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A mesh‐free approach for modelling beam‐wall interactions in particle accelerators is proposed. The key idea of our method is to use a deep neural network as a surrogate for the solution to a set of partial differential equations involving the particle beam, and the surface impedance concept. The proposed approach is applied to the coupling impedance of an infinitely long vacuum chamber with a thin conductive coating, and also verified in comparison with traditional numerical methods.

Physics‐informed neural network method for modelling beam‐wall interactions