A. Dimitrov , M. Tytgat , K. Mota Amarilo , A. Samalan , K. Skovpen , G.A. Alves , E. Alves Coelho , F. Marujo da Silva , M. Barroso Ferreira Filho , E.M. Da Costa , D. De Jesus Damiao , S. Fonseca De Souza , R. Gomes De Souza , L. Mundim , H. Nogima , J.P. Pinheiro , A. Santoro , M. Thiel , A. Aleksandrov , R. Hadjiiska , J. Eysermans
{"title":"CMS RPC非物理事件数据自动化思想","authors":"A. Dimitrov , M. Tytgat , K. Mota Amarilo , A. Samalan , K. Skovpen , G.A. Alves , E. Alves Coelho , F. Marujo da Silva , M. Barroso Ferreira Filho , E.M. Da Costa , D. De Jesus Damiao , S. Fonseca De Souza , R. Gomes De Souza , L. Mundim , H. Nogima , J.P. Pinheiro , A. Santoro , M. Thiel , A. Aleksandrov , R. Hadjiiska , J. Eysermans","doi":"10.1016/j.nima.2025.170506","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents a streamlined framework for real-time processing and analysis of condition data from the CMS experiment Resistive Plate Chambers (RPC). Leveraging data streaming, it uncovers correlations between RPC performance metrics, like currents and rates, and LHC luminosity or environmental conditions. The Java-based framework automates data handling and predictive modeling, integrating extensive datasets into synchronized, query-optimized tables. By segmenting LHC operations and analyzing larger virtual detector objects, the automation enhances monitoring precision, accelerates visualization, and provides predictive insights, revolutionizing RPC performance evaluation and future behavior modeling.</div></div>","PeriodicalId":19359,"journal":{"name":"Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment","volume":"1076 ","pages":"Article 170506"},"PeriodicalIF":1.5000,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CMS RPC non-physics event data automation ideology\",\"authors\":\"A. Dimitrov , M. Tytgat , K. Mota Amarilo , A. Samalan , K. Skovpen , G.A. Alves , E. Alves Coelho , F. Marujo da Silva , M. Barroso Ferreira Filho , E.M. Da Costa , D. De Jesus Damiao , S. Fonseca De Souza , R. Gomes De Souza , L. Mundim , H. Nogima , J.P. Pinheiro , A. Santoro , M. Thiel , A. Aleksandrov , R. Hadjiiska , J. Eysermans\",\"doi\":\"10.1016/j.nima.2025.170506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper presents a streamlined framework for real-time processing and analysis of condition data from the CMS experiment Resistive Plate Chambers (RPC). Leveraging data streaming, it uncovers correlations between RPC performance metrics, like currents and rates, and LHC luminosity or environmental conditions. The Java-based framework automates data handling and predictive modeling, integrating extensive datasets into synchronized, query-optimized tables. By segmenting LHC operations and analyzing larger virtual detector objects, the automation enhances monitoring precision, accelerates visualization, and provides predictive insights, revolutionizing RPC performance evaluation and future behavior modeling.</div></div>\",\"PeriodicalId\":19359,\"journal\":{\"name\":\"Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment\",\"volume\":\"1076 \",\"pages\":\"Article 170506\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2025-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0168900225003079\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INSTRUMENTS & INSTRUMENTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168900225003079","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
CMS RPC non-physics event data automation ideology
This paper presents a streamlined framework for real-time processing and analysis of condition data from the CMS experiment Resistive Plate Chambers (RPC). Leveraging data streaming, it uncovers correlations between RPC performance metrics, like currents and rates, and LHC luminosity or environmental conditions. The Java-based framework automates data handling and predictive modeling, integrating extensive datasets into synchronized, query-optimized tables. By segmenting LHC operations and analyzing larger virtual detector objects, the automation enhances monitoring precision, accelerates visualization, and provides predictive insights, revolutionizing RPC performance evaluation and future behavior modeling.
期刊介绍:
Section A of Nuclear Instruments and Methods in Physics Research publishes papers on design, manufacturing and performance of scientific instruments with an emphasis on large scale facilities. This includes the development of particle accelerators, ion sources, beam transport systems and target arrangements as well as the use of secondary phenomena such as synchrotron radiation and free electron lasers. It also includes all types of instrumentation for the detection and spectrometry of radiations from high energy processes and nuclear decays, as well as instrumentation for experiments at nuclear reactors. Specialized electronics for nuclear and other types of spectrometry as well as computerization of measurements and control systems in this area also find their place in the A section.
Theoretical as well as experimental papers are accepted.