Plasmonic Metamaterial Absorbers Design Based on XGBoost and LightGBM Algorithms

• Published in: Plasmonics (Norwell, Mass.) Vol. 17; no. 5; pp. 2037 - 2047
• Main Authors: Gu, Leilei, Xie, Shusheng, Zhang, Ying, Huang, Yule, He, Yaojun, Liu, Hongzhan, Wei, Zhongchao, Guo, Jianping
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-10-2022; Springer Nature B.V
• Subjects: Absorbers; Absorbers (materials); Algorithms; Biochemistry; Biological and Medical Physics; Biophysics; Biotechnology; Chemistry; Chemistry and Materials Science; Design parameters; Inverse design; Metamaterials; Nanotechnology; Plasmonics; Metamaterials; Reflection value; Inverse design; LightGBM; XGBoost
• ISSN: 1557-1955; 1557-1963
• DOI: 10.1007/s11468-022-01697-6

The emergence of metamaterials has brought a revolutionary way to manipulate the behavior of light on the nanoscale. However, there are still many problems in design process, such as time-consuming and many-to-one mapping. Here, we demonstrate the forward and inverse design of plasmonic metamaterial absorbers based on Light gradient boosting machine (LightGBM) and Extreme Gradient Boosting (XGBoost). The inverse framework can use the input reflection value to design the metamaterial parameter structure. The experimental results show that XGBoost has better performance in forward and inverse design (Forward-
R
2
: 0.956; Inverse-
R
2
: 0.967). The framework is suitable for designing metamaterials on demand, and it can be used in zoom imaging, metamaterial absorbers, metamaterial filters, and other fields.