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Research on beam dynamics optimization of a storage ring based on machine learning
2024-01-25
会议录名称2023 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND NEXT GENERATION NETWORKS(ICNGN)
发表状态已发表
DOI10.1109/ICNGN59831.2023.10396700
摘要This paper discusses the machine learning methods for the beam dynamics optimization in a storage ring for synchrotron light sources. A new method of closed orbit feedback based on machine learning was developed to enhance synchrotron radiation stability, which was then piloted at Shanghai Synchrotron Radiation Facility (SSRF). We use a novel machine learning technique to calibrate the linear optics, which differs from the traditional singular value decomposition (SVD)-based linear optics from closed orbit (LOCO). Predicting dynamic apertures is also one of the machine learning applications in our work. © 2023 IEEE.
关键词machine learning calibration and fitting methods synchrotron light sources cluster finding storage ring convolutional neural network
会议名称2nd International Conference on Intelligent Computing and Next Generation Networks, ICNGN 2023
会议地点Hangzhou, China
会议日期17-18 November 2023
URL查看原文
收录类别EI
语种英语
出版者Institute of Electrical and Electronics Engineers Inc.
EI入藏号20240815572530
EI主题词Machine learning
EI分类号723.4 Artificial Intelligence ; 921 Mathematics ; 932.1.1 Particle Accelerators
原始文献类型Conference article (CA)
来源库IEEE
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/346080
专题物质科学与技术学院_博士生
作者单位
1.Shanghai Synchrotron Radiation Facility, Shanghai Advanced Research Institute, Chinese Academy of Sciences
2.School of Physical Science and Technology, ShanghaiTech University
第一作者单位物质科学与技术学院
推荐引用方式
GB/T 7714
Ruichun Li,Qinglei Zhang,Zhentang Zhao,et al. Research on beam dynamics optimization of a storage ring based on machine learning[C]:Institute of Electrical and Electronics Engineers Inc.,2024.
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