CERN Accelerating science

CMS Detector Performance Summaries

Darreres entrades:
2026-06-24
17:27
Evolution of the HLT Scouting of the CMS experiment in 2022 -- 2026 during LHC Run 3: statistics /CMS Collaboration
Data scouting is a CMS data-taking strategy that uses trigger-level reconstruction to record compact event information at the High Level Trigger (HLT), enabling higher acquisition rates and looser selections than standard triggers. First tested in Run 1 for low-mass dijet searches, scouting was expanded in Run 2 with both hadronic and muon-based paths, using Calo and Particle-Flow (PF) event content. [...]
CMS-DP-2026-097; CERN-CMS-DP-2026-097.- Geneva : CERN, 2026 - 1 p. Fulltext: PDF;

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2026-06-24
17:27
Output rates and bandwiths of the High-Level Trigger during 2025 & 2026 PbPb runs /CMS Collaboration
This note presents the output rates and bandwidth of the CMS High-Level Trigger during 2025 and 2026 PbPb runs. The results are shown for representative fills from November 2025 and May 2026, at the nominal luminosity leveling..
CMS-DP-2026-094; CERN-CMS-DP-2026-094.- Geneva : CERN, 2026 - 1 p. Fulltext: PDF;

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2026-06-24
17:12
Identifying Quenched Jets in CMS Using Machine Learning /CMS Collaboration
Jet quenching is a phenomenon in heavy-ion collisions arising from interactions between jets and the quark-gluon plasma (QGP). Modifications of jet-quenching observables result from multiple physical processes, while underlying-event backgrounds and detector effects can significantly influence these observables and must be properly accounted for when identifying quenched jets. [...]
CMS-DP-2026-095; CERN-CMS-DP-2026-095.- Geneva : CERN, 2026 - 1 p. Fulltext: PDF;

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2026-06-01
08:07
ECAL performance with prompt reconstructed 2025 data and ECAL alignment in 2026 /CMS Collaboration
ECAL performance with prompt reconstructed 2025 data and ECAL alignment in 2026..
CMS-DP-2026-060; CERN-CMS-DP-2026-060.- Geneva : CERN, 2026 - 26 p. Fulltext: PDF;

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2026-05-29
14:37
Validation of HGCAL TPG Stage1 Trigger Cell (TC) processor using test-beam data /CMS Collaboration
The HGCAL test beam data has been crucial to validate detector instrumentation, data collections and detector performance. The HGCAL Trigger Primitive Generation (TPG) activities were focussed on backend data flow and validation of TPG emulation. [...]
CMS-DP-2026-059; CERN-CMS-DP-2026-059.- Geneva : CERN, 2026 - 8 p. Fulltext: PDF;

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2026-05-29
14:37
Data quality monitoring of the preseries cassettes of the CMS High Granularity Calorimeter /CMS Collaboration
This note reports on the data quality monitoring (DQM) of the pre-series cassettes of the CMS High Granularity Calorimeter (HGCAL) during their commissioning. The procedure involves exercising the full control, trigger, data acquisition and offline software chains. [...]
CMS-DP-2026-058; CERN-CMS-DP-2026-058.- Geneva : CERN, 2026 - 17 p. Fulltext: PDF;

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2026-05-29
14:37
GNN-based end-to-end reconstruction in the CMS Phase-2 High-Granularity Calorimeter /CMS Collaboration
In this note, the first application of a one-pass, Machine Learning (ML) based imaging calorimeter reconstruction approach to the latest full CMS High-Granularity Calorimeter (HGCAL) simulation is presented. The model is a Graph Neural Network (GNN) that directly processes the hits in the High Granularity Calorimeter (HGCAL), one of the most important upgrades of the Compact Muon Solenoid detector in preparation for the High-Luminosity phase of the Large Hadron Collider planned to begin operations in 2030. The network is trained to group hits originating from the same incident particle by assigning them to a common cluster. The accuracy of the reconstruction is evaluated through physics-inspired metrics that quantify how accurately the properties of individual particles are measured. The algorithm is studied using simulations of different particle types in HGCAL and its performance is tested in single-particle environments. While this exploratory study uses zero pile-up simulations and thus does not fully reflect expected detector performance, the results shown in this note demonstrate the viability of an end-to-end, ML-based reconstruction framework for the HGCAL..
CMS-DP-2026-057; CERN-CMS-DP-2026-057.- Geneva : CERN, 2026 - 17 p. Fulltext: PDF;

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2026-05-29
14:37
HGCal Silicon modules at different absorbed doses /CMS Collaboration
Several set of modules have been irradiated to study the hybrid assembly approach transfer tape + epoxy for the HGCal silicon modules. In these slides, modules with different shapes, baseplate materials, sensor thicknesses and density, HGCROC readout electronic version (due to availability), have been built at University of California Santa Barbara (UCSB) and National Taiwan University (NTU), then they have been irradiated to different absorbed doses in a Co-60 facility in Croatia to study robustness of the assembly method at different expected level of absorbed dose. After irradiation, all modules have been measured and thermal cycled at UCSB. [...]
CMS-DP-2026-056; CERN-CMS-DP-2026-056.- Geneva : CERN, 2026 - 25 p. Fulltext: PDF;

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2026-05-29
14:37
Results from HGCAL beam tests of 2025 for the scintillator setup /CMS Collaboration
As part of its HL-LHC upgrade program, the CMS experiment is developing a High Granularity Calorimeter (HGCAL) to replace the existing endcap calorimeters. The HGCAL will be realized as a sampling calorimeter equipped with modules of silicon or scintillator tiles read out by SiPMs. [...]
CMS-DP-2026-055; CERN-CMS-DP-2026-055.- Geneva : CERN, 2026 - 15 p. Fulltext: PDF;

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2026-05-29
14:37
Results from HGCAL beam tests of 2025 for the silicon setup /CMS Collaboration
As part of its HL-LHC upgrade program, the CMS experiment is developing a High Granularity Calorimeter (HGCAL) to replace the existing endcap calorimeters. The HGCAL will be realized as a sampling calorimeter equipped with modules of silicon or scintillator tiles read out by SiPMs. [...]
CMS-DP-2026-054; CERN-CMS-DP-2026-054.- Geneva : CERN, 2026 - 27 p. Fulltext: PDF;

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