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Optical diffractive neural networks have triggered extensive research withtheir low power consumption and high speed in image processing. In this work,we propose a reconfigurable digital all-optical diffractive neural network(R-ODNN) structure. The optical neurons are built with Sb2Se3 phase-changematerial, making our network reconfigurable, digital, and non-volatile. Usingthree digital diffractive layers with 14,400 neurons on each and 10photodetectors connected to a resistor network, our model achieves 94.46%accuracy for handwritten digit recognition. We also performed full-vectorsimulations and discussed the impact of errors to demonstrate the feasibilityand robustness of the R-ODNN.

Non-volatile Reconfigurable Digital Optical Diffractive Neural Network Based on Phase Change Material