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physics.acc-ph2025
Explainable physics-based constraints on reinforcement learning for accelerator controls
Jonathan Colen, Malachi Schram, Kishansingh Rajput +1
We present a reinforcement learning (RL) framework for controlling particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is…
physics.acc-ph2024
Harnessing the Power of Gradient-Based Simulations for Multi-Objective Optimization in Particle Accelerators
Kishansingh Rajput, Malachi Schram, Auralee Edelen +6
Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-Objective Optimization (MOO) is particularly challenging due to trade-offs between t…