2D Mutation-Based Elitist Genetic Algorithm for Optimal Design of Transmissive Linear-to-Circular Polarization Conversion Metasurfaces
Year: 2025
Type: article
Abstract: 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.
Source: Applied Sciences
DOI: 10.3390/app152011265
Authors: Jiao Wang, Wanguang Xiong, Hongkai Zhou, Chao Xu, Yannan Jiang
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Awards: G3147675913, G5968424648, G7147743611
OpenAlex ID: W4415403238
