Multiple Scattering

Multiple scattering, the complex interaction of waves with multiple objects, is a significant challenge across diverse fields, with research focusing on accurately modeling and efficiently computing these interactions. Current efforts leverage neural networks, particularly physics-informed neural operators and diffusion models, to learn and approximate solutions to the underlying scattering equations, often incorporating geometric information and symmetries to improve accuracy and efficiency. These advancements are driving progress in areas such as inverse scattering problems, real-time rendering of complex materials, and acoustic signal processing, offering potential for improved imaging techniques, more realistic simulations, and novel computational architectures.