An adaptive assisted method based on MOPSO for THz MMA effective designing

Abstract To address the high time cost and low efficiency of traditional terahertz (THz) metamaterial absorber (MMA) design, an adaptive method based on multi-objective particle swarm optimization (PSO) was proposed. First, we presented a symmetric absorber of a four-split-ring resonator with a cross-shaped top layer. The structural parameters were optimized by the PSO and multi-objective PSO (MOPSO) algorithms. The simulation results indicated that the MOPSO rapidly obtained geometric parameters that balance the high absorptivity and high quality factors. This method quickly identified a symmetric structure with absorptivity greater than 99% and quality factor of 377.45 at 1.584 THz. Additionally, the asymmetric structure achieved near-perfect absorption at 1.585 THz with a Q value of 281.32. By studying the electric field distribution and the surface current distribution, the physical mechanism of the absorber designed has been explained. This adaptive assisted method based on MOPSO can efficiently design MMAs and offer an artificial intelligence strategy for THz functional device design.