A Machine-Learning-Enabled Metasurface Adapting to the Environment
Paper in 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
Author
Thijs Albert van Rossum
Chalmers, Physics, Condensed Matter and Materials Theory
Thomas Koschny
Iowa State University
Philippe Tassin
Chalmers, Physics, Condensed Matter and Materials Theory
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,
Creating New Photonic Metasurfaces with Artificial Intelligence
Swedish Research Council (VR) (2020-05284), 2020-12-01 -- 2024-11-30.
Subject Categories (SSIF 2025)
Telecommunications
Other Physics Topics
Signal Processing