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Lyapunov analysis of data-driven models of high dimensional dynamics using reservoir computing: Lorenz-96 system and fluid flow

Miki U Kobayashi, Kengo Nakai, Yoshitaka Saiki • Journal of Physics: Complexity (2024)

We computed the Lyapunov spectrum and finite-time Lyapunov exponents of a data-driven model constructed using reservoir computing. This analysis was performed for two dynamics that exhibit a highly dimensionally unstable structure. We focus...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-072X/ad5264

Large-scale quantum reservoir computing using a Gaussian Boson Sampler

Valeria Cimini, Mandar M. Sohoni, Federico Presutti, Benjamin K. Malia et al. • npj Quantum Information (2026)

Abstract A Gaussian boson sampler (GBS) is a special-purpose quantum computer that can be practically realized at a large scale in optics. Here we report on experiments in which we used a frequency-multiplexed GBS with > 400 modes as a quan...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41534-026-01251-w

Photonic Neural Networks: A Survey

Lorenzo De Marinis, Marco Cococcioni, P. Castoldi, Nicola Andriolli • IEEE Access (2019)

Photonic solutions are today a mature industrial reality concerning high speed, high throughput data communication and switching infrastructures. It is still a matter of investigation to what extent photonics will play a role in next-genera...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2019.2957245

Attractor reconstruction by machine learning

Zhixin Lu, Brian R. Hunt, Edward Ott • Chaos An Interdisciplinary Journal of Nonlinear Science (2018)

A machine-learning approach called "reservoir computing" has been used successfully for short-term prediction and attractor reconstruction of chaotic dynamical systems from time series data. We present a theoretical framework that describes...

OPENALEX Open Access DOI: https://doi.org/10.1063/1.5039508