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

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URI: https://hdl.handle.net/10902/32910
ISSN: 1748-0221
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Autoría
Tumasyan, A.; Brochero Cifuentes, Javier AndrésAutoridad Unican; Cabrillo Bartolomé, José IbanAutoridad Unican; Calderón Tazón, AliciaAutoridad Unican; Duarte Campderros, JorgeAutoridad Unican; Fernández García, MarcosAutoridad Unican; Fernández Madrazo, CeliaAutoridad Unican; Gómez Gramuglio, GervasioAutoridad Unican; Lasaosa García, Clara; Martínez Rivero, Celso; Martínez Ruiz del Árbol, PabloAutoridad Unican; Matorras Weinig, FranciscoAutoridad Unican; Matorras Cuevas, PabloAutoridad Unican; Piedra Gómez, JonatanAutoridad Unican; Prieëls, Cedric; Scodellaro, LucaAutoridad Unican; Vila Álvarez, Iván Autoridad Unican; Vizán García, Jesús ManuelAutoridad Unican
Fecha
2023-11
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© 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.
Publicado en
Journal of Instrumentation, 2023, 11, P11017
Editorial
Institute of Physics
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Palabras clave
Calorimeters
Data reduction methods
Resumen/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.
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© 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.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.