Search Results for author: Tom Powers

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Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory

no code implementations11 Jun 2020 Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin

We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab.

BIG-bench Machine Learning General Classification +2

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