Optical information processing and computing can potentially offer enhanced performance,
scalability and energy efficiency. However, achieving nonlinearity—a critical component of …

Nonlinear encoding of optical information can be achieved using various forms of data
representation. Here, we analyze the performances of different nonlinear information …

The increasing size of neural networks for deep learning applications and their energy
consumption create a need for alternative neuromorphic approaches, for example, using …

Artificial Intelligence (AI) demands large data flows within datacenters, heavily relying on
multicasting data transfers. As AI models scale, the requirement for high-bandwidth and low …

Physical neural networks (PNNs) are a class of neural-like networks that leverage the
properties of physical systems to perform computation. While PNNs are so far a niche …

Over the last two decades, spatial light modulators (SLMs) have revolutionised our ability to
shape optical fields. They grant independent dynamic control over thousands of degrees-of …