Neural network assisted high-spatial-resolution polarimetry with non-interleaved chiral metasurfaces

作者：Chen Chen, Xingjian Xiao, Xin Ye, Jiacheng Sun, Jitao Ji, Rongtao Yu, Wange Song, Shining Zhu, Tao Li · 发表于：Light Science & Applications · 年份：2023 · DOI：10.1038/s41377-023-01337-6 · 被引用次数：70 · 研究领域：Metamaterials and Metasurfaces Applications、Optical Polarization and Ellipsometry、Orbital Angular Momentum in Optics

Polarimetry plays an indispensable role in modern optics. Nevertheless, the current strategies generally suffer from bulky system volume or spatial multiplexing scheme, resulting in limited performances when dealing with inhomogeneous polarizations. Here, we propose a non-interleaved, interferometric method to analyze the polarizations based on a tri-channel chiral metasurface. A deep convolutional neural network is also incorporated to enable fast, robust and accurate polarimetry. Spatially uniform and nonuniform polarizations are both measured through the metasurface experimentally. Distinction between two semblable glasses is also demonstrated. Our strategy features the merits of compactness and high spatial resolution, and would inspire more intriguing design for detecting and sensing.