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

Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

Reservoir computing is a highly efficient network for processing temporal signals due to its
low training cost compared to standard recurrent neural networks, and generating rich …

Artificial neural networks are computational network models inspired by signal processing in
the brain. These models have dramatically improved performance for many machine …

Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and
interact to process information. Taking inspiration from this behaviour to realize high-density …

Polariton lasers emit coherent monochromatic light through a spontaneous emission
process. As a rare example of a system in which Bose–Einstein condensation and …

Understanding the fundamental relationships between physics and its information-
processing capability has been an active research topic for many years. Physical reservoir …

The increasing demands on information processing require novel computational concepts
and true parallelism. Nevertheless, hardware realizations of unconventional computing …

Reservoir computing, originally referred to as an echo state network or a liquid state
machine, is a brain-inspired paradigm for processing temporal information. It involves …

We review a novel paradigm that has emerged in analogue neuromorphic optical
computing. The goal is to implement a reservoir computer in optics, where information is …