High-efficiency polarization beam merging metagrating design via global initial solution-based topology optimization

被引:0
|
作者
Han, Zhiqiang [1 ,2 ,3 ,4 ]
Zheng, Yuhan [1 ,2 ,4 ]
Xu, Mingfeng [1 ,2 ,3 ,4 ]
Wang, Si [1 ,2 ,3 ]
Pu, Mingbo [1 ,2 ,3 ,4 ]
Ma, Xiaoliang [1 ,2 ,4 ]
Guo, Yinghui [1 ,2 ,3 ,4 ]
Li, Xiong [1 ,2 ,4 ]
Luo, Xiangang [1 ,2 ,4 ]
机构
[1] Chinese Acad Sci, Natl Key Lab Opt Field Manipulat Sci & Technol, Chengdu 610209, Peoples R China
[2] Chinese Acad Sci, Inst Opt & Elect, State Key Lab Opt Technol Nanofabricat & Microengn, Chengdu 610209, Peoples R China
[3] Chinese Acad Sci, Inst Opt & Elect, Res Ctr Vector Opt Fields, Chengdu 610209, Peoples R China
[4] Univ Chinese Acad Sci, Coll Mat Sci & Optoelect Technol, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
GENETIC-ALGORITHM; ANGLE;
D O I
10.1364/OL.557718
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Freeform metasurfaces based on topology optimization enable precise control over electromagnetic functionalities, with widespread applications in metagratings, metalenses, and polarization transformations. The selection of the initial structure plays a crucial role in determining the quality of the final optimization results. In this study, a global initial solution-based topology optimization (GISTO) is proposed to design a polarization beam merging metagrating efficiently. A two-dimensional encoded non-dominated sorting genetic algorithm II is employed for global exploration to obtain a high-quality initial structure, which is then refined using gradient-based topology optimization for a local optimization design. By integrating global and local optimization, the efficiency of polarization beam merging metagrating is significantly improved. Under symmetric incidence, the efficiencies for x-polarized and y-polarized beams reach 93.67c and 95.37c, respectively, while under asymmetric incidence, the efficiencies achieve 99.47c and 95.47c, respectively. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
引用
收藏
页码:1637 / 1640
页数:4
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