An efficient neural optimizer for resonant nanostructures: demonstration of highly-saturated red silicon structural color

Understand

Freeform nanostructures have the potential to support complex resonances and their interactions, which are crucial for achieving desired spectral responses.

• However, the design optimization of such structures is nontrivial and computationally intensive.
• Furthermore, the current "black box" design approaches for freeform nanostructures often neglect the underlying physics.
• Here, we present a hybrid data-efficient neural optimizer for resonant nanostructures by combining a reinforcement learning algorithm and Powell's local optimization technique.