most citedDeveloping Robust Digital Twins and Reinforcement Learning for Accelerator Control Systems at the Fermilab Booster

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

physics.acc-ph2021★ 1 cited

Developing Robust Digital Twins and Reinforcement Learning for Accelerator Control Systems at the Fermilab Booster

D. Kafkes, M. Schram

We describe the offline machine learning (ML) development for an effort to precisely regulate the Gradient Magnet Power Supply (GMPS) at the Fermilab Booster accelerator complex vi…

physics.acc-ph2020

Real-time Artificial Intelligence for Accelerator Control: A Study at the Fermilab Booster

Jason St. John, Christian Herwig, Diana Kafkes +11

We describe a method for precisely regulating the gradient magnet power supply at the Fermilab Booster accelerator complex using a neural network trained via reinforcement learning…