ArticleScience advances2025
Complex-valued matrix-vector multiplication using a scalable coherent photonic processor.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- 192-dimensional wavelength-/mode-/polarization-multiplexed photonic architecture for highly parallel optical computing.National science review · 2026Article
- Emerging integrated photonic neural network technologies for artificial intelligence: from devices to systems.National science review · 2026Review
- Integrated Neuromorphic Photonic Computing for AI Acceleration: Emerging Devices, Network Architectures, and Future Paradigms.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Dual-Mode MOSCAP Silicon Microring Resonator for Energy-Efficient Analog Optical Computing.ACS photonics · 2026Article
- Time-synthetic optical neural networks with stable programmable gain.Nature communications · 2026Article
- Article
- LightIN: a versatile silicon-integrated photonic field programmable gate array with an intelligent configuration framework for next-generation AI clusters.Light, science & applications · 2026Article
- Compact, reconfigurable, and scalable photonic neurons by modulation-and-weighting microring resonators.eLight · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.