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Description
This paper introduces an accelerator surrogate model utilizing Diffusion Models. The proposed model leverages the parameters of the incoming beam bunch as conditional inputs to accurately and efficiently predict the phase space distribution of the beam at the accelerator’s exit. By focusing on the Medium Energy Beam Transport (MEBT) section of the China Accelerator Facility for Superheavy Elements (CAFe2), this study constructs an overall surrogate model by progressively substituting each accelerator component with a diffusion model and connecting them in series. This method not only significantly reduces computational complexity but also ensures high prediction accuracy, providing substantial practical significance for the design, optimization, and operational maintenance of accelerators.
