The past decades have witnessed an explosion of interest in topological materials, and a lot
of mathematical concepts have been introduced in condensed matter physics. Among them …

Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …

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

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

The catalytic transformation of CO2 into valuable fuels/chemicals is a promising and
economically profitable process because it offers an alternative toward fossil feedstocks and …

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 …

Large-scale, highly integrated and low-power-consuming hardware is becoming
progressively more important for realizing optical neural networks (ONNs) capable of …

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

Programmable photonic integrated circuits (PICs) are dense assemblies of tunable elements
that provide flexible reconfigurability to enable different functions to be selected; however …

Diffusion driven by temperature or concentration gradients is a fundamental mechanism of
energy and mass transport that inherently differs from wave propagation in both physical …