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dc.contributor.authorHayrapetyan, A.
dc.contributor.authorTumasyan, A.
dc.contributor.authorBhowmik, Sandeep
dc.contributor.authorBlanco Fernández, Sergio 
dc.contributor.authorCabrillo Bartolomé, José Ibán
dc.contributor.authorCalderón Tazón, Alicia 
dc.contributor.authorDuarte Campderros, Jorge 
dc.contributor.authorFernández García, Marcos 
dc.contributor.authorGómez Gramuglio, Gervasio 
dc.contributor.authorLasaosa García, Clara
dc.contributor.authorLópez Ruiz, Rubén
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.accessioned2025-12-18T15:23:44Z
dc.date.available2025-12-18T15:23:44Z
dc.date.issued2025-04-10
dc.identifier.issn1748-0221
dc.identifier.otherMDM-2017-0765es_ES
dc.identifier.urihttps://hdl.handle.net/10902/38572
dc.description.abstractThe TOTEM Roman pot detectors are used to reconstruct the transverse momentum of scattered protons and to estimate the transverse location of the primary interaction. This paper presents new methods of track reconstruction, measurements of strip-level detection efficiencies, cross-checks of the LHC beam optics, and detector alignment techniques, along with their application in the selection of signal collision events. The track reconstruction is performed by exploiting hit cluster information through a novel method using a common polygonal area in the intercept-slope plane. The technique is applied in the relative alignment of detector layers with um precision. A tag-and-probe method is used to extract strip-level detection efficiencies. The alignment of the Roman pot system is performed through time-dependent adjustments, resulting in a position accuracy of 3 um in the horizontal and 60 um in the vertical directions. The goal is to provide an optimal reconstruction tool for central exclusive physics analyses based on the high-B* data-taking period at V¯(s) = 13 TeV in 2018.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 and TOTEM institutes for their contributions to the success of the common CMS-TOTEM 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 and TOTEM detectors, 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); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, Magnus Ehrnrooth Foundation, MEC, HIP, and Waldemar von Frenckell Foundation (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); LMTLT (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, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (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 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), among others, 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 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA-64, and 2021-4.1.2-NEMZ_KI-2024- 00036 (Hungary); the Council of Science and Industrial Research, India; ICSC — National Research Centre for High Performance Computing, Big Data and Quantum Computing and FAIR — Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Centre, 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 B39G670016 (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.extent54 p.es_ES
dc.language.isoenges_ES
dc.publisherInstitute of Physicses_ES
dc.rightsAttribution 4.0 International. © 2025 CERN.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceJournal of Instrumentation, 2025, 20(4), P04012es_ES
dc.subject.otherPattern Recognitiones_ES
dc.subject.otherCluster Findinges_ES
dc.subject.otherCalibration and Fitting Methodses_ES
dc.subject.otherPerformance of High Energy Physics Detectorses_ES
dc.titleProton reconstruction with the TOTEM Roman pot detectors for high-B* LHC dataes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1088/1748-0221/20/04/P04012es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1088/1748-0221/20/04/P04012
dc.type.versionpublishedVersiones_ES


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Attribution 4.0 International. © 2025 CERN.Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International. © 2025 CERN.