ArticleLight, science & applications2021
Nanoprinted high-neuron-density optical linear perceptrons performing near-infrared inference on a CMOS chip.
Article in Light, science & applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- How nanophotonics can drive optical computing toward practical applications.Nature nanotechnology · 2026Review
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- Microcomb-enabled parallel self- calibration optical convolution streaming processor.Light, science & applications · 2026Article
- What is next for LLMs? Pushing the boundaries of next-gen AI computing hardware with photonic chips.Nanophotonics (Berlin, Germany) · 2025Review
- Review for optical metalens based on metasurfaces: fabrication and applications.Microsystems & nanoengineering · 2025Review
- Broadband unidirectional visible imaging using wafer-scale nano-fabrication of multi-layer diffractive optical processors.Light, science & applications · 2025Article
- Ultracompact 3D integrated photonic chip for high-fidelity high-dimensional quantum gates.Science advances · 2025Article
- Neuromorphic Computing Using Synaptic Plasticity of Supercapacitors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- A guidance to intelligent metamaterials and metamaterials intelligence.Nature communications · 2025Review
- Wavefront-aberration-tolerant diffractive deep neural networks using volume holographic optical elements.Scientific reports · 2025Article
- TOPS-speed complex-valued convolutional accelerator for feature extraction and inference.Nature communications · 2025Article
- Optical neural networks: progress and challenges.Light, science & applications · 2024Review
- Harnessing the capabilities of VCSELs: unlocking the potential for advanced integrated photonic devices and systems.Light, science & applications · 2024Review
- Neural network-assisted meta-router for fiber mode and polarization demultiplexing.Nanophotonics (Berlin, Germany) · 2024Article
- Femtosecond laser direct nanolithography of perovskite hydration for temporally programmable holograms.Nature communications · 2024Article
- All-optical phase conjugation using diffractive wavefront processing.Nature communications · 2024Article
- All-optical image denoising using a diffractive visual processor.Light, science & applications · 2024Article
- Article
- High-throughput terahertz imaging: progress and challenges.Light, science & applications · 2023Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Optical machine learning has emerged as an important research area that, by leveraging the advantages inherent to optical signals, such as parallelism and high speed, paves the way for a future where optical hardware can process data at the speed of light. In this work, we present such optical devices for data processing in the form of single-layer nanoscale holographic perceptrons trained to perform optical inference tasks. We experimentally show the functionality of these passive optical devices in the example of decryptors trained to perform optical inference of single or whole classes of keys through symmetric and asymmetric decryption. The decryptors, designed for operation in the near-infrared region, are nanoprinted on complementary metal-oxide-semiconductor chips by galvo-dithered two-photon nanolithography with axial nanostepping of 10 nm
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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.