Space‐Time Projection Enabled Ultrafast All‐Optical Diffractive Neural Network

Author:

Zhang Ziyang1,Feng Fu12ORCID,Gan Jiaan3,Lin Wei3,Chen Guangyong4,Somekh Michael G1,Yuan Xiaocong1

Affiliation:

1. Research Center for Frontier Fundamental Studies Zhejiang Lab Hangzhou 311100 China

2. State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and Engineering Zhejiang University Hangzhou 310027 China

3. Institute of Modern Optics Nankai University Tianjin 300350 China

4. Research Center for Life Science Computing Zhejiang Lab Hangzhou 311100 China

Abstract

AbstractAll‐optical neural networks have advantages in higher throughput, higher speed as well as lower energy consumption compared to electrical neural networks. Optical neural networks have already shown great potential in various applications; however, the operation speed of the network is limited by the 2D detector as most optical neural networks rely on space to space projection. Here, a space to time projection approach to build diffractive deep neural network (D2NN) is proposed, which can project spatial intensity distribution into time‐domain intensity variation, thus bypassing the detection speed limit of 2D imaging device. Based on this scheme, high‐speed all‐optical logic gates are theoretically analyzed and experimentally realized. In this case, the network's operation speed is only limited by the photodetector (PD), which can reach GHz levels. Moreover, the method will show great advantage when it comes to wavelengths where 2D detectors are not achievable easily such as infrared, terahertz or microwaves.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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