CERN Accelerating science

CMS Detector Performance Summaries

Ultimi arrivi:
2022-05-16
15:44
Performance of electron energy calibration in the CMS ECAL using graph neural networks /CMS Collaboration
The Compact Muon Solenoid (CMS) detector is one of two general-purpose detectors on the energy frontier of particle physics at the CERN Large Hadron Collider (LHC). Products of proton-proton collisions at a center of mass energy of 13 TeV are reconstructed in the CMS detector to probe the standard model of particle physics, and to search for processes beyond the standard model. [...]
CMS-DP-2022-009; CERN-CMS-DP-2022-009.- Geneva : CERN, 2022 - 17 p. Fulltext: PDF;

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2022-05-09
12:48
First results from LHC October pilot beam test and laboratory measurements using BCM1F luminometer /CMS Collaboration
To achieve the required high luminosity precision during the Run 3 LHC operations, the fast Beam Condition Monitor (BCM1F) was upgraded. It was rebuilt with new sensors, produced as a part of the Phase 2 Outer Tracker sensor production. [...]
CMS-DP-2022-008; CERN-CMS-DP-2022-008.- Geneva : CERN, 2022 - 12 p. Fulltext: PDF;

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2022-05-02
13:37
ECAL trigger for Run 3
The ECAL trigger team has been investigating the potential use of a second set of L1 amplitude weights. The first set of weights is optimized to provide the correct amplitude for in-time signals. [...]
CMS-DP-2022-007; CERN-CMS-DP-2022-007.- Geneva : CERN, 2022 - 24 p. Fulltext: PDF;

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2022-04-11
15:09
Performance of low-$\text{E}_{\text{T}}$ electrons and photons using 2018 ultraperipheral PbPb /CMS Collaboration
This note presents the performance of low-$\text{E}_{\text{T}}$ electrons and photons, optimized for lead-lead (PbPb) ultraperipheral collisions recorded in 2018 by the CMS experiment. The energy scale and resolution of electromagnetic superclusters are shown, as well as the electron reconstruction+identification and Level-1 electromagnetic cluster efficiencies. [...]
CMS-DP-2022-006; CERN-CMS-DP-2022-006.- Geneva : CERN, 2022 - 10 p. Fulltext: PDF;

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2022-04-01
11:59
High Granularity Calorimeter Reconstruction Results using a Graph Neural Network /CMS Collaboration
We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based reconstruction. The model used is based on graph Neural Networks (GNNs) and analyzes the hits in each HGCAL endcap. [...]
CMS-DP-2022-004; CERN-CMS-DP-2022-004.- Geneva : CERN, 2022 - 13 p. Fulltext: PDF;

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2022-04-01
11:58
CLUE: a clustering algorithm for current and future experiments
CLUE (CLUstering of Energy) is a fast parallel clustering algorithm for High Granularity Calorimeters in High Energy Physics. In these types of detectors, such as that to be built to cover the endcap region in the CMS Phase-2 Upgrade for HL-LHC, the standard clustering algorithms using combinatorics are expected to fail due to large number of digitised energy deposits (hits) in the reconstruction stage bringing to a consequent memory/timing explosion. This innovative algorithm uses a grid spatial index for fast querying of neighbours and its timing scales linearly with the number of hits within the range considered. [...]
CMS-DP-2022-003; CERN-CMS-DP-2022-003.- Geneva : CERN, 2022 - 16 p. Fulltext: PDF;

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2022-04-01
11:58
Trackster ID and cleaning for EM iterations /CMS Collaboration
The Iterative Clustering (TICL) is a modular framework developed for iteratively reconstructing particles in the high granularity calorimeter (HGCAL) which will be installed in the endcaps of CMS for Phase II of the LHC. This note reports on the development of algorithms which improve the purity of the electromagnetic (EM) iteration in TICL in the presence of pile up (PU). [...]
CMS-DP-2022-002; CERN-CMS-DP-2022-002.- Geneva : CERN, 2022 - 10 p. Fulltext: PDF;

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2022-04-01
10:15
Calibration of the mass-decorrelated ParticleNet tagger for boosted $\mathrm{b}\bar{\mathrm{b}}$ and $\mathrm{c}\bar{\mathrm{c}}$ jets using LHC Run 2 data /CMS Collaboration
The calibration of the new generation jet tagging algorithms exploiting advanced machine learning techniques becomes a challenging task. This note presents a novel approach for the calibration of the mass-decorrelated ParticleNet (ParticleNet-MD) boosted jet flavour tagging algorithm, focusing on the $\mathrm{X} \rightarrow \mathrm{b}\bar{\mathrm{b}}$ and $\mathrm{X} \rightarrow \mathrm{c}\bar{\mathrm{c}}$ mode. [...]
CMS-DP-2022-005; CERN-CMS-DP-2022-005.- Geneva : CERN, 2022 - 15 p. Fulltext: PDF;

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2022-02-15
17:08
DT Slice Test 2021 Calibration Stability plots /CMS Collaboration
A "Slice Test", corresponding to one sector of the CMS Drift Tube (DT) detector, was installed during the LHC Shut Down 2, to develop and test the DT electronics designed for LHC Run 4 (Phase 2). An accurate calibration of the produced signals is needed to guarantee the optimal time resolution of future Local Trigger. [...]
CMS-DP-2022-001; CERN-CMS-DP-2022-001.- Geneva : CERN, 2022 - 11 p. Fulltext: PDF;

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2022-01-27
14:37
New opportunities of heavy ion physics with CMS-MTD at the HL-LHC
The document presents full simulation results on new opportunities of heavy ion physics with CMS-MTD at the HL-LHC, with a broad range of observables..
CMS-DP-2021-037; CERN-CMS-DP-2021-037.- Geneva : CERN, 2021 - 29 p. Fulltext: PDF;

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