A Machine-Learning-Enabled Metasurface Adapting to the Environment
Paper i proceeding, 2026
We propose a machine-learning-based adaptive algorithm for tunable metasurfaces in a changing environment. We use a neural network processing information from the metasurface to predict the environment, followed by another neural network to reconfigure it. We demonstrate this for a metasurface adapting to a beam with unknown angle of incidence.
metamaterials
adaptive metasurfaces
machine learning
Författare
Thijs Albert van Rossum
Chalmers, Fysik, Kondenserad materie- och materialteori
Thomas Koschny
Iowa State University
Philippe Tassin
Chalmers, Fysik, Kondenserad materie- och materialteori
International Conference on Metamaterials, Photonic Crystals and Plasmonics
24291390 (eISSN)
1098-1099
16th International Conference on Metamaterials, Photonic Crystals and Plasmonics, META 2026
Dublin, Ireland,
Dublin, Ireland,
Utveckling av nya fotoniska metaytor med hjälp av artificiell intelligens
Vetenskapsrådet (VR) (2020-05284), 2020-12-01 -- 2024-11-30.
Ämneskategorier (SSIF 2025)
Telekommunikation
Annan fysik
Signalbehandling