As an important computing operation,photonic matrix-vector multiplication is widely used in photonic neutral networks and signal processing.However,conventional incoherent matrix-vector multiplication focuses on real-valued operations,which cannot work well in complex-valued neural networks and discrete Fourier transform.In this paper,we propose a systematic solution to extend the matrix computation of microring arrays from the real-valued field to the complex-valued field,and from small-scale(i.e.,4×4)to large-scale matrix computation(i.e.,16×16).Combining matrix decomposition and matrix partition,our photonic complex matrix-vector multiplier chip can support arbitrary large-scale and complex-valued matrix computation.We further demonstrate Walsh-Hardmard transform,discrete cosine transform,discrete Fourier transform,and image convolutional processing.Our scheme provides a path towards breaking the limits of complex-valued computing accelerator in conventional incoherent optical architecture.More importantly,our results reveal that an integrated photonic platform is of huge potential for large-scale,complex-valued,artificial intelligence computing and signal processing.

Junwei Cheng;Yuhe Zhao;Wenkai Zhang;Hailong Zhou;Dongmei Huang;Qing Zhu;Yuhao Guo;Bo Xu;Jianji Dong;Xinliang Zhang

Wuhan National Laboratory for Optoelectronics,School of Optical and Electronic Information,Huazhong University of Science and Technology,Wuhan 430074,China;Photonics Research Centre,Department of Electronic and Information Engineering,The Hong Kong Polytechnic University,Hong Kong 999077,China;The Hong Kong Polytechnic University Shenzhen Research Institute,Shenzhen 518057,China;Photonics Research Centre,Department of Electrical Engineering,The Hong Kong Polytechnic University,Hong Kong 999077,China;Institute of Strategic Research,Huawei Technologies,Shenzhen 518129,China

光电子前沿（英文版）

[1]Junwei Cheng;Yuhe Zhao;Wenkai Zhang;Hailong Zhou;Dongmei Huang;Qing Zhu;Yuhao Guo;Bo Xu;Jianji Dong;Xinliang Zhang-.A small microring array that performs large complex-valued matrix-vector multiplication)[J].光电子前沿（英文版）,2022(02):1-15

Hardmard

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