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

dc.contributor.authorAad, Georges
dc.contributor.authorAguilar Saavedra, Juan Antonio 
dc.contributor.authorRodríguez Chala, Mikael 
dc.contributor.authorAtlas Collaboration
dc.date.accessioned2023-09-29T11:18:40Z
dc.date.available2023-09-29T11:18:40Z
dc.date.issued2023-07-31
dc.identifier.citationAad, G., Abbott, B., Abbott, D.C. et al. ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset. Eur. Phys. J. C 83, 681 (2023). [https://doi.org/10.1140/epjc/s10052-023-11699-1]es_ES
dc.identifier.urihttps://hdl.handle.net/10481/84741
dc.descriptionWe acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Türkiye; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CCIN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NLT1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers.es_ES
dc.description.abstractThe 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.es_ES
dc.description.sponsorshipCERNes_ES
dc.description.sponsorshipMICINN, Spaines_ES
dc.description.sponsorshipCOSTes_ES
dc.description.sponsorshipERCes_ES
dc.description.sponsorshipERDFes_ES
dc.description.sponsorshipEuropean Uniones_ES
dc.description.sponsorshipLa Caixa Banking Foundationes_ES
dc.description.sponsorshipH2020 Marie Skłodowska-Curie Actions MSCAes_ES
dc.description.sponsorshipEuropean Research Council ERCes_ES
dc.description.sponsorshipGeneralitat de Catalunyaes_ES
dc.description.sponsorshipAgencia Nacional de Promoción Científica y Tecnológica ANPCyTes_ES
dc.description.sponsorshipHorizon 2020es_ES
dc.description.sponsorshipAgencia Nacional de Investigación y Desarrollo ANIDes_ES
dc.description.sponsorshipGeneralitat Valenciana, Spaines_ES
dc.description.sponsorshipPIC (Spain)es_ES
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleATLAS flavour-tagging algorithms for the LHC Run 2 pp collision datasetes_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1140/epjc/s10052-023-11699-1
dc.type.hasVersionVoRes_ES


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