Journals of Accelerator Conferences Website (JACoW)
JACoW
is a publisher in Geneva, Switzerland that publishes the
proceedings of accelator conferences held around the world
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| URL | https://doi.org/10.18429/JACoW-IPAC2024-THPR35 |
|---|---|
| Title | Optimizing non-linear kicker injection parameters using machine learning |
| Authors |
|
| Abstract | Synchrotron light source storage rings aim to maintain a continuous beam current without observable beam motion during injection. One element that paves the way to this target is the non-linear kicker (NLK). The field distribution it generates poses challenges for optimizing the topping-up operation. Within this study, a reinforcement learning agent was developed and trained to optimize the NLK operation parameters. We present the models employed, the optimization process, and the achieved results. |
| Paper | download: THPR35.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 15th International Particle Accelerator Conference |
| Series | |
| Location | Nashville, TN |
| Date | 19-24 May 2024 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | Fulvia Pilat - Oak Ridge National Laboratory Wolfram Fischer - Brookhaven National Laboratory Robert Saethre - Oak Ridge National Laboratory Petr Anisimov - Los Alamos National Laboratory Ivan Andrian - Elettra-Sincrotrone Trieste S.C.p.A. |
| Online ISBN | 978-3-95450-247-9 |
| Online ISSN | 2673-5490 |
| Received | 15 May 2024 |
| Revised | 21 May 2024 |
| Accepted | 21 May 2024 |
| Issued | 01 July 2024 |
| DOI | 10.18429/JACoW-IPAC2024-THPR35 |
| Pages | 3571-3574 |
| 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. |