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CMS Preprints

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2025-03-06
05:43
Luminosity measurement for lead-lead collisions at $ \sqrt{\smash[b]{s_{_{\mathrm{NN}}}}}= $ 5.02 TeV in 2015 and 2018 at CMS
Measurements of the luminosity delivered to the CMS experiment during the lead-lead data-taking periods in 2015 and 2018 are presented for the first time. [...]
CERN-EP-2025-018 ; CMS-LUM-20-002-003. - 2025
Additional information for the analysis - CMS AuthorList - Fulltext

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2025-03-04
06:57
Observation of the charged-particle multiplicity dependence of $ \sigma_{\psi(2\text{S})} /\sigma_{\mathrm{J}/\psi} $ in pPb collisions at 8.16 TeV
Bound states of charm and anticharm quarks, known as charmonia, have a rich spectroscopic structure that can be used to probe the dynamics of hadron production in high-energy hadron collisions. [...]
CERN-EP-2025-006 ; CMS-HIN-24-001-003. - 2025
Additional information for the analysis - CMS AuthorList - Fulltext

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2025-02-28
15:56
CMS Outer Tracker Module Production and Integration at NISER / Rahul Kumar Agrawal
In the LHC long shutdown 3, due to start in mid-2026, the LHC will be upgraded to the High-Luminosity LHC. To address the challenges for operation at the HL-LHC, such as an increased interaction rate and higher radiation levels, an upgrade of the tracking system of the CMS detector is being built. [...]
CMS-CR-2025-031.- Geneva : CERN, 2025 - 5 p. Fulltext: PDF;
In : 26th DAE-BRNS High Energy Physics Symposium 2024, Varanasi, India, 19 - 23 Dec 2024

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2025-02-28
15:52
Advanced monitoring capabilities of the CMS Experiment for LHC Run3 and beyond / Legger, Federica (INFN, Turin) ; Tuckus, Nikodemas (CERN) ; Brij Kishor Jashal /CMS Collaboration
The CMS computing infrastructure spread globally over 150 WLCG sites forms a intricate ecosystem of computing resources, software and services. In 2024, the production computing cores breached half a million mark and storage capacity is at 250 PetaBytes on disk and 1.20 ExaBytes on Tape. [...]
CMS-CR-2025-074.- Geneva : CERN, 2025 - 7 p. Fulltext: PDF;
In : 42nd International Conference on High Energy Physics (ICHEP 2024), Prague, Czech Republic, 18 - 24 Jul 2024

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2025-02-28
15:52
Optimization of distributed compute resources utilization in the CMS Global Pool / Mascheroni, Marco (UC, San Diego) ; Perez-Calero Yzquierdo, Antonio Maria (Madrid, CIEMAT) ; Kim, Hyunwoo (Fermilab) ; Florian Von Cube ; Zokaite, Vaiva (Vilnius U.) ; Frank Wurthwein /CMS Collaboration
The CMS Submission Infrastructure is the primary system for managing computing resources for CMS workflows, including data processing, simulation, and analysis. It integrates geographically distributed resources from Grid, HPC, and cloud providers into federated pools managed by HTCondor and GlideinWMS, for a total of around 500k CPU cores. [...]
CMS-CR-2025-071.- Geneva : CERN, 2025 - 9 p. Fulltext: PDF;
In : 42nd International Conference on High Energy Physics (ICHEP 2024), Prague, Czech Republic, 18 - 24 Jul 2024

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2025-02-28
15:52
Commissioning and exploitation of the MareNostrum5 cluster at the Barcelona Supercomputing Center for CMS computing / Delgado Peris, Antonio (Madrid, CIEMAT) ; Flix Molina, Jose (Madrid, CIEMAT) ; Hernandez, Jonathan Matthew (UC, San Diego) ; Perez-Calero Yzquierdo, Antonio Maria (Madrid, CIEMAT) /CMS Collaboration
The MareNostrum 5 (MN5) is the newly deployed pre-exascale EuroHPC supercomputer hosted at the Barcelona Supercomputing Center (BSC) in Spain. Its 750,000-core general-purpose CPU cluster offers new opportunities for CMS data processing and simulation but also presents integration challenges within the CMS distributed computing system, particularly due to network segregation for compute nodes. [...]
CMS-CR-2025-069.- Geneva : CERN, 2025 - 9 p. Fulltext: PDF;
In : 42nd International Conference on High Energy Physics (ICHEP 2024), Prague, Czech Republic, 18 - 24 Jul 2024

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2025-02-28
15:51
R and D Adoption and Progress in Full Simulation of the CMS experiment / Srimanobhas, Norraphat (Chulalongkorn U.) ; Banerjee, Sunanda (Wisconsin U., Madison) ; Cossutti, Fabio (INFN, Trieste) ; Ivantchenko, Vladimir (Dubna, JINR) ; Krammer, Natascha (Vienna, OAW) ; Muzaffar, M. S ; Pedro, Kevin Jerome (Fermilab) ; Pezzotti, L /CMS Collaboration
In this work we report on evolution of usage of Geant4 within CMSSW and adaptation of the newest Geant4 11.2.1, which is expected to be used for CMS simulation production in 2025. Physics validation results and results on CPU performance are reported. [...]
CMS-CR-2025-059.- Geneva : CERN, 2025 - 9 p. Fulltext: PDF;
In : 42nd International Conference on High Energy Physics (ICHEP 2024), Prague, Czech Republic, 18 - 24 Jul 2024

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2025-02-28
15:51
Migration of CADI to Fence / Imran, Muhammad (Quaid-i-Azam U.) ; Pfeiffer, Andreas (CERN) ; Rao Muhammad Atif Shad ; Joel Closier ; Samantas, Athanasios (CERN) ; Misha Urooj Khan /CMS Collaboration
CMS Analysis Database Interface (CADI) is a management tool for physics publications in the CMS experiment. It acts as a central database for the CMS collaboration, keeping track of the various analysis projects being conducted by researchers. [...]
CMS-CR-2025-053.- Geneva : CERN, 2025 - 9 p. Fulltext: PDF;
In : 42nd International Conference on High Energy Physics (ICHEP 2024), Prague, Czech Republic, 18 - 24 Jul 2024

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2025-02-28
15:51
Orchestrated columnar-based analysis with columnflow / Frahm, Mathis (Hamburg U.) /CMS Collaboration
\textit{Columnflow} is a tool for columnar-based data analysis. It is written in \textit{Python}, experiment-agnostic in its core, and supports any flat $n$-tuple format, such as \textit{ROOT}-based \textit{TTrees} or \textit{Parquet} files. [...]
CMS-CR-2025-051.- Geneva : CERN, 2025 - 8 p. Fulltext: PDF;
In : 42nd International Conference on High Energy Physics (ICHEP 2024), Prague, Czech Republic, 18 - 24 Jul 2024

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2025-02-28
15:51
Development of machine-learning based app for anomaly detection in CMSWEB / Imran, Muhammad (Quaid-i-Azam U.) /CMS Collaboration
This paper presents an anomaly detection system for CMSWEB services, a critical component of CMS infrastructure supporting over two dozen web services. The system employs deep learning techniques to enhance service performance and reliability by detecting anomalies in real time. [...]
CMS-CR-2025-049.- Geneva : CERN, 2025 - 9 p. Fulltext: PDF;
In : 42nd International Conference on High Energy Physics (ICHEP 2024), Prague, Czech Republic, 18 - 24 Jul 2024

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