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Data Augmentation for Breakdown Prediction in CLIC RF Cavities
One of the primary limitations on the achievable accelerating gradient in normal-conducting accelerator cavities is the occurrence of vacuum arcs, also known as RF breakdowns. A recent study on experimental data from the CLIC XBOX2 test stand at CERN proposes the use of supervised machine learning m...
| Autores principales: | , , , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.18429/JACoW-IPAC2022-TUPOMS054 http://cds.cern.ch/record/2845799 |