Persistent stability of a chaotic system

Greg Huber, Marc Pradas, Alain Pumir and Michael Wilkinson

Physica A: Statistical Mechanics and its Applications, 2018, vol. 492, issue C, 517-523

Abstract: We report that trajectories of a one-dimensional model for inertial particles in a random velocity field can remain stable for a surprisingly long time, despite the fact that the system is chaotic. We provide a detailed quantitative description of this effect by developing the large-deviation theory for fluctuations of the finite-time Lyapunov exponent of this system. Specifically, the determination of the entropy function for the distribution reduces to the analysis of a Schrödinger equation, which is tackled by semi-classical methods. The system has ‘generic’ instability properties, and we consider the broader implications of our observation of long-term stability in chaotic systems.

Keywords: Stochastic analysis methods; Nonlinear dynamics and chaos; Fluctuation phenomena; Random processes; Noise; Brownian motion; Butterfly effect (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:492:y:2018:i:c:p:517-523

DOI: 10.1016/j.physa.2017.10.042

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