Modern computational technologies are gradually encountering significant limitations, driving a shift toward alternative paradigms such as optical computing. In this study, novel all-optical combinational logic units based on diffractive neural networks (D 2 NNs) were introduced, which were designed to perform highorder logical operations efficiently and swiftly with the adoption of only two modulation layers. This innovative design exhibits increased processing speed, improved energy efficiency, robust environmental stability, and high error tolerance, making it exceptionally well-suited for a broad spectrum of applications in optical computing and communications. By leveraging the transfer learning, we successfully developed a fifth-order cascaded combinational logic circuit for a practical information transmission system. Furthermore, we revealed a pioneering application of the device in optical time division multiplexing (OTDM), demonstrating its capability to manage high-speed data transfer seamlessly without the need for electronic conversion. Extensive simulations and experimental validations demonstrate the potential of the model as a foundational technology for future optical computing architectures, which paves the way toward more sustainable and efficient optical data processing platforms.

Haiqi Gao

Yu Shao

Yipeng Chen

Junren Wen

Yuchuan Shao

Yueguang Zhang

Weidong Shen

Chenying Yang

Chip

All-optical Combinational Logical Units featuring Fifth-Order Cascade

全光组合逻辑单元：五阶级联特征

All-optical Combinational Logical Units featuring Fifth-Order Cascade

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