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)
licence : Domaine public
licence : Domaine public
