Metasurface-enabled on-chip multiplexed diffractive neural networks in the visible
Open accessAbstract
Replacing electrons with photons is a compelling route toward high-speed, massively parallel, and low-power artificial intelligence computing. Recently, diffractive networks composed of phase surfaces were trained to perform machine learning tasks through linear optical transformations. However, the existing architectures often comprise bulky components and, most critically, they cannot mimic the human brain for multitasking. Here, we demonstrate a multi-skilled diffractive neural network based on a metasurface device, which can perform on-chip multi-channel sensing and multitasking in the visible. The polarization multiplexing scheme of the subwavelength nanostructures is applied to construct a multi-channel classifier framework for simultaneous recognition of digital and fashionable items. The areal density of the artificial neurons can reach up to 6.25 × 10 6 mm −2 multiplied by the number of channels. The metasurface is integrated with the mature complementary metal-oxide semiconductor imaging sensor, providing a chip-scale architecture to process information directly at physical layers for energy-efficient and ultra-fast image processing in machine vision, autonomous driving, and precision medicine.
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Recent prototypes have demonstrated SIMs with capabilities for MIMO beamforming, radar sensing, and image classification.
“Recent prototypes have demonstrated SIMs with impressive capabilities for applications such as MIMO beamforming [25], radar sensing [26], and image classification [27].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [27]
The Results report an experimental on-chip metasurface diffractive neural network that classifies images of digits and fashion items, supporting the image-classification application attributed to [27]. The Discussion describes a multilayer version as designed and simulated, not experimentally demonstrated; thus this paper does not establish a prototype of a stacked intelligent metasurface (SIM). MIMO beamforming and radar sensing have separate citations in the citing sentence. (LLM, conf=0.84)
Experimental — accuracy not yet measuredLuo et al. developed a SIM device that can simultaneously recognize digital and fashionable items by leveraging polarization multiplexing in the visible spectrum.
“To enhance the parallelism capability of SIM, Luo et al. [27] developed a SIM device that can simultaneously recognize digital and fashionable items by leveraging polarization multiplexing in the visible spectrum.”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [27]
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- Authors
- Luo, X., Hu, Y., Ou, X., Li, X., Lai, J., Liu, N., Cheng, X., Pan, A., & Duan, H.
- Affiliations
- Tongji University (CN)
- Hunan University (CN)
- University of Stuttgart (DE)
- Corresponding author
- Hu, Yueqiang
- Duan, Huigao
- Venue
- Light: Science & Applications
- Published
- 2022-05-27
- Volume
- 11
- Issue
- 1
- Pages
- 158-158
- ISSN
- 2047-7538 (ISSN-L)
- PMC
- PMC9142536
- OpenAlex
- W3184400519
- Cited by
- 335
- References
- 76
- Citations by year
- 2026: 58 · 2025: 105 · 2024: 100 · 2023: 56 · 2022: 15
- FWCI
- 15.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Light Science & Applications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- arXiv (Cornell University)
- Funders
- National Natural Science Foundation of China (52005175)
- Topics
- Physical Sciences › Materials Science › Electronic, Optical and Magnetic Materials › Metamaterials and Metasurfaces Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Reservoir Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Keywords
- metasurfaces, diffractive neural networks, polarization multiplexing, on-chip image processing, optical neuromorphic computing, artificial neurons
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