Complex-valued matrix-vector multiplication using a scalable coherent photonic processor

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.