151 citations · 464 across the 35 of their papers we have counts for
3 papers · 1 filter
Multi-Objective Bayesian Optimization for Accelerator Tuning
Ryan Roussel, Adi Hanuka, Auralee Edelen
Particle accelerators require constant tuning during operation to meet beam quality, total charge and particle energy requirements for use in a wide variety of physics, chemistry a…
Physics-informed Gaussian Process for Online Optimization of Particle Accelerators
Adi Hanuka, X. Huang, J. Shtalenkova +5
High-dimensional optimization is a critical challenge for operating large-scale scientific facilities. We apply a physics-informed Gaussian process (GP) optimizer to tune a complex…
Advanced Control Methods for Particle Accelerators (ACM4PA) 2019 Workshop Report
Alexander Scheinker, Claudio Emma, Auralee L. Edelen +1
Los Alamos is currently developing novel particle accelerator controls and diagnostics algorithms to enable higher quality beams with lower beam losses than is currently possible.…