Reconfigurable optical metasurfaces are rapidly emerging as a major frontier in photonics
research, development and commercialization. They promise compact, lightweight and …

Innovative approaches and tools play an important role in sha** design, characterization
and optimization for the field of photonics. As a subset of machine learning that learns …

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

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 …

Deep learning in the context of nano-photonics is mostly discussed in terms of its potential
for inverse design of photonic devices or nano-structures. Many of the recent works on …

Meta-optics has achieved major breakthroughs in the past decade; however, conventional
forward design faces challenges as functionality complexity and device size scale up …

Nanophotonics has garnered intensive attention due to its unique capabilities in molding the
flow of light in the subwavelength regime. Metasurfaces (MSs) and photonic integrated …

The refractive-lens technique has been well developed over a long period of evolution,
offering powerful imaging functionalities, such as microscopes, telescopes, and …

Optical metasurfaces with subwavelength thickness hold considerable promise for future
advances in fundamental optics and novel optical applications due to their unprecedented …

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 …