Non-interleaved chiral metasurfaces and neural networks enhance the spatial resolution of polarimetry

Jaewon Jang; Minsu Park; Yeonsang Park

doi:10.1038/s41377-024-01397-2

Non-interleaved chiral metasurfaces and neural networks enhance the spatial resolution of polarimetry

Light Sci Appl. 2024 Feb 20;13(1):53. doi: 10.1038/s41377-024-01397-2.

Authors

Jaewon Jang^{1

2}, Minsu Park^{1

2}, Yeonsang Park^{3

4}

Affiliations

¹ Department of Physics, Chungnam National University, Daejeon, 34134, Korea.
² Institute of Quantum Systems, Chungnam National University, Daejeon, 34134, Korea.
³ Department of Physics, Chungnam National University, Daejeon, 34134, Korea. yeonsang.park@cnu.ac.kr.
⁴ Institute of Quantum Systems, Chungnam National University, Daejeon, 34134, Korea. yeonsang.park@cnu.ac.kr.

Abstract

Non-interleaved chiral metasurfaces for high-spatial-resolution polarimetry are proposed and demonstrated. Furthermore, a convolutional neural network is incorporated to analyze interferometric images with the polarization state of light, and it results in accurate Stokes parameters.