Machine learning for beam dynamics studies at the CERN Large Hadron Collider

Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is only up until recently that Machine Learning has started to be...

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Detalles Bibliográficos
Autores principales: Arpaia, P., Azzopardi, G., Blanc, F., Bregliozzi, G., Buffat, X., Coyle, L., Fol, E., Giordano, F., Giovannozzi, M., Pieloni, T., Prevete, R., Redaelli, S., Salvachua, B., Salvant, B., Schenk, M., Solfaroli Camillocci, M., Tomás, R., Valentino, G., Van der Veken, F.F., Wenninger, J.
Lenguaje:eng
Publicado: 2020
Materias:
physics.acc-ph
Accelerators and Storage Rings
Acceso en línea:https://dx.doi.org/10.1016/j.nima.2020.164652
http://cds.cern.ch/record/2730823

Internet

https://dx.doi.org/10.1016/j.nima.2020.164652
http://cds.cern.ch/record/2730823

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