Speaker
Description
The CMS Pixel Detector in Run 3, with about 1400 silicon modules, is a central part of the Tracker, providing precise tracking and vertex reconstruction. Ensuring high quality data requires continuous monitoring, as modules can degrade or suffer operational issues. Traditionally, experts relied on a GUI that displayed histograms integrated over entire runs, making it difficult to spot short-lived or localized anomalies. This monitoring involved visually inspecting hundreds of histograms, a process that is slow and prone to human error. To address this, the DIALS platform was deployed in 2024 which now provides histograms at the Lumisection (LS) level - each LS representing roughly 23 seconds of data. This finer granularity enabled Machine Learning (ML) models, such as Non-negative Matrix Factorization (NMF), to identify brief anomalies, sometimes lasting only a minute, that previously went unnoticed. Removing these affected LS improves overall data quality while minimally impacting integrated luminosity. Integrating ML into the DQM workflow has thus improved anomaly detection, making Run 3 data certification faster and more reliable.