Physics-aware Modeling of an Accelerated Particle Cloud
Emmanuel Goutierre ⋅ Hayg Guler ⋅ Christelle Bruni ⋅ Johanne Cohen ⋅ Michele Sebag
Abstract
Particle accelerator simulators, pivotal for acceleration optimization, are constrained by computational time.While current machine learning surrogate models for particle accelerator simulators offer efficiency, they lack in-depth positional data for individual particles.Drawing from 3D computer vision, we propose adapting the point cloud deep learning methods, adept at processing 3D point sets, to model particle beams.
Chat is not available.
Successful Page Load