Xie Yiwei, Ke Xiyuan, Hong Shihan, Sun Yuxin, Song Lijia, Li Huan, Wang Pan, Dai Daoxin
State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang Key Laboratory of Optoelectronic Information Technology, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310058, China.
Jiaxing Key Laboratory of Photonic Sensing and Intelligent Imaging, Intelligent Optics and Photonics Research Center, Zhejiang University, Jiaxing 314000, China.
Sci Adv. 2025 Apr 4;11(14):eads7475. doi: 10.1126/sciadv.ads7475.
Matrix-vector multiplication is a fundamental operation in modern signal processing and artificial intelligence. Developing a chip-scale photonic matrix-vector multiplication processor (MVMP) offers the potential for notably enhanced computing speed and energy efficiency beyond microelectronics. Here, we propose and demonstrate a 16-channel programmable on-chip coherent photonic processor capable of performing complex-valued matrix-vector multiplication at a computing speed of 1.28 tera-operations per second (TOPS). Low phase error Mach-Zehnder interferometers mesh and ultralow-loss broadened photonic waveguide delay lines are firstly combined for optical computing, enabling the encoding of amplitude and phase information, along with high-speed coherent detection. The proposed MVMP demonstrates high flexibility in implementing various functions, including arbitrary matrix transformation, parallel image processing, and handwritten digital recognition. Our work demonstrates the MVMP's advantages in scalability and function flexibility, enabled by the low-loss and low phase error designs, making a substantial advancement in high-speed and large-scale photonic computing technologies.
矩阵向量乘法是现代信号处理和人工智能中的一项基本运算。开发芯片级光子矩阵向量乘法处理器（MVMP）有望显著提高计算速度和能源效率，超越微电子技术。在此，我们提出并展示了一种16通道可编程片上相干光子处理器，它能够以每秒1.28万亿次运算（TOPS）的计算速度执行复数值矩阵向量乘法。低相位误差马赫曾德尔干涉仪网格和超低损耗扩展光子波导延迟线首次被组合用于光学计算，实现了幅度和相位信息的编码以及高速相干检测。所提出的MVMP在实现各种功能方面展现出高度灵活性，包括任意矩阵变换、并行图像处理和手写数字识别。我们的工作展示了MVMP在可扩展性和功能灵活性方面的优势，这得益于低损耗和低相位误差设计，在高速和大规模光子计算技术方面取得了重大进展。
