Compact Planar-Waveguide Integrated Diffractive Optical Neural Network Chip

Diffractive optical neural networks (DONNs) have exhibited the advantages of parallelization, high speed, and low consumption. However, the existing DONNs based on free-space diffractive optical elements are bulky and unsteady. In this study, we propose a planar-waveguide integrated diffractive neural network chip architecture. The three diffractive layers are engraved on the same side of a quartz wafer. The three-layer chip is designed with 32-mm3 processing space and enables a computing speed of 3.1×109 Tera operations per second. The results show that the proposed chip achieves 73.4% experimental accuracy for the Modified National Institute of Standards and Technology database while showing the system's robustness in a cycle test. The consistency of experiments is 88.6%, and the arithmetic mean standard deviation of the results is ~4.7%. The proposed chip architecture can potentially revolutionize high-resolution optical processing tasks with high robustness.