Identification of low-momentum muons in the CMS detector using multivariate techniques in proton-proton collisions at √s = 13.6 TeV

The CMS collaboration

Research output: Contribution to journalArticlepeer-review

Abstract

"Soft"muons with a transverse momentum below 10 GeV are featured in many processes studied by the CMS experiment, such as decays of heavy-flavor hadrons or rare tau lepton decays. Maximizing the selection efficiency for these muons, while simultaneously suppressing backgrounds from long-lived light-flavor hadron decays, is therefore important for the success of the CMS physics program. Multivariate techniques have been shown to deliver better muon identification performance than traditional selection techniques. To take full advantage of the large data set currently being collected during Run 3 of the CERN LHC, a new multivariate classifier based on a gradient-boosted decision tree has been developed. It offers a significantly improved separation of signal and background muons compared to a similar classifier used for the analysis of the Run 2 data.

Original languageEnglish (US)
Article numberP04021
JournalJournal of Instrumentation
Volume20
Issue number4
DOIs
StatePublished - Apr 1 2025

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Mathematical Physics

Keywords

  • Data processing methods
  • Performance of High Energy Physics Detectors

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