Using Synchronization for Prediction of High-Dimensional Chaotic Dynamics

TL;DR

This paper demonstrates that synchronization between a numerical model and experimental data enables effective prediction of high-dimensional chaotic dynamics in an optoelectronic delay system, with potential applications in forecasting complex systems.

Contribution

It introduces a novel approach using synchronization for data assimilation and prediction in high-dimensional chaotic systems with delay dynamics.

Findings

Synchronization allows accurate prediction for several delay periods.

The system exhibits approximately 15-dimensional chaos.

Delay differential equations effectively model the experimental system.

Abstract

We experimentally observe the nonlinear dynamics of an optoelectronic time-delayed feedback loop designed for chaotic communication using commercial fiber optic links, and we simulate the system using delay differential equations. We show that synchronization of a numerical model to experimental measurements provides a new way to assimilate data and forecast the future of this time-delayed high-dimensional system. For this system, which has a feedback time delay of 22 ns, we show that one can predict the time series for up to several delay periods, when the dynamics is about 15 dimensional.