ArticleNature communications2025
Digital-analog hybrid matrix multiplication processor for optical neural networks.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- Reconfigurable optical arithmetic logic unit and its applications.Nature communications · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
Optical neural networks (ONNs) promise computing efficiency beyond microelectronics for modern artificial intelligence (AI). Current ONNs using analog matrix-vector multiplication (MVM) implementations are fundamentally limited in numerical precision due to accumulated noise in electro-optical processing. We propose a digital-analog hybrid MVM architecture that achieves a high numerical precision without sacrificing computing efficiency. Our fabricated proof-of-concept hybrid optical processor (HOP) achieves 16-bit precision in high-definition image processing, with a pixel error rate of 1.8 × 10
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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.