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CMS Detector Performance Summaries

新增:
2022-08-15
11:07
A new back-propagation method for the CMS GEM chamber alignment with six misalignment parameters /CMS Collaboration
The next phase of high luminosity LHC (HL-LHC) foresees and increases the instantaneous luminosity in order to extend the discovery potential of the detector. In order to meet the increased particle rates and to ensure a robust and redundant system, CMS is adding new detector layers in the forward region of the muon system along with other upgrades. [...]
CMS-DP-2022-028; CERN-CMS-DP-2022-028.- Geneva : CERN, 2022 - 12 p. Fulltext: PDF;

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2022-07-20
13:57
The CMS GEM alignment with a new back-propagation method /CMS Collaboration
The next phase of high luminosity LHC (HL-LHC) foresees and increases the instantaneous luminosity in order to extend the discovery potential of the detector. In order to meet the increased particle rates and to ensure a robust and redundant system, CMS is adding new detector layers in the forward region of the muon system along with other upgrades. [...]
CMS-DP-2022-027; CERN-CMS-DP-2022-027.- Geneva : CERN, 2022 - 11 p. Fulltext: PDF;

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2022-07-20
13:57
Pixel Detector Performance in 2021 /CMS Collaboration
The performance of the CMS pixel detector during 900 GeV collisions recorded in 2021 is presented..
CMS-DP-2022-026; CERN-CMS-DP-2022-026.- Geneva : CERN, 2022 - 12 p. Fulltext: PDF;

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2022-07-11
12:49
Update of the MTD physics case /CMS Collaboration
The physics case for a Mip Timing detector in CMS was presented in CMS-TDR-020. An update is provided, extending the coverage for different scenarios for Barrel Timing Layer resolution, particle identification (PID) performance assessment and its application to b physics..
CMS-DP-2022-025; CERN-CMS-DP-2022-025.- Geneva : CERN, 2022 - 16 p. Fulltext: PDF;

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2022-07-11
12:49
Illustration of the performance of the CMS tracker and reconstruction on early Run 3 data, on the example of D* meson reconstruction
In this note some of the first distributions from CMS Run 3, showing a signal for charm production in Minimum Bias data taken at the injection center-of-mass energy of 900 GeV, are shown as an illustration of the readiness of CMS for data taking in Run 3, with particular focus on the tracker, tracking, and vertexing performance at low transverse momenta..
CMS-DP-2022-024; CERN-CMS-DP-2022-024.- Geneva : CERN, 2022 - 10 p. Fulltext: PDF;

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2022-07-11
12:49
Background studies in the CMS muon system /CMS Collaboration
The plots in this DPS are a first set of plots that will be part of a dedicated paper of the CMS Muon Collaboration discussing the backgrounds observed in the muon detectors during Run-2..
CMS-DP-2022-023; CERN-CMS-DP-2022-023.- Geneva : CERN, 2022 - 28 p. Fulltext: PDF;

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2022-07-11
12:43
$\pi^{-}$ energy reconstruction in HGCAL Beam Test prototype detector using Graph Neural Networks /CMS Collaboration
The current CMS endcap calorimeter will be replaced by a high granularity sampling calorimeter (HGCAL) for the high luminosity operation of the LHC. The HGCAL is a sampling calorimeter based on silicon sensors and scintillator tiles directly readout by SiPMs for the active media with very fine transverse and longitudinal granularity. [...]
CMS-DP-2022-022; CERN-CMS-DP-2022-022.- Geneva : CERN, 2022 - 16 p. Fulltext: PDF;

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2022-07-04
13:34
Neural network-based algorithm for the identification of bottom quarks in the CMS Phase-2 Level-1 trigger /CMS Collaboration
The Phase-2 upgrade of the CMS detector for the High Luminosity upgrade of the LHC (HL-LHC) includes the introduction of many new capabilities into the Level-1 trigger, including tracking and the new high- granularity calorimeter. The inclusion of tracking in particular offers the possibility of developing an algorithm to identify jets originating from bottom quarks (b-tagging) for use in the Level-1 trigger for the first time at CMS. [...]
CMS-DP-2022-021; CERN-CMS-DP-2022-021.- Geneva : CERN, 2022 - 20 p. Fulltext: PDF;

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2022-07-04
13:34
Performance Plots Showing the Effect of Different Cuts and Weighting in the Baseline Approach and a Technical Plot Showing the Effects of Pruning and Quantisation of the End-to-End Neural Network Approach to Phase-2 Level-1 Trigger Primary Vertex Reconstruction /CMS Collaboration
The Phase-2 upgrade of the Level-1 (L1) Trigger will see tracker tracks reconstructed and passed down to global triggering algorithms such as primary vertex (PV) finding. This will be used to associate tracks and other trigger objects to the PV in an event, reducing the impact of pile-up (PU) and increasing trigger performance in certain scenarios. [...]
CMS-DP-2022-020; CERN-CMS-DP-2022-020.- Geneva : CERN, 2022 - 11 p. Fulltext: PDF;

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2022-06-30
11:51
Performance of Run-3 HLT Track Reconstruction /CMS Collaboration
This note reports on track and vertex reconstruction in the context of HLT at LHC Run-3..
CMS-DP-2022-014; CERN-CMS-DP-2022-014.- Geneva : CERN, 2022 - 37 p. Fulltext: PDF;

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