The rise of intelligent matter

C Kaspar, BJ Ravoo, WG van der Wiel, SV Wegner… - Nature, 2021 - nature.com
Artificial intelligence (AI) is accelerating the development of unconventional computing
paradigms inspired by the abilities and energy efficiency of the brain. The human brain …

Polariton condensates for classical and quantum computing

A Kavokin, TCH Liew, C Schneider… - Nature Reviews …, 2022 - nature.com
Polariton lasers emit coherent monochromatic light through a spontaneous emission
process. As a rare example of a system in which Bose–Einstein condensation and …

11 TOPS photonic convolutional accelerator for optical neural networks

X Xu, M Tan, B Corcoran, J Wu, A Boes, TG Nguyen… - Nature, 2021 - nature.com
Convolutional neural networks, inspired by biological visual cortex systems, are a powerful
category of artificial neural networks that can extract the hierarchical features of raw data to …

Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit

T Zhou, X Lin, J Wu, Y Chen, H **e, Y Li, J Fan, H Wu… - Nature …, 2021 - nature.com
There is an ever-growing demand for artificial intelligence. Optical processors, which
compute with photons instead of electrons, can fundamentally accelerate the development …

Physics for neuromorphic computing

D Marković, A Mizrahi, D Querlioz, J Grollier - Nature Reviews Physics, 2020 - nature.com
Neuromorphic computing takes inspiration from the brain to create energy-efficient hardware
for information processing, capable of highly sophisticated tasks. Systems built with standard …

Photonic perceptron based on a Kerr Microcomb for high‐speed, scalable, optical neural networks

X Xu, M Tan, B Corcoran, J Wu… - Laser & Photonics …, 2020 - Wiley Online Library
Optical artificial neural networks (ONNs)—analog computing hardware tailored for machine
learning—have significant potential for achieving ultra‐high computing speed and energy …

[HTML][HTML] Recent advances in physical reservoir computing: A review

G Tanaka, T Yamane, JB Héroux, R Nakane… - Neural Networks, 2019 - Elsevier
Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

Backpropagation algorithms and reservoir computing in recurrent neural networks for the forecasting of complex spatiotemporal dynamics

PR Vlachas, J Pathak, BR Hunt, TP Sapsis, M Girvan… - Neural Networks, 2020 - Elsevier
We examine the efficiency of Recurrent Neural Networks in forecasting the spatiotemporal
dynamics of high dimensional and reduced order complex systems using Reservoir …

Physical reservoir computing—an introductory perspective

K Nakajima - Japanese Journal of Applied Physics, 2020 - iopscience.iop.org
Understanding the fundamental relationships between physics and its information-
processing capability has been an active research topic for many years. Physical reservoir …

Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states

AE Hramov, VA Maksimenko, AN Pisarchik - Physics Reports, 2021 - Elsevier
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …