Recent years have witnessed promising artificial intelligence (AI) applications in many
disciplines, including optics, engineering, medicine, economics, and education. In particular …

The data-science revolution is poised to transform the way photonic systems are simulated
and designed. Photonic systems are, in many ways, an ideal substrate for machine learning …

Conventional human-driven methods face limitations in designing complex functional
metasurfaces. Inverse design is poised to empower metasurface research by embracing fast …

Metasurfaces are ushering in an era of multifunctional control over optical wavefronts
realized with ultrathin planarized devices. Recent advances have been enabling …

Deep learning has become the dominant approach in artificial intelligence to solve complex
data-driven problems. Originally applied almost exclusively in computer-science areas such …

We present a global optimizer, based on a conditional generative neural network, which can
output ensembles of highly efficient topology-optimized metasurfaces operating across a …

Deep neural networks (DNNs) are empirically derived systems that have transformed
traditional research methods, and are driving scientific discovery. Artificial electromagnetic …

A key challenge in metasurface design is the development of algorithms that can effectively
and efficiently produce high-performance devices. Design methods based on iterative …

Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …

Abstract Machine learning, as a study of algorithms that automate prediction and decision‐
making based on complex data, has become one of the most effective tools in the study of …