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Abstract The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online data quality monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. A real-time autoencoder-based anomaly detection system using semi-supervised machine learning is presented enabling the detection of anomalies in the CMS electromagnetic calorimeter data. A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. The autoencoder-based system is able to efficiently detect anomalies, while maintaining a very low false discovery rate. The performance of the system is validated with anomalies found in 2018 and 2022 LHC collision data. In addition, the first results from deploying the autoencoder-based system in the CMS online data quality monitoring workflow during the beginning of Run 3 of the LHC are presented, showing its ability to detect issues missed by the existing system.
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This content will become publicly available on August 1, 2027
The CLAS12 RICH detector
The CLAS12 RICH detector installed in the Hall B of the Jefferson Laboratory has been designated to provide clean kaon identification in the momentum range from 3 to 8 GeV/c. The detector adopted a novel hybrid design, with aerogel radiator, a system of planar and spherical mirrors and a highly segmented readout system based on multi-anode photomultipliers. We present here the status of the detector and its performance after a few years of operation.
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- Award ID(s):
- 2310067
- PAR ID:
- 10697152
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
- Volume:
- 1088
- Issue:
- C
- ISSN:
- 0168-9002
- Page Range / eLocation ID:
- 171470
- Subject(s) / Keyword(s):
- High energy physics Cherenkov detectors Particle identification
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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