The editorial introduces the joint theme issue of Advanced Photonics and Advanced Photonics Nexus, “Photonics and AI,” which showcases the latest research at the intersection of...

Demetri Psaltis (École Polytechnique Fédérale de Lausanne) discusses advances in optical computing, in conversation with Guohai Situ (Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences), for the Advanced

The article comments on a recently developed neural network that enables ultrathin flat optics imaging in full...

Metal halide perovskite materials have rapidly advanced in the perovskite solar cells and light-emitting diodes due to their superior optoelectronic properties. The structure of perovskite optoelectronic devices includes the perov

Planar cameras with high performance and wide field of view (FOV) are critical in various fields, requiring highly compact and integrated technology. Existing wide FOV metalenses show great potential for ultrathin optical componen

The global chip industry is grappling with dual challenges: a profound shortage of new chips and a surge of counterfeit chips valued at $75 billion, introducing substantial risks of malfunction and unwanted surveillance. To counte

Quantitative phase imaging (QPI) is a label-free technique that provides optical path length information for transparent specimens, finding utility in biology, materials science, and engineering. Here, we present QPI of a three-di

Optical superoscillation enables far-field superresolution imaging beyond diffraction limits. However, existing superoscillatory lenses for spatial superresolution imaging systems still confront critical performance limitations du

Optical computing is considered a promising solution for the growing demand for parallel computing in various cutting-edge fields that require high integration and high-speed computational capacity. We propose an optical computati

Machine-learning techniques have gained popularity in nanophotonics research, being applied to predict optical properties, and inversely design structures. However, one limitation is the cost of acquiring training data, as complex

We propose an approach for recognizing the pose and surface material of diverse objects, leveraging diffuse reflection principles and data fusion. Through theoretical analysis and the derivation of factors influencing diffuse refl

Leveraging an optical system for image encryption is a promising approach to information security since one can enjoy parallel, high-speed transmission, and low-power consumption encryption features. However, most existing optical

Two mainstream approaches for solving inverse sample reconstruction problems in programmable illumination computational microscopy rely on either deep models or physical models. Solutions based on physical models possess strong ge

Deep learning has transformed computational imaging, but traditional pixel-based representations limit their ability to capture continuous multiscale object features. Addressing this gap, we introduce a local conditional neural fi

Phase recovery, calculating the phase of a light wave from its intensity measurements, is essential for various applications, such as coherent diffraction imaging, adaptive optics, and biomedical imaging. It enables the reconstruc

Photonic computing has recently become an interesting paradigm for high-speed calculation of computing processes using light–matter interactions. Here, we propose and study an electromagnetic wave-based structure with the ab