Haoming Li

Rapid, material-aware inverse design of one-dimensional photonic crystals using a mixture-of-physics-expert framework

In this work, we present an unsupervised physics-informed neural network (PINN) framework for the inverse design of 1D photonic crystals, addressing the limitations of conventional methods, such as high computational cost and inability to optimize materials. A “mixture-of-physics...