ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset

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dc.contributor.authorAad G.
dc.contributor.authorAbbott B.
dc.contributor.authorAbeling K.
dc.contributor.authorAbicht N. J.
dc.contributor.authorAbidi S. H.
dc.contributor.authorAboulhorma A.
dc.contributor.authorAbramowicz H.
dc.contributor.authorAbreu H.
dc.contributor.authorAbulaiti Y.
dc.contributor.authorAbusleme Hoffman A. C.
dc.contributor.authorAcharya B. S.
dc.contributor.authorAdam Bourdarios C.
dc.contributor.authorAdamczyk L.
dc.contributor.authorAdamek L.
dc.contributor.authorAddepalli S. V.
dc.contributor.authorAddison M. J.
dc.contributor.authorAdelman J.
dc.contributor.authorAdiguzel A.
dc.contributor.authorAdorni S.
dc.contributor.authorAdye T.
dc.contributor.authorAffolder A. A.
dc.contributor.authorAfik Y.
dc.contributor.authorAgaras M. N.
dc.contributor.authorAgarwala J.
dc.contributor.authorAggarwal A.
dc.contributor.authorAgheorghiesei C.
dc.contributor.authorAhmad A.
dc.contributor.authorAhmadov F.
dc.contributor.authorAhmed W. S.
dc.contributor.authorAhuja S.
dc.contributor.authorAi X.
dc.contributor.authorAielli G.
dc.contributor.authorAit Tamlihat M.
dc.contributor.authorAitbenchikh B.
dc.contributor.authorAizenberg I.
dc.contributor.authorAkbiyik M.
dc.contributor.authorAkesson T. P. A.
dc.contributor.authorAkimov A. V.
dc.contributor.authorAkiyama D.
dc.contributor.authorAkolkar N. N.
dc.date.accessioned2025-05-19T16:37:51Z
dc.date.available2025-05-19T16:37:51Z
dc.date.issued2023/07/31
dc.description.abstractThe 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.
dc.identifier.doihttp://dx.doi.org/10.1140/epjc/s10052-023-11699-1
dc.identifier.issn1434-6044
dc.identifier.urihttps://publicacionesabiertas.userena.cl/handle/123456789/254
dc.languageEnglish
dc.publisherSPRINGER
dc.titleATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset
dc.typeArticle

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