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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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2025-03-01
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| Series: | Physical Review Accelerators and Beams |
| Online Access: | http://doi.org/10.1103/PhysRevAccelBeams.28.034602 |
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