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

Research in photonic computing has flourished due to the proliferation of optoelectronic
components on photonic integration platforms. Photonic integrated circuits have enabled …

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 …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Artificial intelligence tasks across numerous applications require accelerators for fast and
low-power execution. Optical computing systems may be able to meet these domain-specific …

In optical communication systems, fibre nonlinearity is the major obstacle in increasing the
transmission capacity. Typically, digital signal processing techniques and hardware are …

With the proliferation of ultrahigh-speed mobile networks and internet-connected devices,
along with the rise of artificial intelligence (AI), the world is generating exponentially …

Optical imaging is commonly used for both scientific and technological applications across
industry and academia. In image sensing, a measurement, such as of an object's position or …

Deep learning has become a widespread tool in both science and industry. However,
continued progress is hampered by the rapid growth in energy costs of ever-larger deep …