A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV

Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire dis...

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Autores: Tumasyan, A., Brochero Cifuentes, Javier Andrés|||0000-0003-2093-7856, Cabrillo Bartolomé, José Iban|||0000-0002-0367-4022, Calderón Tazón, Alicia|||0000-0002-7205-2040, Duarte Campderros, Jorge|||0000-0003-0687-5214, Fernández García, Marcos|||0000-0002-4824-1087, Fernández Madrazo, Celia|||0000-0001-9748-4336, Fernández Manteca, Pedro José|||0000-0003-2566-7496, García Alonso, Andrea, Gómez Gramuglio, Gervasio|||0000-0002-1077-6553, Martínez Rivero, Celso, Martínez Ruiz del Árbol, Pablo|||0000-0002-7737-5121, Matorras Weinig, Francisco|||0000-0003-4295-5668, Matorras Cuevas, Pablo|||0000-0001-7481-7273, Piedra Gómez, Jonatan|||0000-0002-9157-1700, Prieëls, Cedric, Rodrigo Anoro, Teresa, Ruiz Jimeno, Alberto|||0000-0002-3639-0368, Scodellaro, Luca|||0000-0002-4974-8330, Vila Álvarez, Iván|||0000-0002-6797-7209, Vizán García, Jesús Manuel|||0000-0002-6823-8854
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/28626
Acceso en línea:https://hdl.handle.net/10902/28626
Access Level:acceso abierto
Palabra clave:Large detector-systems performance
Pattern recognition
Cluster finding
Calibration and fitting methods
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spelling A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeVTumasyan, A.Brochero Cifuentes, Javier Andrés|||0000-0003-2093-7856 Cabrillo Bartolomé, José Iban|||0000-0002-0367-4022Calderón Tazón, Alicia|||0000-0002-7205-2040Duarte Campderros, Jorge|||0000-0003-0687-5214Fernández García, Marcos|||0000-0002-4824-1087Fernández Madrazo, Celia|||0000-0001-9748-4336Fernández Manteca, Pedro José|||0000-0003-2566-7496García Alonso, AndreaGómez Gramuglio, Gervasio|||0000-0002-1077-6553Martínez Rivero, CelsoMartínez Ruiz del Árbol, Pablo|||0000-0002-7737-5121Matorras Weinig, Francisco|||0000-0003-4295-5668Matorras Cuevas, Pablo|||0000-0001-7481-7273Piedra Gómez, Jonatan|||0000-0002-9157-1700Prieëls, CedricRodrigo Anoro, TeresaRuiz Jimeno, Alberto|||0000-0002-3639-0368Scodellaro, Luca|||0000-0002-4974-8330Vila Álvarez, Iván|||0000-0002-6797-7209Vizán García, Jesús Manuel|||0000-0002-6823-8854Large detector-systems performancePattern recognitionCluster findingCalibration and fitting methodsMany measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb-1 at ?s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.Universidad de Cantabria20222022-01-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttps://hdl.handle.net/10902/28626Journal of Instrumentation, 2022, 17, P03014reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/286262026-06-02T12:39:31Z
dc.title.none.fl_str_mv A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
title A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
spellingShingle A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
Tumasyan, A.
Large detector-systems performance
Pattern recognition
Cluster finding
Calibration and fitting methods
title_short A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
title_full A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
title_fullStr A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
title_full_unstemmed A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
title_sort A new calibration method for charm jet identification validated with proton-proton collision events at vs = 13TeV
dc.creator.none.fl_str_mv Tumasyan, A.
Brochero Cifuentes, Javier Andrés|||0000-0003-2093-7856
Cabrillo Bartolomé, José Iban|||0000-0002-0367-4022
Calderón Tazón, Alicia|||0000-0002-7205-2040
Duarte Campderros, Jorge|||0000-0003-0687-5214
Fernández García, Marcos|||0000-0002-4824-1087
Fernández Madrazo, Celia|||0000-0001-9748-4336
Fernández Manteca, Pedro José|||0000-0003-2566-7496
García Alonso, Andrea
Gómez Gramuglio, Gervasio|||0000-0002-1077-6553
Martínez Rivero, Celso
Martínez Ruiz del Árbol, Pablo|||0000-0002-7737-5121
Matorras Weinig, Francisco|||0000-0003-4295-5668
Matorras Cuevas, Pablo|||0000-0001-7481-7273
Piedra Gómez, Jonatan|||0000-0002-9157-1700
Prieëls, Cedric
Rodrigo Anoro, Teresa
Ruiz Jimeno, Alberto|||0000-0002-3639-0368
Scodellaro, Luca|||0000-0002-4974-8330
Vila Álvarez, Iván|||0000-0002-6797-7209
Vizán García, Jesús Manuel|||0000-0002-6823-8854
author Tumasyan, A.
author_facet Tumasyan, A.
Brochero Cifuentes, Javier Andrés|||0000-0003-2093-7856
Cabrillo Bartolomé, José Iban|||0000-0002-0367-4022
Calderón Tazón, Alicia|||0000-0002-7205-2040
Duarte Campderros, Jorge|||0000-0003-0687-5214
Fernández García, Marcos|||0000-0002-4824-1087
Fernández Madrazo, Celia|||0000-0001-9748-4336
Fernández Manteca, Pedro José|||0000-0003-2566-7496
García Alonso, Andrea
Gómez Gramuglio, Gervasio|||0000-0002-1077-6553
Martínez Rivero, Celso
Martínez Ruiz del Árbol, Pablo|||0000-0002-7737-5121
Matorras Weinig, Francisco|||0000-0003-4295-5668
Matorras Cuevas, Pablo|||0000-0001-7481-7273
Piedra Gómez, Jonatan|||0000-0002-9157-1700
Prieëls, Cedric
Rodrigo Anoro, Teresa
Ruiz Jimeno, Alberto|||0000-0002-3639-0368
Scodellaro, Luca|||0000-0002-4974-8330
Vila Álvarez, Iván|||0000-0002-6797-7209
Vizán García, Jesús Manuel|||0000-0002-6823-8854
author_role author
author2 Brochero Cifuentes, Javier Andrés|||0000-0003-2093-7856
Cabrillo Bartolomé, José Iban|||0000-0002-0367-4022
Calderón Tazón, Alicia|||0000-0002-7205-2040
Duarte Campderros, Jorge|||0000-0003-0687-5214
Fernández García, Marcos|||0000-0002-4824-1087
Fernández Madrazo, Celia|||0000-0001-9748-4336
Fernández Manteca, Pedro José|||0000-0003-2566-7496
García Alonso, Andrea
Gómez Gramuglio, Gervasio|||0000-0002-1077-6553
Martínez Rivero, Celso
Martínez Ruiz del Árbol, Pablo|||0000-0002-7737-5121
Matorras Weinig, Francisco|||0000-0003-4295-5668
Matorras Cuevas, Pablo|||0000-0001-7481-7273
Piedra Gómez, Jonatan|||0000-0002-9157-1700
Prieëls, Cedric
Rodrigo Anoro, Teresa
Ruiz Jimeno, Alberto|||0000-0002-3639-0368
Scodellaro, Luca|||0000-0002-4974-8330
Vila Álvarez, Iván|||0000-0002-6797-7209
Vizán García, Jesús Manuel|||0000-0002-6823-8854
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
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author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Large detector-systems performance
Pattern recognition
Cluster finding
Calibration and fitting methods
topic Large detector-systems performance
Pattern recognition
Cluster finding
Calibration and fitting methods
description Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb-1 at ?s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10902/28626
url https://hdl.handle.net/10902/28626
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Journal of Instrumentation, 2022, 17, P03014
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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