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

Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability. Deep-learning …

Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …

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 …

There is an ever-growing demand for artificial intelligence. Optical processors, which
compute with photons instead of electrons, can fundamentally accelerate the development …

Let there be light–to change the world we want to be! Over the past several decades, and
ever since the birth of the first laser, mankind has witnessed the development of the science …

Electronically reprogrammable photonic circuits based on phase-change chalcogenides
present an avenue to resolve the von-Neumann bottleneck; however, implementation of …