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

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 93.6% and 95.3%, respectively, while under asymmetric incidence, the efficiencies achieve 99.4% and 95.4%, respectively.