Deep learning and heuristic algorithm assisted optimization of structure parameters of asymmetric polarization converter

Jiacheng Yu; Qingguo Du

doi:10.1117/12.2683450

26 June 2023 Deep learning and heuristic algorithm assisted optimization of structure parameters of asymmetric polarization converter

Jiacheng Yu, Qingguo Du

Author Affiliations +

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 127211E (2023) https://doi.org/10.1117/12.2683450
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

Due to the high-dimensional structure parameters and time-consuming of numerical simulations, it is hard to obtained the optimized structure parameters of metasurface structures. To address this issue, in this paper, in order to maximize the performance of the proposed asymmetric polarization converter, a deep learning with heuristic algorithm approach is applied to search for the optimal set of structure parameters. With optimized structure parameters, the average transmittance is larger than 0.5 for the wavelength range from 447 to 475nm and a maximum transmittance of 0.623 at 457.5nm. The bandwidth of transmittance larger than 0.5 is 6nm wider and the maximum transmittance is 0.02 higher than those of the reinforcement learning model we used for the parameters’ optimization of the same structure in our previously published papers respectively. The optimization time is about 10 minutes, which is only 50% of that used in the reinforcement learning algorithm.

Citation Download Citation

Jiacheng Yu and Qingguo Du "Deep learning and heuristic algorithm assisted optimization of structure parameters of asymmetric polarization converter", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 127211E (26 June 2023); https://doi.org/10.1117/12.2683450

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