Linear Optics Calibration in a Storage Ring Based on Machine Learning

Inevitably, various errors occur in an actual storage ring, such as magnetic field errors, magnet misalignments, and ground settlement deformation, which cause closed orbit distortion and tuning shift. Therefore, linear optics calibration is an essential procedure for storage rings. In this paper, w...

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Bibliographic Details
Published inApplied sciences Vol. 13; no. 14; p. 8034
Main Authors Li, Ruichun, Jiang, Bocheng, Zhang, Qinglei, Zhao, Zhentang, Li, Changliang, Wang, Kun
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2023
Subjects
Analysis
Calibration
Computational linguistics
convolutional neural network
Language processing
linear optics calibration
Machine learning
Magnetic fields
Natural language interfaces
Neural networks
Optics
Radiation
Research methodology
storage ring
China
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Summary:Inevitably, various errors occur in an actual storage ring, such as magnetic field errors, magnet misalignments, and ground settlement deformation, which cause closed orbit distortion and tuning shift. Therefore, linear optics calibration is an essential procedure for storage rings. In this paper, we introduce a new method using machine learning to calibrate linear optics. This method is different from the traditional linear optics from closed orbit (LOCO) method, which is based on singular value decomposition (SVD). The machine learning model does not need to be computed by SVD. Our study shows that the machine-learning-based method can significantly reduce the difference between the model response matrix and the measurement response matrix by adjusting the strength of the quadrupoles.
ISSN:2076-3417
2076-3417
DOI:10.3390/app13148034