Cargando…
Machine Learning-Based Modeling of Muon Beam Ionization Cooling
Surrogate modeling can lead to significant improvements of beam dynamics simulations in terms of computational time and resources. Application of supervised machine learning, using collected simulation data allows to build surrogate models which can estimate beam parameters evolution based on the pr...
| Autores principales: | , , |
|---|---|
| Lenguaje: | eng |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.18429/JACoW-IPAC2022-WEPOMS046 http://cds.cern.ch/record/2845835 |