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 …

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

Metasurfaces, with extremely exotic capabilities to manipulate electromagnetic (EM) waves,
have derived a plethora of advanced metadevices with intriguing functionalities …

The research of metamaterial shows great potential in the field of solar energy harvesting. In
the past decade, the design of broadband solar metamaterial absorber (SMA) has attracted …

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

Deep artificial neural networks are powerful tools with many possible applications in
nanophotonics. Here, we demonstrate how a deep neural network can be used as a fast …

Using the transfer matrix method, a unidirectional absorber with an ultrabroadband
absorption bandwidth and angular stability is realized in the graphene-embedded photonic …

Toroidal moments in artificial media have received growing attention and considered as a
promising framework for initiating novel approaches to manage intrinsic radiative losses in …

Silicon nanostructure color has achieved unprecedented high printing resolution and larger
color gamut than sRGB. The exact color is determined by localized magnetic and electric …