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Using Machine Learning to Improve Dynamic Aperture Estimates
The dynamic aperture (DA) is an important concept in the study of nonlinear beam dynamics. Several analytical models used to describe the evolution of DA as a function of time, and to extrapolate to realistic time scales that would not be reachable otherwise due to computational limitations, have be...
| Autores principales: | , , , , |
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| Lenguaje: | eng |
| Publicado: |
JACoW
2021
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.18429/JACoW-IPAC2021-MOPAB028 http://cds.cern.ch/record/2804876 |