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Identification of hadronic tau lepton decays using a deep neural network

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dc.contributor.authorChadeeva, M.
dc.contributor.authorOskin, A.
dc.contributor.authorParygin, P.
dc.contributor.authorPopova, E.
dc.contributor.authorSelivanova, D.
dc.contributor.authorMatveev, V.
dc.contributor.authorZhemchugov, E.
dc.contributor.authorЧадеева, Марина Валентиновна
dc.contributor.authorМатвеев, Виктор Анатольевич
dc.date.accessioned2024-12-25T07:28:13Z
dc.date.available2024-12-25T07:28:13Z
dc.date.issued2022
dc.description.abstractA new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (τ h) that originate from genuine tau leptons in the CMS detector against τ h candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a τ h 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 τ h to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient τ h 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 τ h reconstruction method are validated with LHC proton-proton collision data at s = 13 TeV. © 2022 CERN.
dc.identifier.citationIdentification of hadronic tau lepton decays using a deep neural network / Tumasyan, A. [et al.] // Journal of Instrumentation. - 2022. - 17. - № 7. - 10.1088/1748-0221/17/07/P07023
dc.identifier.doi10.1088/1748-0221/17/07/P07023
dc.identifier.urihttps://www.doi.org/10.1088/1748-0221/17/07/P07023
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85135918744&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/27314
dc.relation.ispartofJournal of Instrumentation
dc.titleIdentification of hadronic tau lepton decays using a deep neural network
dc.typeArticle
dspace.entity.typePublication
oaire.citation.issue7
oaire.citation.volume17
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