The identification of prompt and isolated muons, as well as muons from heavy -flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10 GeV. One provides a continuous variable as an alternative to a cut -based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb-1 of proton-proton collisions data at a centre-of-mass energy of root s = 13 TeV collected in 2018 with the CMS experiment at the CERN LHC.
Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at sqrt(s) = 13 TeV
Cappati, A.;Meridiani, P.;Amapane, N.;Argiro, S.;Bellan, R.;Bellora, A.;Costa, M.;Covarelli, R.;Grippo, M.;Kiani, B.;Mecca, A.;Migliore, E.;Obertino, M. M.;Pacher, L.;Siviero, F.;Sola, V.;Solano, A.;Soldi, D.;Tornago, M.;Shchelina, K.;Rumerio, P.;Ravera, F.;Salvatico, R.;Vagnerini, A.;
2024-01-01
Abstract
The identification of prompt and isolated muons, as well as muons from heavy -flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10 GeV. One provides a continuous variable as an alternative to a cut -based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb-1 of proton-proton collisions data at a centre-of-mass energy of root s = 13 TeV collected in 2018 with the CMS experiment at the CERN LHC.File | Dimensione | Formato | |
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Hayrapetyan_2024_J._Inst._19_P02031.pdf
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