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 √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

CANDELISE, V.;DE LEO, K.;DELLA RICCA, G.;
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 √𝑠 = 13 TeV collected in 2018 with the CMS experiment at the CERN LHC.
2024
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https://iopscience.iop.org/article/10.1088/1748-0221/19/02/P02031
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3069619
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