5 citations · 5 across the 2 of their papers we have counts for
2 papers
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…
physics.acc-ph2024★ 5 cited
Synthesizing Particle-in-Cell Simulations Through Learning and GPU Computing for Hybrid Particle Accelerator Beamlines
Ryan T. Sandberg, Remi Lehe, Chad E. Mitchell +5
Particle accelerator modeling is an important field of research and development, essential to investigating, designing and operating some of the most complex scientific devices eve…