Applications of Differentiable Physics Simulations in Particle Accelerator Modeling

2022/11/16 by Ryan Roussel, Roussel, Ryan, Auralee Edelen +1 · 2 citations
Engineering · #Accelerator Physics (physics.acc-ph) #FOS: Physical sciences #Particle Accelerators and Free-Electron Lasers #Particle accelerators and beam dynamics

paper · pdf · doi:10.48550/arxiv.2211.09077

openalex publication_date 2022/11/16 · openalex created_date 2023/02/15 · openalex updated_date 2026/07/28

Abstract

Current physics models used to interpret experimental measurements of particle beams require either simplifying assumptions to be made in order to ensure analytical tractability, or black box optimization methods to perform model based inference. This reduces the quantity and quality of information gained from experimental measurements, in a system where measurements have a limited availability. However differentiable physics modeling, combined with machine learning techniques, can overcome these analysis limitations, enabling accurate, detailed model creation of physical accelerators. Here we examine two applications of differentiable modeling, first to characterize beam responses to accelerator elements exhibiting hysteretic behavior, and second to characterize beam distributions in high dimensional phase spaces.

Cited by

• Study of fully coupled 3D envelope instability using automatic differentiation
• A multi-language auto-differentiation module and its application to a parallel particle-in-cell code on distributed computers

Related

• Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations
• Bridging the gap between machine learning and particle accelerator physics with high-speed, differentiable simulations
• Efficient 6-dimensional phase space reconstruction from experimental measurements using generative machine learning
• Differentiable simulations for particle tracking in accelerators: analysis, benchmarking and optimization
• Adaptive Machine Learning for Time-Varying Systems: Towards 6D Phase Space Diagnostics of Short Intense Charged Particle Beams