ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset
G. Aad, B. Abbott, D. C. Abbott, K. Abeling, S. H. Abidi, A. Aboulhorma, H. Abramowicz, H. Abreu, Y. Abulaiti, A. C. Abusleme Hoffman, B. S. Acharya, C. Adam Bourdarios, L. Adamczyk, L. Adámek, S. V. Addepalli, J. Adelman, A. Adıgüzel, S. Adorni, T. Adye, A. A. Affolder, Y. Afik, M. N. Agaras, J. Agarwala, A. Aggarwal, C. Agheorghiesei, J. A. Aguilar–Saavedra, A. Ahmad, F. Ahmadov, W. S. Ahmed, S. Ahuja, X. Ai, G. Aielli, M. Ait Tamlihat, B. Aitbenchikh, I. Aizenberg, M. Akbiyik, T. P. A. Åkesson, A. V. Akimov, K. Al Khoury, G. L. Alberghi, J. Albert, P. Albicocco, S. Alderweireldt, M. Aleksa, I. N. Aleksandrov, C. Alexa, T. Alexopoulos, A. Alfonsi, F. Alfonsi, M. Alhroob, B. Ali, S. Ali, M. Aliev, G. Alimonti, W. Alkakhi, C. Allaire, B. M. M. Allbrooke, C. Flores, P. P. Allport, A. Aloisio, F. Alonso, C. Alpigiani, M. Alvarez Estevez, M. G. Alviggi, M. Aly, Y. Amaral Coutinho, A. Ambler, C. Amelung, M. Amerl, C. G. Ames, D. Amidei, S. P. Amor Dos Santos, K. R. Amos, V. Ananiev, C. Anastopoulos, T. Andeen, J. K. Anders, S. Y. Andrean, A. Andreazza, S. Angelidakis, A. Angerami, A. V. Anisenkov, A. Annovi, C. Antel, M. T. Anthony, E. Antipov, M. Antonelli, D. J. A. Antrim, F. Anulli, M. Aoki, T. Aoki, J. A. Aparisi Pozo, M. A. Aparo, L. Aperio Bella, C. Appelt, N. Aranzabal, V. Araujo Ferraz, C. Arcangeletti, A. T. H. Arce, E. Arena
Abstract
Abstract The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of $$\sqrt{s} = 13$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msqrt> <mml:mi>s</mml:mi> </mml:msqrt> <mml:mo>=</mml:mo> <mml:mn>13</mml:mn> </mml:mrow> </mml:math> 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 $$t\bar{t}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> </mml:mrow> </mml:math> events; similarly, at a c -jet identification efficiency of 30%, a light-jet ( b -jet) rejection factor of 70 (9) is obtained.