Skip to main navigation Skip to search Skip to main content

Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at (Formula presented)

  • CMS Collaboration
  • A. Alikhanian Yerevan Institute of Physics
  • Yerevan State University
  • Austrian Academy of Sciences
  • TU Wien
  • University of Antwerp
  • Vrije Universiteit Brussel
  • Université libre de Bruxelles

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Measurements in the highly Lorentz-boosted regime provoke increased interest in probing the Higgs boson properties and in searching for particles beyond the standard model at the LHC. In the CMS Collaboration, various boosted-object tagging algorithms, designed to identify hadronic jets originating from a massive particle decaying to (Formula presented) or (Formula presented), have been developed and deployed across a range of physics analyses. This paper highlights their performance on simulated events, and summarizes novel calibration techniques using proton-proton collision data collected at (Formula presented) during the 2016–2018 LHC data-taking period. Three dedicated methods are used for the calibration in multijet events, leveraging either machine learning techniques, the presence of muons within energetic boosted jets, or the reconstruction of hadronically decaying high-energy Z bosons. The calibration results, obtained through a combination of these approaches, are presented and discussed.

Original languageEnglish
Article numberP11006
JournalJournal of Instrumentation
Volume20
Issue number11
DOIs
StatePublished - Nov 1 2025

Keywords

  • calibration and fitting methods
  • cluster finding
  • Pattern recognition
  • Performance of High Energy Physics Detectors

Fingerprint

Dive into the research topics of 'Performance of heavy-flavour jet identification in Lorentz-boosted topologies in proton-proton collisions at (Formula presented)'. Together they form a unique fingerprint.

Cite this