| Title |
Current Study of Applying Machine Learning to Accelerator Physics at IHEP |
| Authors |
- J. Wan, Y. Jiao
IHEP, Beijing, People’s Republic of China
|
| Abstract |
In recent years, machine learning (ML) has attracted increasing interest among the accelerator field. As a complex collection of multiple physical subsystems, the design and operation of an accelerator can be very nonlinear and complicated, while ML is taken as a powerful tool to solve such nonlinear and complicated problems. In this study, we report on several successful applications of ML to accelerator physics at IHEP. The nonlinear dynamics optimization of the High Energy Photon Source (HEPS) that is a 4th-generation light source is a challenging topic. In this optimization, we use a ML surrogate model to fast select the potentially competitive solutions for a multiobjective genetic algorithm that can significantly improve the convergence rate and the diversity among obtained solutions. Besides, we also tried to apply a generative adversarial net to solve one-to-many problems of longitudinal beam current profile shaping. Unlike most supervised machine learning methods than cannot learn one-to-many maps, the generative adversarial net-based method is able to predict multiple solutions instead of one for a 4-dipole chicane to realize several desired custom current profiles.
|
| Funding |
National Natural Science Foundation of China(No.11922512), Youth Innovation Promotion Association of Chinese Academy of Sciences(No.Y201904) and National Key R&D Program of China(No.2016YFA0401900). |
| Paper |
download TUPAB052.PDF [0.787 MB / 4 pages] |
| Poster |
download TUPAB052_POSTER.PDF [0.913 MB] |
| Export |
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| Conference |
IPAC2021 |
| Series |
International Particle Accelerator Conference (12th) |
| Location |
Campinas, SP, Brazil |
| Date |
24-28 May 2021 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Liu Lin (LNLS, Campinas, Brazil); John M. Byrd (ANL, Lemont, IL, USA); Regis Neuenschwander (LNLS, Campinas, Brazil); Renan Picoreti (LNLS, Campinas, Brazil); Volker R. W. Schaa (GSI, Darmstadt, Germany) |
| Online ISBN |
978-3-95450-214-1 |
| Online ISSN |
2673-5490 |
| Received |
11 May 2021 |
| Accepted |
21 June 2021 |
| Issue Date |
27 August 2021 |
| DOI |
doi:10.18429/JACoW-IPAC2021-TUPAB052 |
| Pages |
1477-1480 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 3.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
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