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Persistent stability of a chaotic system

Author

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  • Huber, Greg
  • Pradas, Marc
  • Pumir, Alain
  • Wilkinson, Michael

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.

Suggested Citation

  • Huber, Greg & Pradas, Marc & Pumir, Alain & Wilkinson, Michael, 2018. "Persistent stability of a chaotic system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 517-523.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:517-523
    DOI: 10.1016/j.physa.2017.10.042
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    Cited by:

    1. Wang, Jufeng & Zhou, MengChu & Liu, Chunfeng, 2018. "Stochastic stability of Markovian jump linear systems over networks with random quantization density and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1128-1139.

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