Physics-aware modelling of an accelerated particle cloud
Résumé
Particle accelerator simulators, pivotal for acceleration optimization, are computationally heavy; surrogate, machine learning-based models are thus trained to facilitate the accelerator fine-tuning. While these current models are efficient, they do not allow for simulating the beam at the individual particle-level. This paper adapts point cloud deep learning methods, developed for computer vision, to model particle beams.
| Origine | Fichiers produits par l'(les) auteur(s) |
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| licence |
Domaine public
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