• Medientyp: E-Artikel
  • Titel: Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at sqrt(s) = 13 TeV
  • Beteiligte: Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J.W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P.S.; Jeitler, M.; Krammer, N.; Liko, D.; Mikulec, I.; Schieck, J.; Schöfbeck, R.; Schwarz, D.; Sonawane, M.; Templ, S.; Waltenberger, W.; Wulz, C.-E.; Darwish, M.R.; Janssen, T.; Van Mechelen, P.; [...]
  • Erschienen: IOP Publishing, 2024
  • Erschienen in: Journal of Instrumentation, 19 (2024) 2, Seite P02031
  • Sprache: Ohne Angabe
  • DOI: 10.1088/1748-0221/19/02/p02031
  • ISSN: 1748-0221
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: 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.