Synchronization in networks of slightly nonidentical elements
Alexander E. Hramov, Anastasiya E. Khramova, Alexey A. Koronovskii and, Stefano Boccaletti
TL;DR
This paper investigates how slight differences in parameters among chaotic systems in a network affect synchronization, modeling these differences as noise to analyze stability of the synchronized state.
Contribution
It introduces a noise-based modeling approach to understand synchronization stability in networks of nearly identical chaotic systems.
Findings
Parameter dispersion can be effectively modeled as noise.
Synchronization stability is influenced by the distribution of parameters.
The approach provides a quantitative measure of synchronization robustness.
Abstract
We study synchronization processes in networks of slightly non identical chaotic systems, for which a complete invariant synchronization manifold does not rigorously exist. We show and quantify how a slightly dispersed distribution in parameters can be properly modelled by a noise term affecting the stability of the synchronous invariant solution emerging for identical systems when the parameter is set at the mean value of the original distribution.
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