ReviewLight, science & applications2022
Photonic matrix multiplication lights up photonic accelerator and beyond.
Review in Light, science & applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
84 citing papers in PubMed.
- 192-dimensional wavelength-/mode-/polarization-multiplexed photonic architecture for highly parallel optical computing.National science review · 2026Article
- How nanophotonics can drive optical computing toward practical applications.Nature nanotechnology · 2026Review
- Programmable photonic neural engine with all-optical nonlinear activation and 40,000 connections.Science advances · 2026Article
- On-chip non-volatile all-optical residual neural network accelerator.Light, science & applications · 2026Article
- Photonic integrated computing engine for concurrent optical computing.Nature communications · 2026Article
- Grating based interferometric devices on a silicon photonic platform.Scientific reports · 2026Article
- Generation of ultra-broadband frequency comb in strongly bistable nonlinear magnonic resonator.Nature communications · 2026Article
- Photonic Mixture-of-Experts for scalable multi-task on-chip optical neural networks.Nature communications · 2026Article
- Spatial-Wavelength Multiplexing Error-Controlled Photonic Analog Computing System.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- Recent Progress in Nanophotonics for Green Energy, Medicine, Healthcare, and Optical Computing Applications.Materials (Basel, Switzerland) · 2026Review
- Diffractive Optical Neural Networks: Pathways Toward Intelligent and Scalable Photonic Computing.Nanophotonics (Berlin, Germany) · 2026Review
- Monolithic Silicon-Photonics Sign-Sign Dot-Product Circuits Toward Artificial Intelligence and Multiple-Input Multiple-Output Accelerators.Nanophotonics (Berlin, Germany) · 2026Article
- Pavlov's experiment-inspired optical neural networks based on dual-color fluorescence switching effect.National science review · 2026Article
- Non-Volatile Phase Modulation with Ultralow Energy Consumption Enabled by 2D Ferroelectric/TMD Heterostructures.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Femto-joule threshold reconfigurable all-optical nonlinear activators for picosecond pulsed optical neural networks.Light, science & applications · 2026Article
- Inverse-Designed On-Chip Orbital Angular Momentum Mode Converter for Optical Convolution Acceleration.Nanophotonics (Berlin, Germany) · 2026Article
- Physical neural networks using sharpness-aware training.Nature communications · 2026Article
- Demonstrating completeness in optical neural computing.Light, science & applications · 2026Article
- Article
24 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Matrix computation, as a fundamental building block of information processing in science and technology, contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms. Photonic accelerators are designed to accelerate specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for computing resources and capacity. Photonic matrix multiplication has much potential to expand the domain of telecommunication, and artificial intelligence benefiting from its superior performance. Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors. In this review, we first introduce the methods of photonic matrix multiplication, mainly including the plane light conversion method, Mach-Zehnder interferometer method and wavelength division multiplexing method. We also summarize the developmental milestones of photonic matrix multiplication and the related applications. Then, we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years. Finally, we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.
Identifiers
What OpenQuestion holds
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.