Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/10667
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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.date.accessioned2023-10-24T06:59:06Z-
dc.date.available2023-10-24T06:59:06Z-
dc.date.issued2023-
dc.identifier.issn1434-6044-
dc.identifier.issn1434-6052-
dc.identifier.urihttps://doi.org/10.1140/epjc/s10052-023-11699-1-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/10667-
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.en_US
dc.description.sponsorshipANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW; FWF, Austria; ANAS; CNPq; FAPESP, Brazil; NSERC; CFI, Canada; NSFC, China; MEYS CR, Czech Republic; DNRF; DNSRC, Denmark; IN2P3-CNRS; CEA-DRF/IRFU, France; BMBF; MPG, Germany; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MEiN, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARRS; MIZS, Slovenia; MICINN, Spain; Wallenberg Foundation, Sweden; SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; DOE; NSF, United States of America; BCKDF; CANARIE; CRC, Canada [PRIMUS 21/SCI/017, UNCE SCI/013]; Czech Republic; ERC; ERDF; Marie Skodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex; ANR, France; DFG; AvH Foundation, Germany - EU-ESF; Greek NSRF, Greece; BSF-NSF; NCN; La Caixa Banking Foundation; CERCA Programme Generalitat de Catalunya; PROMETEO; Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; Royal Society; Leverhulme Trust, United Kingdomen_US
dc.description.sponsorshipWe 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 MIZS, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TENMAK, Turkiye; 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 Skodowska-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; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofEuropean Physical Journal Cen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleAtlas Flavour-Tagging Algorithms for the Lhc Run 2 Pp Collision Dataseten_US
dc.typeArticleen_US
dc.departmentTOBB ETÜen_US
dc.identifier.volume83en_US
dc.identifier.issue7en_US
dc.authoridLee, Lawrence/0000-0002-5590-335X-
dc.authoridCieśla, Krzysztof/0000-0003-2751-3474-
dc.authoridBenchekroun, Driss/0000-0001-5196-8327-
dc.authoridChwastowski, Janusz J./0000-0002-6190-8376-
dc.authoridMaleev, Victor/0000-0003-1028-8602-
dc.authoridVasile, Matei-Eugen/0000-0001-8415-0759-
dc.authoridTerashi, Koji/0000-0001-6520-8070-
dc.identifier.wosWOS:001062397400001en_US
dc.identifier.scopus2-s2.0-85167625195en_US
dc.institutionauthor…-
dc.identifier.doi10.1140/epjc/s10052-023-11699-1-
dc.authorwosidLee, Lawrence/AAU-6790-2021-
dc.authorwosidCieśla, Krzysztof/AAM-4181-2021-
dc.authorwosidChwastowski, Janusz J./I-4480-2012-
dc.authorwosidBenchekroun, Driss/JCN-4659-2023-
dc.authorwosidMaleev, Victor/R-4140-2016-
dc.authorwosidVasile, Matei-Eugen/ADS-3975-2022-
dc.authorwosidTerashi, Koji/ITW-2370-2023-
dc.authorscopusid26326745400-
dc.authorscopusid35226946900-
dc.authorscopusid57940808000-
dc.authorscopusid57210132793-
dc.authorscopusid56536227400-
dc.authorscopusid57246251500-
dc.authorscopusid35226937900-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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