Linear Optics Calibration in a Storage Ring Based on Machine Learning

Autor: Wang, Ruichun Li, Bocheng Jiang, Qinglei Zhang, Zhentang Zhao, Changliang Li, Kun
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Applied Sciences; Volume 13; Issue 14; Pages: 8034
ISSN: 2076-3417
DOI: 10.3390/app13148034
Popis: 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.
Databáze: OpenAIRE