TL;DR
Stable chaos extends chaotic behavior to continuous systems, characterized by irregular yet stable dynamics, with tools and models discussed to understand transitions from order to chaos.
Contribution
This review introduces the concept of stable chaos, compares it with deterministic chaos, and presents analytical tools and models illustrating its properties.
Findings
Stable chaos exhibits irregular yet linearly stable dynamics.
Transitions from order to stable chaos are analyzed.
Models like the diatomic hard-point gas and neural networks exemplify stable chaos.
Abstract
Stable chaos is a generalization of the chaotic behaviour exhibited by cellular automata to continuous-variable systems and it owes its name to an underlying irregular and yet linearly stable dynamics. In this review we discuss analogies and differences with the usual deterministic chaos and introduce several tools for its characterization. Some examples of transitions from ordered behavior to stable chaos are also analyzed to further clarify the underlying dynamical properties. Finally, two models are specifically discussed: the diatomic hard-point gas chain and a network of globally coupled neurons.
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