Application of machine learning in orbital correction of storage ring

Abstract

Synchrotron light source is one of the most powerful tools in modern science and technology. Shanghai Synchrotron Radiation Facility (SSRF), located in Shanghai, China, is an advanced 3.5 GeV 3rd-generation medium energy light source. The 3rd-generation synchrotron radiation light source will provide high brilliance and high stability synchrotron radiation to fulfill the advanced experimental conditions in frontier researches. To achieve highly stable radiation, it is important to have highly stable beam orbit. Thus we adopted machine learning method to control and feedback the orbit. Using this neural network-based orbit correction method, which doesn’t rely on the response matrix, we can establish a nonlinear mapping relationship between correctors and the orbit distortions and perform continuous online retraining. This new method can significantly improve the orbit stability of SSRF.