Biological neural networks effortlessly tackle complex computational problems and excel at
predicting outcomes from noisy, incomplete data, a task that poses significant challenges to …

A high efficiency hardware integration of neural networks benefits from realizing
nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems …

The liaison between photonics and computing is a pillar of modern optics and subject of
cutting-edge research for more than half a century. As in many scientific disciplines, high …

It has long been known that photonic communication can alleviate the data movement
bottlenecks that plague conventional microelectronic processors. More recently, there has …

The explosive growth of data and information has motivated various emerging non-von
Neumann computational approaches in the More-than-Moore era. Photonics neuromorphic …

With an ongoing trend in computing hardware toward increased heterogeneity, domain-
specific coprocessors are emerging as alternatives to centralized paradigms. The tensor …

For many years, optics has been employed in computing, although the major focus has been
and remains to be on connecting parts of computers, for communications, or more …

Ever‐growing demands of bandwidth, computing speed, and power consumption are now
accelerating the transformation of computing research, as work‐at‐home becomes a new …

Neuromorphic photonics is an emerging field at the intersection of photonics and
neuromorphic engineering, with the goal of producing accelerated processors that combine …

Microelectronic computers have encountered challenges in meeting all of today's demands
for information processing. Meeting these demands will require the development of …