Optical Bistability in Photonic Topological Hypercrystals and Its Applications in Photonic Neural Network.

Optical bistability is a nonlinear phenomenon enabling stable switching between two optical states and has important applications in optical communication and photonic neural networks (PNNs). However, conventional bistable devices often suffer from fabrication imperfections and scattering losses, which limit their robustness and dispersionless performance. In this study, we numerically investigate optical bistability from a one-dimensional photonic topological hypercrystal (PhH) composed of alternating hyperbolic metamaterials (HMMs) and dielectric layers. By designing a center-inversed symmetric layered PhH structure and introducing Kerr nonlinearity into the localized dielectric region of maximum electric field intensity at the inversion center, we achieve a robust, angle-insensitive optical bistability for TM polarization through phase variation compensation mechanism. When applied as a nonlinear activation function in PNNs, the bistable PhH exhibits performance comparable to conventional digital activation functions such as ReLU and Sigmoid in image-recognition tasks. Our work paves the way for integrating topological bistable devices into next-generation PNNs.