Time- and wavelength-multiplexed photonic matrix-matrix multiplication processor with on-chip wavelength (de)multiplexers
Chengli Chai, Rui Tang, Makoto Okano, Kasidit Toprasertpong, Mitsuru Takenaka · Optics Express · 2026
Photonic processors offer a promising approach to accelerating matrix multiplications, which dominate the workload in AI computations. Photonic matrix multiplication processors based on time-division multiplexing (TDM) have attracted significant interest due to their superior scalability, which is critical for realizing large-scale matrices with a limited number of on-chip optical components. To further enhance parallelism, wavelength-division multiplexing (WDM) can be incorporated, with each wavelength carrying different vector information. While several prior studies have demonstrated such photonic matrix processors using both TDM and WDM, the (de)multiplexing of multiple wavelengths is typically performed off-chip. In this work, we propose and demonstrate a hybrid WDM-TDM photonic matrix-matrix multiplication processor, which employs microring resonator (MRR) arrays as on-chip wavelength (de)multiplexers, achieving a higher level of integration compared with approaches that use off-chip (de)multiplexers. A 3-wavelength, 12-channel circuit is fabricated on a Si-on-insulator (SOI) platform and applied to handwritten digit recognition, achieving a classification accuracy of 93.2% on 2000 images. Furthermore, the scalability of wavelength multiplexing and computational performance are analyzed, providing design guidelines for scaling the proposed architecture.