Artificial intelligence has prevailed in all trades and professions due to the assistance of big
data resources, advanced algorithms, and high-performance electronic hardware. However …

This tutorial–review on applications of artificial neural networks in photonics targets a broad
audience, ranging from optical research and engineering communities to computer science …

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 …

Advancements in optical coherence control,,,–have unlocked many cutting-edge
applications, including long-haul communication, light detection and ranging (LiDAR) and …

Diffractive neural network in electromagnetic wave–driven system has attracted great
attention due to its ultrahigh parallel computing capability and energy efficiency. However …

Modes of propagation through an optical system are generally defined as the eigensolutions
of the wave equation in the system. When propagation occurs through complicated or highly …

Photonics offers a transformative approach to artificial intelligence (AI) and neuromorphic
computing by enabling low-latency, high-speed, and energy-efficient computations …

Wireless sensing of the wave propagation direction from radio sources lays the foundation
for communication, radar, navigation, etc. However, the existing signal processing paradigm …

Photonic integrated circuits (PICs) with rapid prototy** and reprogramming capabilities
promise revolutionary impacts on a plethora of photonic technologies. We report direct-write …

Integrated photonic neural networks (PNNs) are at the forefront of AI computing, leveraging
light's unique properties, such as large bandwidth, low latency, and potentially low power …