Mostrar el registro sencillo

dc.contributor.authorHayrapetyan, A.
dc.contributor.authorBhowmik, Sandeep
dc.contributor.authorBlanco Fernández, Sergio 
dc.contributor.authorBrochero Cifuentes, Javier Andrés 
dc.contributor.authorCabrillo Bartolomé, José Ibán
dc.contributor.authorCalderón Tazón, Alicia 
dc.contributor.authorDuarte Campderros, Jorge 
dc.contributor.authorFernández García, Marcos 
dc.contributor.authorFernández Madrazo, Celia 
dc.contributor.authorGómez Gramuglio, Gervasio 
dc.contributor.authorLasaosa García, Clara
dc.contributor.authorMartínez Rivero, Celso
dc.contributor.authorMartínez Ruiz del Árbol, Pablo 
dc.contributor.authorMatorras Weinig, Francisco 
dc.contributor.authorMatorras Cuevas, Pablo 
dc.contributor.authorNavarrete Ramos, Efrén
dc.contributor.authorPiedra Gómez, Jonatan 
dc.contributor.authorScodellaro, Luca 
dc.contributor.authorVila Álvarez, Iván 
dc.contributor.authorVizán García, Jesús Manuel 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2025-03-21T18:55:56Z
dc.date.available2025-03-21T18:55:56Z
dc.date.issued2024-02-23
dc.identifier.issn1748-0221
dc.identifier.urihttps://hdl.handle.net/10902/36073
dc.description.abstractThe identification of prompt and isolated muons, as well as muons from heavy-flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10 GeV. One provides a continuous variable as an alternative to a cut-based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb-1 of proton-proton collisions data at a centre-of-mass energy of vs = 13 TeV collected in 2018 with the CMS experiment at the CERN LHC.es_ES
dc.description.sponsorshipWe congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid and other centres for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); MoER, ERC PUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (U.S.A.). Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science — EOS” — be.h project n. 30820817; the Beijing Municipal Science & Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), under Germany’s Excellence Strategy — EXC 2121 “Quantum Universe” — 390833306, and under project number 400140256 - GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program - ÚNKP, the NKFIH research grants K 124845, K 124850, K 128713, K 128786, K 129058, K 131991, K 133046, K 138136, K 143460, K 143477, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64 (Hungary); the Council of Science and Industrial Research, India; ICSC — National Research Centre for High Performance Computing, Big Data and Quantum Computing, funded by the EU NexGeneration program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundação para a Ciência e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF “a way of making Europe”, and the Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia María de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation, grant B05F650021 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.).es_ES
dc.format.extent44 p.es_ES
dc.language.isoenges_ES
dc.publisherInstitute of Physicses_ES
dc.rightsAttribution 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceJournal of Instrumentation, 2024, 19(2), P02031es_ES
dc.subject.otherMuon spectrometerses_ES
dc.subject.otherParticle identification methodses_ES
dc.subject.otherParticle tracking detectorses_ES
dc.titleMuon identification using multivariate techniques in the CMS experiment in proton-proton collisions at vS = 13 TeVes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1088/1748-0221/19/02/P02031es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1088/1748-0221/19/02/P02031
dc.type.versionpublishedVersiones_ES


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo

Attribution 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International