First Steps Toward an Autonomous Accelerator, A Common Project Between DESY and KIT

A. Eichler¹, F. Burkart¹, J. Kaiser¹, W. Kuropka¹, O. Stein¹, E. Bründermann², A. Santamaria Garcia², C. Xu²

¹Deutsches Elektronen-Synchrotron DESY, ²Karlsruhe Institute of Technology KIT

12th International Particle Accelerator Conference

Abstract

Reinforcement learning algorithms have risen in pop-ularity in the accelerator physics community in recentyears, showing potential in beam control and in the opti-mization and automation of tasks in accelerator operation.The Helmholtz AI project “Machine Learning Toward Au-tonomous Accelerators” is a collaboration between DESYand KIT that works on investigating and developing rein-forcement learning applications for the automatic start-upof electron linear accelerators. The work is carried out inparallel at two similar research accelerators: ARES at DESYand FLUTE at KIT, giving the unique opportunity of trans-fer learning between facilities. One of the first steps of thisproject is the establishment of a common interface betweenthe simulations and the machine, in order to test and applyvarious optimization approaches interchangeably betweenthe two accelerators. In this paper we present first results onthe common interface and its application to beam focusingin ARES as well as the idea of laser shaping with spatiallight modulators at FLUTE.

Read the paper: https://jacow.org/ipac2021/papers/tupab298.pdf

Contact: Annika Eichler