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 accelerator vacuum chamber with thin conductive coating, and also verified in comparison with the existing analytical formula.

翻译：提出了在粒子加速器中模拟波束-壁相互作用的无网状方法,我们方法的关键思想是利用深神经网络作为替代,解决一套涉及粒子波束和表面阻力概念的局部差异方程式。 所提议的方法适用于加速器真空室与细导波涂层的混合阻力,并与现有的分析公式进行比较。