42 citations · 82 across the 8 of their papers we have counts for
10 papers · 1 filter
Controls Abstraction Towards Accelerator Physics: A Middle Layer Python Package for Particle Accelerator Control
M. King, A. D. Brynes, F. Jackson +11
Control system middle layers act as a co-ordination and communication bridge between end users, including operators, system experts, scientists, and experimental users, and the low…
Four-Dimensional Phase-Space Reconstruction of Flat and Magnetized Beams Using Neural Networks and Differentiable Simulations
Seongyeol Kim, Juan Pablo Gonzalez-Aguilera, Philippe Piot +9
Beams with cross-plane coupling or extreme asymmetries between the two transverse phase spaces are often encountered in particle accelerators. Flat beams with large transverse-emit…
Demonstration of Autonomous Emittance Characterization at the Argonne Wakefield Accelerator
Ryan Roussel, Auralee Edelen, Dylan Kennedy +3
Transverse beam emittance plays a key role in the performance of high brightness accelerators. Characterizing beam emittance is often done using a quadrupole scan, which fits beam…
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…