3 papers
physics.acc-ph2025
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…
physics.acc-ph2024
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…
physics.acc-ph2024
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…