41 citations · 81 across the 6 of their papers we have counts for
6 papers
Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements
Seongyeol Kim, Juan Pablo Gonzalez-Aguilera, Ryan Roussel +7
Understanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse d…
Efficient 6-dimensional phase space reconstruction from experimental measurements using generative machine learning
Ryan Roussel, Juan Pablo Gonzalez-Aguilera, Auralee Edelen +5
Next-generation accelerator concepts which hinge on the precise shaping of beam distributions, demand equally precise diagnostic methods capable of reconstructing beam distribution…
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…
Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations
Ryan Roussel, Auralee Edelen, Christopher Mayes +5
Characterizing the phase space distribution of particle beams in accelerators is a central part of accelerator understanding and performance optimization. However, conventional rec…
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…
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…