Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing
Abstract Information security aims to protect confidentiality and prevent information leakage, which inherently conflicts with the goal of information sharing. Balancing these competing requirements is especially challenging in all-optical systems, where efficient data transmission and rigorous secu...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-59763-6 |
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| author | Ziqing Guo Zhiyu Tan Xiaofei Zang Teng Zhang Guannan Wang Hongguang Li Yuanbo Wang Yiming Zhu Fei Ding Songlin Zhuang |
| author_facet | Ziqing Guo Zhiyu Tan Xiaofei Zang Teng Zhang Guannan Wang Hongguang Li Yuanbo Wang Yiming Zhu Fei Ding Songlin Zhuang |
| author_sort | Ziqing Guo |
| collection | DOAJ |
| description | Abstract Information security aims to protect confidentiality and prevent information leakage, which inherently conflicts with the goal of information sharing. Balancing these competing requirements is especially challenging in all-optical systems, where efficient data transmission and rigorous security are essential. Here we propose and experimentally demonstrate a metasurface-based approach that integrates phase manipulation, polarization conversion, as well as direction- and polarization-selective functionalities into all-optical diffractive neural networks (DNNs). This approach enables a polarization-controllable switch between unidirectional and bidirectional DNNs, thus simultaneously realizing information security and sharing. A cascaded terahertz metasurface comprising quarter-wave plates and metallic gratings is designed to function as a polarization-selective unidirectional-bidirectional classifier and imager. By introducing half-wave plates into a cascade metasurface, we achieve a polarization-controlled transition in unidirectional-bidirectional-unidirectional modes for classification and imaging. Furthermore, we demonstrate a high-security data exchange framework based on these polarization-selective DNNs. The proposed DNNs with polarization-switchable unidirectional/bidirectional capabilities offer significant potential for privacy protection, encryption, communications, and data exchange. |
| format | Article |
| id | doaj-art-737cbbb7676641afae5b328ec612c4fa |
| institution | OA Journals |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-737cbbb7676641afae5b328ec612c4fa2025-08-20T01:51:32ZengNature PortfolioNature Communications2041-17232025-05-0116111110.1038/s41467-025-59763-6Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharingZiqing Guo0Zhiyu Tan1Xiaofei Zang2Teng Zhang3Guannan Wang4Hongguang Li5Yuanbo Wang6Yiming Zhu7Fei Ding8Songlin Zhuang9Terahertz Technology Innovation Research Institute, University of Shanghai for Science and TechnologyTerahertz Technology Innovation Research Institute, University of Shanghai for Science and TechnologyTerahertz Technology Innovation Research Institute, University of Shanghai for Science and TechnologyTerahertz Technology Innovation Research Institute, University of Shanghai for Science and TechnologyTerahertz Technology Innovation Research Institute, University of Shanghai for Science and TechnologyXi’an Institute of Applied OpticsXi’an Institute of Applied OpticsTerahertz Technology Innovation Research Institute, University of Shanghai for Science and TechnologySchool of Electronic Science and Technology, Eastern Institute of TechnologyTerahertz Technology Innovation Research Institute, University of Shanghai for Science and TechnologyAbstract Information security aims to protect confidentiality and prevent information leakage, which inherently conflicts with the goal of information sharing. Balancing these competing requirements is especially challenging in all-optical systems, where efficient data transmission and rigorous security are essential. Here we propose and experimentally demonstrate a metasurface-based approach that integrates phase manipulation, polarization conversion, as well as direction- and polarization-selective functionalities into all-optical diffractive neural networks (DNNs). This approach enables a polarization-controllable switch between unidirectional and bidirectional DNNs, thus simultaneously realizing information security and sharing. A cascaded terahertz metasurface comprising quarter-wave plates and metallic gratings is designed to function as a polarization-selective unidirectional-bidirectional classifier and imager. By introducing half-wave plates into a cascade metasurface, we achieve a polarization-controlled transition in unidirectional-bidirectional-unidirectional modes for classification and imaging. Furthermore, we demonstrate a high-security data exchange framework based on these polarization-selective DNNs. The proposed DNNs with polarization-switchable unidirectional/bidirectional capabilities offer significant potential for privacy protection, encryption, communications, and data exchange.https://doi.org/10.1038/s41467-025-59763-6 |
| spellingShingle | Ziqing Guo Zhiyu Tan Xiaofei Zang Teng Zhang Guannan Wang Hongguang Li Yuanbo Wang Yiming Zhu Fei Ding Songlin Zhuang Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing Nature Communications |
| title | Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing |
| title_full | Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing |
| title_fullStr | Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing |
| title_full_unstemmed | Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing |
| title_short | Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing |
| title_sort | polarization selective unidirectional and bidirectional diffractive neural networks for information security and sharing |
| url | https://doi.org/10.1038/s41467-025-59763-6 |
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