42 citations · 82 across the 6 of their papers we have counts for
7 papers
Applications of Differentiable Physics Simulations in Particle Accelerator Modeling
Ryan Roussel, Auralee Edelen
Current physics models used to interpret experimental measurements of particle beams require either simplifying assumptions to be made in order to ensure analytical tractability, o…
Neural Network Prior Mean for Particle Accelerator Injector Tuning
Connie Xu, Ryan Roussel, Auralee Edelen
Bayesian optimization has been shown to be a powerful tool for solving black box problems during online accelerator optimization. The major advantage of Bayesian based optimization…
Differentiable Preisach Modeling for Characterization and Optimization of Accelerator Systems with Hysteresis
R. Roussel, A. Edelen, D. Ratner +4
Future improvements in particle accelerator performance is predicated on increasingly accurate online modeling of accelerators. Hysteresis effects in magnetic, mechanical, and mate…
Multileaf Collimator for Real-Time Beam Shaping using Emittance Exchange
N. Majernik, G. Andonian, R. Roussel +5
Emittance exchange beamlines employ transverse masks to create drive and witness beams of variable longitudinal profile and bunch spacing. Recently, this approach has been used to…
Turn-Key Constrained Parameter Space Exploration for Particle Accelerators Using Bayesian Active Learning
Ryan Roussel, Juan Pablo Gonzalez-Aguilera, Young-Kee Kim +6
Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input par…
Longitudinal current profile reconstruction from wakefield response in plasmas and structures
Ryan Roussel, Gerard Andonian, James Rosenzweig +1
Present-day and next-generation accelerators, particularly for applications in driving wakefield-based schemes, require longitudinal beam shaping and attendant longitudinal charact…