| dc.contributor.author | Tumasyan, A. | |
| dc.contributor.author | Brochero Cifuentes, Javier Andrés | |
| dc.contributor.author | Cabrillo Bartolomé, José Iban | |
| dc.contributor.author | Calderón Tazón, Alicia | |
| dc.contributor.author | Duarte Campderros, Jorge | |
| dc.contributor.author | Fernández García, Marcos | |
| dc.contributor.author | Fernández Madrazo, Celia | |
| dc.contributor.author | Gómez Gramuglio, Gervasio | |
| dc.contributor.author | Lasaosa García, Clara | |
| dc.contributor.author | Martínez Rivero, Celso | |
| dc.contributor.author | Martínez Ruiz del Árbol, Pablo | |
| dc.contributor.author | Matorras Weinig, Francisco | |
| dc.contributor.author | Matorras Cuevas, Pablo | |
| dc.contributor.author | Piedra Gómez, Jonatan | |
| dc.contributor.author | Prieëls, Cedric | |
| dc.contributor.author | Scodellaro, Luca | |
| dc.contributor.author | Vila Álvarez, Iván | |
| dc.contributor.author | Vizán García, Jesús Manuel | |
| dc.contributor.other | Universidad de Cantabria | es_ES |
| dc.date.accessioned | 2024-05-23T14:02:13Z | |
| dc.date.available | 2024-05-23T14:02:13Z | |
| dc.date.issued | 2023-11 | |
| dc.identifier.issn | 1748-0221 | |
| dc.identifier.uri | https://hdl.handle.net/10902/32910 | |
| dc.description.abstract | A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015-2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared. | es_ES |
| dc.description.sponsorship | Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 884104, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIABelgium); 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; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Deutsche Forschungsgemeinschaft (DFG), under Germany’s Excellence Strategy — EXC 2121 "Quantum Universe" — 390833306, and under project number 400140256 — GRK2497; 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; the National Research Foundation of Korea (NRF/MSIT) grant No. 2020R1C1C1005916 (Korea); 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.extent | 36 p. | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Institute of Physics | es_ES |
| dc.rights | © 2023 CERN for the benefit of the CMS collaboration. Published by IOP Publishing Ltd on behalf of Sissa Medialab. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.source | Journal of Instrumentation, 2023, 11, P11017 | es_ES |
| dc.subject.other | Calorimeters | es_ES |
| dc.subject.other | Data reduction methods | es_ES |
| dc.title | Performance of the local reconstruction algorithms for the CMS hadron calorimeter with Run 2 data | es_ES |
| dc.type | info:eu-repo/semantics/article | es_ES |
| dc.relation.publisherVersion | https://doi.org/10.1088/1748-0221/18/11/P11017 | es_ES |
| dc.rights.accessRights | openAccess | es_ES |
| dc.identifier.DOI | 10.1088/1748-0221/18/11/P11017 | |
| dc.type.version | publishedVersion | es_ES |
Excepto si se señala otra cosa, la licencia del ítem se describe como © 2023 CERN for the benefit of the CMS collaboration. Published by IOP Publishing Ltd on behalf of Sissa Medialab. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence.
