ArticleNature communications2023
In-memory photonic dot-product engine with electrically programmable weight banks.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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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.
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Who cites it
27 citing papers in PubMed.
- High-Endurance, Low-Loss SbACS photonics · 2026Article
- Analog Tensor Processing With Carbon Nanotube In-Memory Matrix Multiplications for Edge Computer Vision Acceleration.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- How nanophotonics can drive optical computing toward practical applications.Nature nanotechnology · 2026Review
- Integrated Neuromorphic Photonic Computing for AI Acceleration: Emerging Devices, Network Architectures, and Future Paradigms.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- High-precision time-domain parallelism photonic computing.Science advances · 2026Article
- Compact photonic spiking neuron with inherent stochasticity based on phase-change material for probabilistic computing.Nature communications · 2026Article
- Nonvolatile photonic field-programmable coupler array.Science advances · 2026Article
- In-memory multilevel control of generic SO(m) holonomy in photonics.Nature communications · 2026Article
- Harnessing Time-Dependent Magnetic Texture Dynamics via Spin-Orbit Torque for Physics-Enhanced Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Achieving high precision in analog in-memory computing systems.Npj unconventional computing · 2026Review
- Non-volatile tuning of cryogenic silicon photonic micro-ring modulators.Nature communications · 2025Article
- Electrically programmable organic in-display neuromorphic computing.National science review · 2025Article
- Phase-Change Memory for In-Memory Computing.Chemical reviews · 2025Review
- Near-Sensor Edge Computing System Enabled by a CMOS Compatible Photonic Integrated Circuit Platform Using Bilayer AlN/Si Waveguides.Nano-micro letters · 2025Article
- Microheater hotspot engineering for spatially resolved and repeatable multi-level switching in foundry-processed phase change silicon photonics.Nature communications · 2025Article
- Nonlocal phase-change metaoptics for reconfigurable nonvolatile image processing.Light, science & applications · 2025Article
- Bond Confinement-Dependent Peierls Distortion in Epitaxially Grown Bismuth Films.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Energy-Efficient Integrated Electro-Optic Memristors.Nano letters · 2024Article
- Multimodal In-Sensor Computing System Using Integrated Silicon Photonic Convolutional Processor.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Durable and programmable ultrafast nanophotonic matrix of spectral pixels.Nature nanotechnology · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved computational success. Here, we achieve this milestone by demonstrating an in-memory photonic-electronic dot-product engine, one that decouples electronic programming of phase-change materials (PCMs) and photonic computation. Specifically, we develop non-volatile electronically reprogrammable PCM memory cells with a record-high 4-bit weight encoding, the lowest energy consumption per unit modulation depth (1.7 nJ/dB) for Erase operation (crystallization), and a high switching contrast (158.5%) using non-resonant silicon-on-insulator waveguide microheater devices. This enables us to perform parallel multiplications for image processing with a superior contrast-to-noise ratio (≥87.36) that leads to an enhanced computing accuracy (standard deviation σ ≤ 0.007). An in-memory hybrid computing system is developed in hardware for convolutional processing for recognizing images from the MNIST database with inferencing accuracies of 86% and 87%.
Identifiers
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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.