There has been a resurgence of interest in optical computing since the early 2010s, both in
academia and in industry, with much of the excitement centred around special-purpose …

Optical microcombs represent a new paradigm for generating laser frequency combs based
on compact chip-scale devices, which have underpinned many modern technological …

The emergence of parallel convolution-operation technology has substantially powered the
complexity and functionality of optical neural networks (ONN) by harnessing the dimension …

Reservoir computing originates in the early 2000s, the core idea being to utilize dynamical
systems as reservoirs (nonlinear generalizations of standard bases) to adaptively learn …

Photonic computing enables faster and more energy-efficient processing of vision data,,,–.
However, experimental superiority of deployable systems remains a challenge because of …

Integrated photonic neural networks provide a promising platform for energy-efficient, high-
throughput machine learning with extensive scientific and commercial applications. Photonic …

As a fundamental optical approach to interferometry, Sagnac interference has been widely
used for reflection manipulation, precision measurements, and spectral engineering in …

Integrated silicon photonics has sparked a significant ramp-up of investment in both
academia and industry as a scalable, power-efficient, and eco-friendly solution. At the heart …

Integrated photonic devices operating via optical nonlinearities offer a powerful solution for
all‐optical information processing, yielding processing speeds that are well beyond that of …

The development of artificial intelligence is typically focused on computer algorithms and
integrated circuits. Recently, all-optical diffractive deep neural networks have been created …