The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1 × 1034 cm-2s-1, twice the initial design value, at √(s)=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.

Performance of the CMS high-level trigger during LHC Run 2

Alexe, C.;Bruschini, D.;
2024

Abstract

The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1 × 1034 cm-2s-1, twice the initial design value, at √(s)=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.
2024
Settore PHYS-01/A - Fisica sperimentale delle interazioni fondamentali e applicazioni
Large detector systems for particle and astroparticle physics; Trigger concepts and systems (hardware and software)
   Advanced Multi-Variate Analysis for New Physics Searches at the LHC
   AMVA4NewPhysics
   European Commission
   Horizon 2020 Framework Programme
   675440

   Search for Higgs bosons decaying to charm quarks
   HIGCC
   European Commission
   Horizon 2020 Framework Programme
   724704

   Direct and indirect searches for new physics in events with top quarks using LHC proton-proton collisions at the CMS detector
   LHCTOPVLQ
   European Commission
   Horizon 2020 Framework Programme
   752730

   Majorana neutrino discovery strategy with CMS
   MajorNet
   European Commission
   Horizon 2020 Framework Programme
   758316

   International Training Network for Statistics in High Energy Physics and Society
   INSIGHTS
   European Commission
   Horizon 2020 Framework Programme
   765710

   The strong interaction at the frontier of knowledge: fundamental research and applications
   STRONG-2020
   European Commission
   Horizon 2020 Framework Programme
   824093

   INnovative TRiggEr techniques for beyond the standard model PhysIcs Discovery at the LHC
   INTREPID
   European Commission
   Horizon Europe Framework Programme
   101115353

   Fundamental properties and time-scan of QCD matter at high densities and temperature exposed by jet substructure in heavy ion collisions with CMS experiment at the LHC
   QCDHighDensityCMS
   European Commission
   Horizon 2020 Framework Programme
   101002207
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/154952
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