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| URL | https://doi.org/10.18429/JACoW-IPAC2023-THPL029 |
|---|---|
| Title | Beam trajectory control with lattice-agnostic reinforcement learning |
| Authors |
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| Abstract | In recent work, it has been shown that reinforcement learning (RL) is capable of outperforming existing methods on accelerator tuning tasks. However, RL algorithms are difficult and time-consuming to train and currently need to be retrained for every single task. This makes fast deployment in operation difficult and hinders collaborative efforts in this research area. At the same time, modern accelerators often reuse certain structures within or across facilities such as transport lines consisting of several magnets, leading to similar tuning tasks. In this contribution, we use different methods, such as domain randomization, to allow an agent trained in simulation to easily be deployed for a group of similar tasks. Preliminary results show that this training method is transferable and allows the RL agent to control the beam trajectory at similar lattice sections of two different real linear accelerators. We expect that future work in this direction will enable faster deployment of learning-based tuning routines, and lead towards the ultimate goal of autonomous operation of accelerator systems and transfer of RL methods to most accelerators. |
| Paper | download: THPL029.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 14th International Particle Accelerator Conference |
| Series | |
| Location | Venice, Italy |
| Date | 07-12 May 2023 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | Ralph Assmann - Deutsches Elektronen-Synchrotron DESY Peter McIntosh - Science and Technology Facilities Council (STFC/DL/ASTeC) Giovanni Bisoffi - Istituto Nazionale di Fisica Nucleare (INFN/LNL) Alessandro Fabris - Elettra-Sincrotrone Trieste S.C.p.A. Ivan Andrian - Elettra-Sincrotrone Trieste S.C.p.A. Giulia Vinicola - Istituto Nazionale di Fisica Nucleare (INFN/LNF) |
| Online ISBN | 978-3-95450-231-8 |
| Online ISSN | 2673-5490 |
| Received | 02 May 2023 |
| Revised | 09 May 2023 |
| Accepted | 11 May 2023 |
| Issued | 26 September 2023 |
| DOI | 10.18429/JACoW-IPAC2023-THPL029 |
| Pages | 4487-4490 |
| Copyright | Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |