Identification of hadronic tau lepton decays using a deep neural network
A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (τh ) that originate from genuine tau leptons in the CMS detector against τh candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed part...
| Autores: | , , , , , , , , , , , , , , , , , , , , |
|---|---|
| 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:10902/28644 |
| Acceso en línea: | https://hdl.handle.net/10902/28644 |
| Access Level: | acceso abierto |
| Palabra clave: | Large detector systems for particle and astroparticle physics Particle identification methods Pattern recognition Cluster finding Calibration and fitting methods |
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Identification of hadronic tau lepton decays using a deep neural networkTumasyan, 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 for particle and astroparticle physicsParticle identification methodsPattern recognitionCluster findingCalibration and fitting methodsA new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (τh ) that originate from genuine tau leptons in the CMS detector against τh candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a τh candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine τh to pass the discriminator against jets increases by 10–30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient τh reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved τh reconstruction method are validated with LHC proton-proton collision data at √ �������� = 13 TeVUniversidad 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/10902/28644Journal of Instrumentation, 2022, 17, P07023reponame: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:10902/286442026-06-02T12:39:31Z |
| dc.title.none.fl_str_mv |
Identification of hadronic tau lepton decays using a deep neural network |
| title |
Identification of hadronic tau lepton decays using a deep neural network |
| spellingShingle |
Identification of hadronic tau lepton decays using a deep neural network Tumasyan, A. Large detector systems for particle and astroparticle physics Particle identification methods Pattern recognition Cluster finding Calibration and fitting methods |
| title_short |
Identification of hadronic tau lepton decays using a deep neural network |
| title_full |
Identification of hadronic tau lepton decays using a deep neural network |
| title_fullStr |
Identification of hadronic tau lepton decays using a deep neural network |
| title_full_unstemmed |
Identification of hadronic tau lepton decays using a deep neural network |
| title_sort |
Identification of hadronic tau lepton decays using a deep neural network |
| 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 author author author |
| dc.contributor.none.fl_str_mv |
Universidad de Cantabria |
| dc.subject.none.fl_str_mv |
Large detector systems for particle and astroparticle physics Particle identification methods Pattern recognition Cluster finding Calibration and fitting methods |
| topic |
Large detector systems for particle and astroparticle physics Particle identification methods Pattern recognition Cluster finding Calibration and fitting methods |
| description |
A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (τh ) that originate from genuine tau leptons in the CMS detector against τh candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a τh candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine τh to pass the discriminator against jets increases by 10–30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient τh reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved τh reconstruction method are validated with LHC proton-proton collision data at √ �������� = 13 TeV |
| 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/10902/28644 |
| url |
https://hdl.handle.net/10902/28644 |
| 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, P07023 reponame:UCrea Repositorio Abierto de la Universidad de Cantabria instname:Universidad de Cantabria (UC) |
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Universidad de Cantabria (UC) |
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UCrea Repositorio Abierto de la Universidad de Cantabria |
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UCrea Repositorio Abierto de la Universidad de Cantabria |
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1869414688257736704 |
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15,301603 |