ArticleiScience2025
Flex multimode neural network for complete optical computation.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Analysis of birefringence modulation performance in RM-embedded CO-polymer waveguides.iScience · 2026Article
- Pavlov's experiment-inspired optical neural networks based on dual-color fluorescence switching effect.National science review · 2026Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Compact and efficient photonic integrated circuits (PICs) are promising route to solving modern computing challenges. Traditional PICs using cascaded Mach-Zehnder Interferometers (MZIs) or micro-ring resonators (MRRs) are limited to rigid linear matrix operations, requiring electronics for data compression, nonlinear activation, and post-processing. The dependence on electronic processing counteracts the advantages brought by photonics. Here we propose a photonic chip that tackles this problem. The idea is to apply two sets of electrodes on a multimode waveguide: one set for data loading and the other for shaping the neural network by manipulating the multimode light interference flexibly. The shaping process, following a genetic algorithm, resorts again to optical computation to bypass the gradient acquisition problem. Once trained, the chip handles computation completely in the optical domain. Experimentally 91% classification accuracy is achieved on the Iris dataset. Our approach may bring PICs closer to practical computation applications without electronics overload.
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Registered trials
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