Explainable Machine Learning for Breakdown Prediction in High Gradient RF Cavities

The occurrence of vacuum arcs or radio frequency (rf) breakdowns is one of the most prevalent factors limiting the high-gradient performance of normal conducting rf cavities in particle accelerators. In this paper, we search for the existence of previously unrecognized features related to the incide...

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Detalles Bibliográficos
Autores principales: Obermair, Christoph, Cartier-Michaud, Thomas, Apollonio, Andrea, Millar, William, Felsberger, Lukas, Fischl, Lorenz, Bovbjerg, Holger Severin, Wollmann, Daniel, Wuensch, Walter, Catalan-Lasheras, Nuria, Boronat, Marçà, Pernkopf, Franz, Burt, Graeme
Lenguaje:eng
Publicado: 2022
Materias:
cs.LG
Computing and Computers
physics.acc-ph
Accelerators and Storage Rings
Acceso en línea:https://dx.doi.org/10.1103/PhysRevAccelBeams.25.104601
http://cds.cern.ch/record/2803014

Internet

https://dx.doi.org/10.1103/PhysRevAccelBeams.25.104601
http://cds.cern.ch/record/2803014

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