The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of 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 tt¯ events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.
ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset / Betti, Alessandra; DE SALVO, Alessandro; Di Domenico, Antonio.; Dionisi, Carlo.; Bini, Cesare; Luci, Claudio; POMPA PACCHI, Elena; Morodei, Federico; Lacava, Francesco; SAFAI TEHRANI, Francesco; Artoni, Giacomo; Santi, Lorenzo; Russo, Graziella; Martinelli, Luca; Maiani, Luciano; Rescigno, Marco; Bauce, Matteo; Gauzzi, Paolo; Gentile, Simonetta; Giagu, Stefano; Ippolito, Valerio. - In: THE EUROPEAN PHYSICAL JOURNAL. C, PARTICLES AND FIELDS. - ISSN 1434-6044. - 83:7(2023), pp. 1-37. [10.1140/epjc/s10052-023-11699-1]
ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset
Betti Alessandra;De Salvo Alessandro;Di Domenico Antonio.;Dionisi Carlo.;Bini Cesare;Luci Claudio;Pompa Pacchi Elena;Morodei Federico;Lacava Francesco;Safai Tehrani Francesco;Artoni Giacomo;Santi Lorenzo;Russo Graziella;Martinelli Luca;Maiani Luciano;Rescigno Marco;Bauce Matteo;Gauzzi Paolo;Gentile Simonetta;Giagu Stefano;Ippolito Valerio
2023
Abstract
The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of 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 tt¯ events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.| File | Dimensione | Formato | |
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