Photonic Band Gap Optimization in SiC-air crystals via Grey Wolf Optimizer

We developed an efficient inverse-design approach using the Grey Wolf Optimizer (GWO) to synthesize two-dimensional photonic crystal (PC) structures with large photonic band-gap (PBG). Using this method, we identified a new optimal SiC–air PC configuration for transverse magnetic (TM) polarization, achieving a PBG with a Gap-to-Midgap Ratio (GMR) of 34.55%.

Photonic crystals are periodic dielectric structures composed of materials with contrasting refractive indices, enabling the formation of PBGs that prevent electromagnetic wave propagation. The inverse design of PCs is challenging due to the high number of degrees of freedom and the intrinsic complexity of Maxwell’s equations. The GWO is a metaheuristic based on grey wolves’ hunting behavior: pursuit, encirclement, and attack. It offers strong global search capabilities, robustness against local minima, and simpler operators compared to other swarm-based optimizers; therefore, we investigate its suitability for this task.

The python-GWO was first validated with standard benchmark functions and then coupled to a Matlab–FORTRAN Finite Element Method (FEM) solver. The PC unit cell, arranged in a triangular lattice, was discretized into a 10×10 grid (100 bits), each assigned either SiC (n = 2.6) or air. The FEM solver computed dispersion diagrams, and the GMR served as the optimization objective. The optimized TM structure achieved a GMR of 34.55%, and GWO convergence curves helped verify solution saturation by hyperparameter.

In conclusion, the GWO proved effective for fast inverse design of SiC–air PCs, yielding a crystal configuration with significantly improved PBG for the TM polarization.