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.

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

Bruschini, D.;
2024

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.
2024
Settore PHYS-01/A - Fisica sperimentale delle interazioni fondamentali e applicazioni
Muon spectrometers; Particle identification methods; Particle tracking detectors
  
     https://doi.org/10.1088/1748-0221/19/02/P02031
     https://dx.doi.org/10.1088/1748-0221/19/02/P02031
File in questo prodotto:
File Dimensione Formato  
Hayrapetyan_2024_J._Inst._19_P02031.pdf

accesso aperto

Tipologia: Published version
Licenza: Creative Commons
Dimensione 2.56 MB
Formato Adobe PDF
2.56 MB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/154800
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
  • OpenAlex 4
social impact