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arxiv 2504.08991 v1 pith:PBVMQKE6 submitted 2025-04-11 hep-ex physics.ins-det

CMS RPC Non-Physics Event Data Automation Ideology

classification hep-ex physics.ins-det
keywords dataautomationframeworkmodelingperformancepredictiveacceleratesanalysis
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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