To achieve low-power convolutional neural networks, we develop a photoelectric hybrid neural network (PHNN), which consists of the optical interference unit (OIU) and field-programmable gate array (FPGA). The OIU composed of Mach–Zehnder interferometers (MZI) arrays, used as convolution kernels, performs multiplication and accumulation operations. The convolution kernel is split and reorganized, forming a new unitary matrix, which reduces MZI quantity. FPGA realizes nonlinear calculation, data scheduling and storage, and phase encoding and modulation. Our PHNN has an accuracy rate of 88.79%, and the energy efficiency ratio is 1.73 times that of traditional electronic products.

中文翻译：

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具有相干纳米光子电路的光电混合卷积神经网络

为了实现低功耗卷积神经网络，我们开发了一种光电混合神经网络（PHNN），它由光干涉单元（OIU）和现场可编程门阵列（FPGA）组成。OIU 由 Mach-Zehnder 干涉仪 (MZI) 阵列组成，用作卷积核，执行乘法和累加运算。卷积核被拆分重组，形成一个新的酉矩阵，减少了MZI数量。FPGA实现非线性计算、数据调度和存储、相位编码和调制。我们的PHNN准确率为88.79%，能效比是传统电子产品的1.73倍。