2D Mutation-Based Elitist Genetic Algorithm for Optimal Design of Transmissive Linear-to-Circular Polarization Conversion Metasurfaces

Although the elitist genetic algorithm (EGA) is an approach for the optimal design of pixelated metasurfaces, it is necessary to convert a two-dimensional (2D) metasurface to a one-dimensional array. This ignores the effects of the mutation on neighboring data in 2D metasurfaces, and hinders the rapid convergence of the algorithms. Therefore, we propose the 2D mutation-based EGA (2DM-EGA) to optimally design the linear-to-circular (LTC) polarization conversion metasurface (PCM). Compared with EGA, 2DM-EGA can significantly improve the convergence rate. Furthermore, combined with the proposed intuitive reward-based fitness function and circular polarization discrimination pertaining to an ellipticity angle β, 2DM-EGA, programmed in Python (2023 version), is used to accomplish optimal targets. Finally, the simulated operating band of the optimized metasurface varies from 8.16 GHz to 11.5 GHz with a reduced ellipticity angle β/π ≥ 0.15 and a relative bandwidth of 33.5%, which suggests that the optimized metasurface realizes the broadband LTC polarization conversion. The measured results are in excellent accord with the simulations validating 2DM-EGA for the optimal design of transmission-type wideband LTC PCMs. Additionally, the physical mechanism of the design is expounded.