Identification of hadronic tau lepton decays using a deep neural network
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Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Iop Publishing Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons (tau(h)) that originate from genuine tau leptons in the CMS detector against tau(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 tau(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 tau(h) to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient tau(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 tau(h) reconstruction method are validated with LHC proton-proton collision data at root s = 13 TeV.
Açıklama
Anahtar Kelimeler
Large detector systems for particle and astroparticle physics, Particle identification methods, Pattern recognition, cluster finding, calibration and fitting methods
Kaynak
Journal of Instrumentation
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
17
Sayı
7
