Nonlinear Sciences – Chaotic Dynamics
Scientific paper
2011-02-15
Phys. Rev. Lett. 107, 114101 (2011)
Nonlinear Sciences
Chaotic Dynamics
4 pages, 3 figures. To appear in Phys. Rev. Lett
Scientific paper
10.1103/PhysRevLett.107.114101
In this Letter we show that the analysis of Lyapunov-exponents fluctuations contributes to deepen our understanding of high-dimensional chaos. This is achieved by introducing a Gaussian approximation for the large deviation function that quantifies the fluctuation probability. More precisely, a diffusion matrix $\bf D$ (a dynamical invariant itself) is measured and analysed in terms of its principal components. The application of this method to three (conservative, as well as dissipative) models, allows: (i) quantifying the strength of the effective interactions among the different degrees of freedom; (ii) unveiling microscopic constraints such as those associated to a symplectic structure; (iii) checking the hyperbolicity of the dynamics.
Kuptsov Pavel V.
Politi Antonio
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