Detecting anomalous SRF cavity behavior with unsupervised learning

Detecting anomalous SRF cavity behavior with unsupervised learning

We present an unsupervised learning framework for detecting anomalous superconducting radio-frequency (SRF) cavity behavior at the Continuous Electron Beam Accelerator Facility (CEBAF), emphasizing its initial performance and effectiveness. Key to the system’s success was the development of data acq...

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Bibliographic Details
Main Authors: Hal Ferguson, Jiang Li, Adam Carpenter, Chris Tennant, Dillon Thomas, Dennis Turner
Format: Article
Language:English
Published: American Physical Society 2025-03-01
Series:Physical Review Accelerators and Beams
Online Access:http://doi.org/10.1103/PhysRevAccelBeams.28.034602
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