Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at $\sqrt{s}$ = 13 TeV

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 $\sqrt{s}$ = 13 TeV collected in 2018 with the CMS experiment at the CERN LHC.

Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at http://cms-results.web.cern.ch/cms-results/public-results/publications/MUO-22-001 (CMS Public Pages)