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The Lyapunov exponents of a dynamical system measure the average rate of exponential stretching along an orbit. Positive exponents are often taken as a defining characteristic of chaotic dynamics. However, the standard…

Chaotic Dynamics · Physics 2024-09-16 E. Sander , J. D. Meiss

For a better understanding of the chaotic behavior of systems of many moving particles it is useful to look at other systems with many degrees of freedom. An interesting example is the high-dimensional Lorentz gas, which, just like a system…

Chaotic Dynamics · Physics 2009-11-10 Astrid S. de Wijn , Henk van Beijeren

We show that in generic one-dimensional Hamiltonian lattices the diffusion coefficient of the maximum Lyapunov exponent diverges in the thermodynamic limit. We trace this back to the long-range correlations associated with the evolution of…

Chaotic Dynamics · Physics 2016-08-03 Diego Pazo , Juan M. Lopez , Antonio Politi

We study dimension theory for dissipative dynamical systems, proving a conditional variational principle for the quotients of Birkhoff averages restricted to the recurrent part of the system. On the other hand, we show that when the whole…

Dynamical Systems · Mathematics 2018-09-18 Godofredo Iommi , Thomas Jordan , Mike Todd

We study random dynamical systems generated by volume-preserving piecewise $C^{1}$ maps. For this class of systems, we establish an invariance principle stating that if all Lyapunov exponents vanish, then there exists a measurable family of…

Dynamical Systems · Mathematics 2026-01-21 Gianluigi Del Magno , João Lopes Dias , José Pedro Gaivão

We apply to bidimensional chaotic maps the numerical method proposed by Ginelli et al. to approximate the associated Oseledets splitting, i.e. the set of linear subspaces spanned by the so called covariant Lyapunov vectors (CLV) and…

Chaotic Dynamics · Physics 2016-12-21 Matteo Sala , Cesar Manchein , Roberto Artuso

We study the problem of estimating the maximal Lyapunov exponent of dominated cocycles. In particular we are concerned with cocycles over Gibbs states on shifts of finite type for which both the function defining the cocycle and the…

Dynamical Systems · Mathematics 2021-05-13 Mark Piraino

We investigate through a Generalized Langevin formalism the phenomenon of anomalous diffusion for asymptotic times, and we generalized the concept of the diffusion exponent. A method is proposed to obtain the diffusion coefficient…

Statistical Mechanics · Physics 2015-03-20 R. M. S. Ferreira , M. V. S. Santos , C. C. Donato , J. S. Andrade , F. A. Oliveira

We prove existence of (at most denumerable many) absolutely continuous invariant probability measures for random one-dimensional dynamical systems with asymptotic expansion. If the rate of expansion (Lyapunov exponents) is bounded away from…

Dynamical Systems · Mathematics 2014-11-18 Vitor Araujo , Javier Solano

Brains process information through the collective dynamics of large neural networks. Collective chaos was suggested to underlie the complex ongoing dynamics observed in cerebral cortical circuits and determine the impact and processing of…

Chaotic Dynamics · Physics 2020-06-04 Rainer Engelken , Fred Wolf , L. F. Abbott

We show that linear analytic cocycles where all Lyapunov exponents are negative infinite are nilpotent. For such one-frequency cocycles we show that they can be analytically conjugated to an upper triangular cocycle or a Jordan normal form.…

Dynamical Systems · Mathematics 2018-03-14 Christian Sadel , Disheng Xu

In a recent Letter, Barnett, Tajima, Nishihara, Ueshima and Furukawa obtained a theoretical expression for the maximum Lyapunov exponent $\lambda_1$ of a dilute gas. They conclude that $\lambda_1$ is proportional to the cube root of the…

Statistical Mechanics · Physics 2009-10-31 A. Torcini , Ch. Dellago , H. A. Posch

By interpreting a temporal network as a trajectory of a latent graph dynamical system, we introduce the concept of dynamical instability of a temporal network, and construct a measure to estimate the network Maximum Lyapunov Exponent (nMLE)…

Data Analysis, Statistics and Probability · Physics 2023-05-03 Annalisa Caligiuri , Victor M. Eguiluz , Leonardo di Gaetano , Tobias Galla , Lucas Lacasa

In the dynamical systems approach to describing turbulent or otherwise chaotic flows, an important quantity is the Lyapunov exponents and vectors that characterize the strange attractor of the flow. In particular, knowledge of the Lyapunov…

Fluid Dynamics · Physics 2019-05-01 Malik Hassanaly , Venkat Raman

We study sporadic randomness by means of a non-extensive form of Lyapunov coefficient. We recover from a different perspective the same conclusion as that of an earlier work, namely, that the ordinary Pesin theorem applies (P.Gaspard and…

Statistical Mechanics · Physics 2007-05-23 Massimiliano Ignaccolo , Paolo Grigolini

Time dependent mode structure for the Lyapunov vectors associated with the stepwise structure of the Lyapunov spectra and its relation to the momentum auto-correlation function are discussed in quasi-one-dimensional many-hard-disk systems.…

Chaotic Dynamics · Physics 2007-05-23 Tooru Taniguchi , Gary P. Morriss

We consider a mechanism for area preserving Hamiltonian systems which leads to the enhanced probability, $P(\lambda, t)$, to find small values of the finite time Lyapunov exponent, $\lambda$. In our investigation of chaotic dynamical…

Chaotic Dynamics · Physics 2007-05-23 P. G. Silvestrov , I. V. Ponomarev

This paper provides a systematic exposition of Lyapunov stability for compact sets in locally compact metric spaces. We explore foundational concepts, including neighborhoods of compact sets, invariant sets, and the properties of dynamical…

Dynamical Systems · Mathematics 2024-12-11 Reza Hadadi

Critical transitions occur in a variety of dynamical systems. Here, we employ quantifiers of chaos to identify changes in the dynamical structure of complex systems preceding critical transitions. As suitable indicator variables for…

Chaotic Dynamics · Physics 2017-09-27 Nahal Sharafi , Marc Timme , Sarah Hallerberg

We establish convergence to an invariant measure as time tends to infinity, for a large class of (possibly non-Markovian) stochastic volatility models. Our arguments are based on a novel coupling idea for Markov chains which also extends to…

Probability · Mathematics 2021-08-30 Balázs Gerencsér , Miklós Rásonyi
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