In this review, we survey the recent advances in nonlinear optics and the applications of two-
dimensional (2D) materials. We briefly cover the key developments pertaining to research in …

In this Review, the theory and applications of optical micro‐and nano‐resonators are
presented from the underlying concept of their natural resonances, the so‐called quasi …

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

We use inverse design to discover metalens structures that exhibit broadband, achromatic
focusing across low, moderate, and high numerical apertures. We show that standard unit …

The robust, sensitive, and selective detection of targeted biomolecules in their native
environment by prospective nanostructures holds much promise for real-time, accurate, and …

In this article, we review strong light-matter coupling at the interface of materials science,
quantum chemistry, and quantum photonics. The control of light and heat at thermodynamic …

The specificity of modal-expansion formalisms is their capabilities to model the physical
properties in the natural resonance-state basis of the system in question, leading to a …

On-chip nanophotonic devices are a class of devices capable of controlling light on a chip to
realize performance advantages over ordinary building blocks of integrated photonics …

We formulate and exploit a computational inverse-design method based on topology
optimization to demonstrate photonic crystal structures supporting complex spectral …

Neural operators have emerged as a powerful tool for solving partial differential equations in
the context of scientific machine learning. Here, we implement and train a modified Fourier …