ArticleNature communications2023
Correlating metasurface spectra with a generation-elimination framework.
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 17 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
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Who cites it
17 citing papers in PubMed.
- Cauchyformer: Few-Shot Spectrum Inference for Photonic Metasurfaces via Mixture of Cauchy.ACS omega · 2026Article
- On the Role of Artificial Intelligent Technology for Millimetre-Wave and Terahertz Applications.Sensors (Basel, Switzerland) · 2025Review
- Anchor-controlled generative adversarial network for high-fidelity electromagnetic and structurally diverse metasurface design.Nanophotonics (Berlin, Germany) · 2025Article
- Polarization dependent bound states in continuum in a tetramer metasurface discovered by random forest algorithm.Scientific reports · 2025Article
- Article
- Transfer Learning Empowered Multiple-Indicator Optimization Design for Terahertz Quasi-Bound State in the Continuum Biosensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Multi-Dimensional Multiplexed Metasurface for Multifunctional Near-Field Modulation by Physics-Driven Intelligent Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- MetaSeeker: sketching an open invisible space with self-play reinforcement learning.Light, science & applications · 2025Article
- Review
- Frequency transfer and inverse design for metasurface under multi-physics coupling by Euler latent dynamic and data-analytical regularizations.Nature communications · 2025Article
- Empowering nanophotonic applications via artificial intelligence: pathways, progress, and prospects.Nanophotonics (Berlin, Germany) · 2025Review
- A guidance to intelligent metamaterials and metamaterials intelligence.Nature communications · 2025Review
- Meta-Attention Deep Learning for Smart Development of Metasurface Sensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Physics-Informed Inverse Design of Programmable Metasurfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Harnessing the Missing Spectral Correlation for Metasurface Inverse Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Creating Anti-Chiral Exceptional Points in Non-Hermitian Metasurfaces for Efficient Terahertz Switching.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- On-demand Doppler-offset beamforming with intelligent spatiotemporal metasurfaces.Nanophotonics (Berlin, Germany) · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Inferring optical response from other correlated optical response is highly demanded for vast applications such as biological imaging, material analysis, and optical characterization. This is distinguished from widely-studied forward and inverse designs, as it is boiled down to another different category, namely, spectra-to-spectra design. Whereas forward and inverse designs have been substantially explored across various physical scenarios, the spectra-to-spectra design remains elusive and challenging as it involves intractable many-to-many correspondences. Here, we first dabble in this uncharted area and propose a generation-elimination framework that can self-orient to the best output candidate. Such a framework has a strong built-in stochastically sampling capability that automatically generate diverse nominations and eliminate inferior nominations. As an example, we study terahertz metasurfaces to correlate the reflection spectra from low to high frequencies, where the inaccessible spectra are precisely forecasted without consulting structural information, reaching an accuracy of 98.77%. Moreover, an innovative dimensionality reduction approach is executed to visualize the distribution of the abstract correlated spectra data encoded in latent spaces. These results provide explicable perspectives for deep learning to parse complex physical processes, rather than "brute-force" black box, and facilitate versatile applications involving cross-wavelength information correlation.
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.