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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.


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DOI: 10.5445/IR/1000170545
Veröffentlicht am 08.05.2024
Originalveröffentlichung
DOI: 10.48550/arXiv.2310.03844
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Zitationen: 1
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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 arXiv
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