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

CMS Collaboration; 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.; ... mehr

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.


Volltext §
DOI: 10.5445/IR/1000170545
Veröffentlicht am 08.05.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Astroteilchenphysik (IAP)
Institut für Experimentelle Teilchenphysik (ETP)
Institut für Prozessdatenverarbeitung und Elektronik (IPE)
Scientific Computing Center (SCC)
Publikationstyp Forschungsbericht/Preprint
Publikationsjahr 2023
Sprache Englisch
Identifikator KITopen-ID: 1000170545
Umfang 41 S.
Vorab online veröffentlicht am 05.10.2023
Nachgewiesen in Dimensions
arXiv
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