Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at sqrt(s) = 13 TeV
The identification of prompt and isolated muons, as well asmuons from heavy-flavour hadron decays, is an important task. Wedeveloped two multivariate techniques to provide highly efficientidentification for muons with transverse momentum greater than10 GeV. One provides a continuous variable as an alternative to acut-based identification selection and offers a betterdiscrimination power against misidentified muons. The other oneselects prompt and isolated muons by using isolation requirements toreduce the contamination from nonprompt muons arising inheavy-flavour hadron decays. Both algorithms are developed using59.7 fb$^{-1}$ of proton-proton collisions data at a centre-of-massenergy of √(s)=13 TeV collected in 2018 with the CMSexperiment at the CERN LHC.