J. P. Gonzalez-Aguilera

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations

D. Ratner, R. Roussel, J. Power, 2022, 2209.04505.

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Young-Kee Kim, Wanming Liu, A. Hanuka, 2021, Nature Communications.

Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis.

R. Roussel, Y. K. Kim, D. Ratner, 2022, Physical Review Letters.

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations.

D. Ratner, R. Roussel, J. Power, 2022, Physical Review Letters.

Efficient 6-dimensional phase space reconstruction from experimental measurements using generative machine learning

Wanming Liu, E. Wisniewski, A. Edelen, 2024, 2404.10853.

Four-Dimensional Phase-Space Reconstruction of Flat and Magnetized Beams Using Neural Networks and Differentiable Simulations

Wanming Liu, R. Roussel, E. Wisniewski, 2024, 2402.18244.

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations.

D. Ratner, R. Roussel, J. Power, 2022, Physical review letters.