Inverse design of bright, dielectric metasurfaces color filters based on back-propagation and multi-valued artificial neural networks
Résumé
The present work showcases an innovative optimization methodology based on deep learning that combines Multi-Valued Artificial Neural Networks and back-propagation optimization. The methodology addresses the inherent limitations of conventional approaches when employed in isolation. We applied the proposed methodology to design structural color filters that surpasses the sRGB gamut while preserving fabrication constraints.
Origine | Fichiers produits par l'(les) auteur(s) |
---|