Non-interleaved chiral metasurfaces and neural networks enhance the spatial resolution of polarimetry
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.
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2024-02-01
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Series: | Light: Science & Applications |
Online Access: | https://doi.org/10.1038/s41377-024-01397-2 |
Summary: | 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. |
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ISSN: | 2047-7538 |