activity
20232026
most citedCheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations

31 citations · 40 across the 4 of their papers we have counts for

collaborators
Showing 2026Show all

1 paper · 1 filter

physics.acc-ph2026

The Memory Scaling of Reverse-Mode Differentiation in Particle Accelerator Simulations with Space Charge

Arjun Dhamrait, Edoardo Zoni, Axel Huebl +7

The recent development of differentiable simulation codes for particle accelerators has enabled gradient-based workflows that promise finer control and more realistic modeling of a…