Daniel Brunner

All-optical neuromorphic computing in optical networks of semiconductor lasers

2016

Networks of interconnected nodes are at the heart of every neural network concept. While neural networks have been implemented in various hardware systems, the efficient realization of such networks still represents a major challenge. We …

Scaling Laws and Topology-Properties of Boolean Reinforcement Learning in Photonic Neural Networks

2019

Since recent years artificial intelligence and more particularly neural networks play a major role in our technological societies. Nevertheless, neural networks still remain emulated by traditional computers, resulting in challenging problems such as parallelization, energy …

Tutorial: Reservoir Computing

2018 · HAL (Le Centre pour la Communication Scientifique Directe)

International audience

Direct coupling of nonlinear integrated cavities for all-optical reservoir computing

2023 · arXiv (Cornell University)

We consider theoretically a network of directly coupled optical microcavities to implement a space-multiplexed optical neural network in an integrated nanophotonic circuit. Nonlinear photonic network integrations based on direct coupling ensures a highly dense integration, …

Experimental reservoir computing with diffractively coupled VCSELs

2024 · Optics Letters

We present experiments on reservoir computing (RC) using a network of vertical-cavity surface-emitting lasers (VCSELs) that we diffractively couple via an external cavity. Our optical reservoir computer consists of 24 physical VCSEL nodes. We evaluate …

Guided nonlinear optics for information processing

2025 · Nanophotonics

This special issue explores the dynamic and rapidly evolving field of optical computing, with a focus on guided nonlinear optics for information processing.Recent years have seen a resurgence of interest in this area [1], fuelled …