Integrated nonlinear photonics provides transformative capabilities for controlling,
enhancing and manipulating material nonlinearities in miniaturized on-chip platforms. The …

The growing maturity of nanofabrication has ushered massive sophisticated optical
structures available on a photonic chip. The integration of subwavelength-structured …

Over the last two decades, the capabilities of metasurfaces in light modulation with
subwavelength thickness have been proven, and metasurfaces are expected to miniaturize …

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 …

Recent years have seen the rapid growth and development of the field of smart photonics,
where machine-learning algorithms are being matched to optical systems to add new …

Optical computing promises to improve the speed and energy efficiency of machine learning
applications,,,,–. However, current approaches to efficiently train these models are limited by …

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 …

Flat optics consisting of nanostructures of high–refractive index materials produce lenses
with thin form factors that tend to operate only at specific wavelengths. Recent attempts to …

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 …

Artificial intelligence (AI) is gaining strength, and materials science can both contribute to
and profit from it. In a simultaneous progress race, new materials, systems, and processes …