2 papers
physics.optics2025
A NEAT Approach to Evolving Neural-Network-based Optimization of Chiral Photonic Metasurfaces: Application of a Neuro-Evolution Pipeline
Davide Filippozzi, Arash Rahimi-Iman
The design of chiral metasurfaces with tailored optical properties remains a central challenge in nanophotonics due to the highly nonlinear relationship between geometry and chirop…
physics.optics2025
Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches
Davide Filippozzi, Alexandre Mayer, Nicolas Roy +2
Chiral photonic metasurfaces provide unique capabilities for tailoring light-matter interactions, which are essential for next-generation photonic devices. Here, we report an advan…