA - English N1 - WOS:001062397400001 ID - ATLASCollaborationAad_etal2023 ER -