Orbit correction based on machine learning

Xiao Dengjie; Qiao Yusi; Chu Zhongming

doi:10.11884/HPLPB202133.200352

Volume 33 Issue 5

May 2021

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Article Navigation > High Power Laser and Particle Beams > 2021 > 33(5): 054004

Xiao Dengjie, Qiao Yusi, Chu Zhongming. Orbit correction based on machine learning[J]. High Power Laser and Particle Beams, 2021, 33: 054004. doi: 10.11884/HPLPB202133.200352

Citation:

Xiao Dengjie, Qiao Yusi, Chu Zhongming. Orbit correction based on machine learning[J]. High Power Laser and Particle Beams, 2021, 33: 054004. doi: 10.11884/HPLPB202133.200352

Xiao Dengjie, Qiao Yusi, Chu Zhongming. Orbit correction based on machine learning[J]. High Power Laser and Particle Beams, 2021, 33: 054004. doi: 10.11884/HPLPB202133.200352

Citation:

Xiao Dengjie, Qiao Yusi, Chu Zhongming. Orbit correction based on machine learning[J]. High Power Laser and Particle Beams, 2021, 33: 054004. doi: 10.11884/HPLPB202133.200352

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Orbit correction based on machine learning

doi: 10.11884/HPLPB202133.200352

Xiao Dengjie^{1, 2
,},
Qiao Yusi^{1, 2},
Chu Zhongming^{3
,
,}

1.
School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China
2.
Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
3.
College of Engineering and Applied Science, Nanjing University, Nanjing 210023, China

Received Date: 2020-12-24
Rev Recd Date: 2021-03-12

Available Online: 2021-04-15

Publish Date: 2021-05-15

Abstract

Abstract

Orbit correction is one of the most fundamental processes used for beam control in accelerators. Algorithms have been developed at various laboratories to meet specific demands. Typically, linear algebraic tools are applied to various response matrices to solve related problems. However, there are still many problems faced by orbit correction algorithms such as lengthy measurement and computation time. A new approach based on machine learning to develop an orbit correction program is introduced. In this method a machine learning program is trained with correctors data and BPMs data for applying to orbit correction. Mathematical formulation, algorithms prototyped and tested on simulated and real data, and future possibilities are discussed.
- orbit correction,
- machine learning,
- operation data,
- magnet error,
- data cleaning

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References(12)

References

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