超材料
圆二色性
严格耦合波分析
光子学
光学
纳米结构
物理
衍射
光子超材料
拓扑(电路)
衍射光栅
量子力学
数学
结晶学
化学
组合数学
作者
Zilong Tao,Jinhong You,Jun Zhang,Xin Zheng,Hengzhu Liu,Tian Jiang
出处
期刊:Optics Letters
[The Optical Society]
日期:2020-03-05
卷期号:45 (6): 1403-1403
被引量:25
摘要
Here, a deep learning (DL) algorithm based on deep neural networks is proposed and employed to predict the chiroptical response of two-dimensional (2D) chiral metamaterials. Specifically, these 2D metamaterials contain nine types of left-handed nanostructure arrays, including U-like, T-like, and I-like shapes. Both the traditional rigorous coupled wave analysis (RCWA) method and DL approach are utilized to study the circular dichroism (CD) in higher-order diffraction beams. One common feature of these chiral metamaterials is that they all exhibit the weakest intensity but the strongest CD response in the third-order diffracted beams. Our work suggests that the DL model can predict CD performance of a 2D chiral nanostructure with a computational speed that is four orders of magnitude faster than RCWA but preserves high accuracy. The DL model introduced in this work shows great potentials in exploring various chiroptical interactions in metamaterials and accelerating the design of hypersensitive photonic devices.
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