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.