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 √s=13 TeV

Carlin, R.;Gasparini, U.;Lusiani, E.;Margoni, M.;Migliorini, M.;Pazzini, J.;Ronchese, P.;Rossin, R.;Strong, G.;Tosi, M.;Triossi, A.;Yarar, H.;Zanetti, M.;Zotto, P.;
2024

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3531608
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