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Performance of the local reconstruction algorithms for the CMS hadron calorimeter with Run 2 data

  • The CMS collaboration
  • A. Alikhanian Yerevan Institute of Physics
  • Yerevan State University
  • Austrian Academy of Sciences
  • TU Wien
  • University of Antwerp
  • Arab Academy for Science, Technology and Maritime Transport
  • Université libre de Bruxelles
  • Vrije Universiteit Brussel
  • Ghent University
  • Université catholique de Louvain
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  • Universidade Federal do Rio Grande do Sul
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  • Universidade Estadual Paulista Júlio de Mesquita Filho
  • Bulgarian Academy of Sciences
  • Sofia University St. Kliment Ohridski
  • Universidad de Tarapacá
  • Beihang University
  • University of Chinese Academy of Sciences
  • Tsinghua University
  • Nanjing Normal University
  • CAS - Institute of High Energy Physics
  • Peking University
  • Sun Yat-Sen University
  • University of Science and Technology of China
  • Fudan University
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  • Universidad de los Andes Colombia
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  • Georgian Technical University
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  • Universidade do Estado do Amazonas
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  • German Electron Synchrotron
  • University of Hamburg
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  • National and Kapodistrian University of Athens
  • National Technical University of Athens
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  • Eötvös Loránd University
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  • University College Dublin
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Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article numberP11017
JournalJournal of Instrumentation
Volume11
DOIs
Publication statusPublished - 1 Nov 2023
Externally publishedYes

Keywords

  • Calorimeters
  • Data reduction methods

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