Mimar Sinan Güzel Sanatlar Üniversitesi Açık Bilim, Sanat Arşivi

Açık Bilim, Sanat Arşivi, Mimar Sinan Güzel Sanatlar Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.

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dc.contributor.authorSirunyan, A.M.
dc.contributor.authorTumasyan, A.
dc.contributor.authorAdam, W.
dc.contributor.authorAmbrogi, F.
dc.contributor.authorBergauer, T.
dc.contributor.authorDragicevic, M.
dc.contributor.authorÖzok, Ferhat
dc.date.accessioned2025-01-09T20:03:31Z
dc.date.available2025-01-09T20:03:31Z
dc.date.issued2022
dc.identifier.issn1748-0221
dc.identifier.urihttps://doi.org/10.1088/1748-0221/17/03/P03014
dc.identifier.urihttps://hdl.handle.net/20.500.14124/7504
dc.description.abstractMany measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb?1 at ?s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses. © 2022 CERN for the benefit of the CMS collaborationen_US
dc.description.sponsorshipCouncil of Scientific and Industrial Research, India, CSIR; Ministry of Education, MOE; Ministry of Business, Innovation and Employment, MBIE; Ministry of Education and Science, MES; Benemérita Universidad Autónoma de Puebla, BUAP; Department of Atomic Energy, Government of India, DAE; Kanton Zürich; National Academy of Sciences of Ukraine, NASU; Federal Agency of Atomic Energy of the Russian Federation; National Science and Technology Development Agency, ????; National Research Foundation of Korea, NRF; National Science Foundation, NSF; Institut National de Physique Nucléaire et de Physique des Particules, IN2P3; Latvijas Zin?tnes Padome; Science and Technology Facilities Council, STFC; Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, CINVESTAV; Ministry of Science, ICT and Future Planning, MSIP; General Secretariat for Research and Innovation; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, FAPERJ; Ministry of Education and Science; Universiti Malaya, UM; Research and Innovation Foundation, RIF; Russian Academy of Sciences, ???; Bundesministerium für Bildung, Wissenschaft und Forschung, BMBWF; Ministry of Science of Montenegro; Haridus- ja Teadusministeerium, HM; Board of the Swiss Federal Institutes of Technology; Instituto Nazionale di Fisica Nucleare, INFN; Secretaría de Educación Pública, SEP; Thailand Center of Excellence in Physics; Austrian Science Fund, FWF; Ministry of Science, Technology and Research, Sri Lanka; Department of Science and Technology, Ministry of Science and Technology, India, ??????; Chulalongkorn Academic; Consejo Nacional de Ciencia y Tecnología, CONACYT; Helsinki Institute of Physics; Türkiye Atom Enerjisi Kurumu, TAEK; Belgian Federal Science Policy Office, BELSPO; Centre National de la Recherche Scientifique, CNRS; MINCIENCIAS; Bundesministerium für Bildung und Forschung, BMBF; Fonds Wetenschappelijk Onderzoek, FWO; Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK; Eidgenössische Technische Hochschule Zürich, ETH; Kavli Foundation; Helmholtz-Gemeinschaft, HGF; Commissariat à l'Énergie Atomique et aux Énergies Alternatives, CEA; Academy of Finland, AKA; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Pakistan Atomic Energy Commission, PAEC; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES; Mexican Funding Agencies; Ministry of Education and Science of the Republic of Kazakhstan; Secretariat for Higher Education, Science, Technology and Innovation; Russian Foundation for Basic Research, ????; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, MPNTR; Science Foundation Ireland, SFI; U.S. Department of Energy, USDOE; Secretaría de Estado de Investigación; Universität Zürich, UZH; Ministry of Education and Science of the Russian Federation, Minobrnauka; Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP; Lietuvos Moksl? Akademija; National Research Centre, NRC; Ministry of Science and Technology, MOST; Ministerio de Ciencia, Tecnología e Innovación Productiva, MINCyT; Stavros Niarchos Foundation, SNF; Bulgarian National Science Fund, BNSF; Direktion für Entwicklung und Zusammenarbeit, DEZA; Alfred P. Sloan Foundation, APSF; Chulalongkorn University, CU; Ministarstvo Znanosti, Obrazovanja i Sporta, MZOS; Chinese Academy of Sciences, CAS; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF; Fonds De La Recherche Scientifique - FNRS, FNRS; Opetus- ja Kulttuuriministeriö; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul, FAPERGS; Weston Havens Foundation; Sociedad Española de Reumatología, SER; Institute for the Promotion of Teaching Science and Technology, IPST; Magyar Tudományos Akadémia, MTA; A.G. Leventis Foundation; European Research Council, ERC; Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture, FRIA; Laboratorio Nacional de Supercómputo del Sureste de Mexico, LNS; European Regional Development Fund, ERDF; Nvidia; Joint Institute for Nuclear Research, JINR; Ministerstvo Školství, Mláde?e a T?lov?chovy, MŠMT; Institute for Studies in Theoretical Physics and Mathematics; Alexander von Humboldt-Stiftung, AvH; Paul Scherrer Institut, PSI; Desarrollo e Innovación; Hrvatska Zaklada za Znanost, HRZZ; Horizon 2020; Agentschap voor Innovatie door Wetenschap en Technologie, IWT; Universidad Autónoma de San Luis Potosí, UASLP; National Natural Science Foundation of China, NSFC; Welch Foundation, (C-1845); Welch Foundation; Horizon 2020 Framework Programme, H2020, (758316, 765710, 752730, 884104, 824093, 675440, 724704); Horizon 2020 Framework Programme, H2020; Eesti Teadusagentuur, ETAg, (PRG803, PRG780, PRG445); Eesti Teadusagentuur, ETAg; Spanish National Plan for Scientific and Technical Research and Innovation, (IDI-2018-000174); Spanish National Plan for Scientific and Technical Research and Innovation; Qatar National Research Fund, QNRF, (FSWW-2020-0008); Qatar National Research Fund, QNRF; Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA, (125105, 128713, 124850, 123842, 124845, 128786, 123959, 129058); Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA; European Cooperation in Science and Technology, COST, (CA16108); European Cooperation in Science and Technology, COST; Excellence of Science, (30820817); Beijing Municipal Science and Technology Commission, BMSTC, (Z191100007219010); Beijing Municipal Science and Technology Commission, BMSTC; Fundação para a Ciência e a Tecnologia, FCT, (CEECIND/01334/2018, CERN/FIS-PAR/0025/2019, CERN/FIS-INS/0032/2019); Fundação para a Ciência e a Tecnologia, FCT; Narodowe Centrum Nauki, NCN, (2014/15/B/ST2/03998, 2015/19/B/ST2/02861); Narodowe Centrum Nauki, NCN; Deutsche Forschungsgemeinschaft, DFG, (400140256 - GRK2497, 390833306); Deutsche Forschungsgemeinschaft, DFGen_US
dc.language.isoengen_US
dc.publisherInstitute of Physicsen_US
dc.relation.ispartofJournal of Instrumentationen_US
dc.rightsMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.subjectLarge detector-systems performanceen_US
dc.subjectPattern recognition, cluster finding, calibration and fitting methodsen_US
dc.titleA new calibration method for charm jet identification validated with proton-proton collision events at ?s = 13TeVen_US
dc.typearticleen_US
dc.departmentFakülteler, Fen Edebiyat Fakültesi, Fizik Bölümüen_US
dc.institutionauthorÖzok, Ferhat
dc.identifier.doi10.1088/1748-0221/17/03/P03014
dc.identifier.volume17en_US
dc.identifier.issue3en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-85127541495en_US
dc.identifier.scopusqualityQ2
dc.indekslendigikaynakScopus
dc.snmzKA_20250105


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