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.