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The concept of weak ergodicity breaking is defined and studied in the context of deterministic dynamics. We show that weak ergodicity breaking describes a weakly chaotic dynamical system: a nonlinear map which generates subdiffusion…

Chaotic Dynamics · Physics 2007-05-23 Golan Bel , Eli Barkai

Recently, a concept of deterministic and stochastic turbulence has been introduced based on experiments with a boundary layer. In these experiments, the flow was driven with controlled random perturbation; in addition, natural ambient noise…

Chaotic Dynamics · Physics 2025-11-19 Arkady Pikovsky

Coupled dynamical systems with one slow element and many fast elements are analyzed. By averaging over the dynamics of the fast variables, the adiabatic kinetic branch is introduced for the dynamics of the slow variable in the adiabatic…

Chaotic Dynamics · Physics 2015-06-15 Hidetoshi Aoki , Kunihiko Kaneko

A new type of deterministic chaos for a system described by iterative two-dimensional maps is reported. The series being generated by the original map has an average upward trend while the first difference, which is the series of changes…

Chaotic Dynamics · Physics 2010-07-22 Taisei Kaizoji

Ever since the link between nonlinear science and cryptography became apparent, the problem of applying chaotic dynamics to the construction of cryptographic systems has gained a broad audience and has been the subject of thousands of…

Cryptography and Security · Computer Science 2024-05-07 Samuel Everett

An approach for the description of stochastic systems is derived. Some of the variables in the system are studied forward in time, others backward in time. The approach is based on a perturbation expansion in the strength of the coupling…

Statistical Mechanics · Physics 2021-08-04 Piero Olla

We introduce the notion of a quasistatic dynamical system, which generalizes that of an ordinary dynamical system. Quasistatic dynamical systems are inspired by the namesake processes in thermodynamics, which are idealized processes where…

Dynamical Systems · Mathematics 2016-05-18 Neil Dobbs , Mikko Stenlund

We investigate chaos in mixed-phase-space Hamiltonian systems using time series of the finite- time Lyapunov exponents. The methodology we propose uses the number of Lyapunov exponents close to zero to define regimes of ordered…

Chaotic Dynamics · Physics 2015-06-16 R. M. da Silva , C. Manchein , M. W. Beims , E. G. Altmann

We study chaotic synchronization in networks with time-delayed coupling. We introduce the notion of strong and weak chaos, distinguished by the scaling properties of the maximum Lyapunov exponent within the synchronization manifold for…

Recent work in dynamical systems theory has shown that many properties that are associated with irreversible processes in fluids can be understood in terms of the dynamical properties of reversible, Hamiltonian systems. That is,…

chao-dyn · Physics 2015-06-24 J. R. Dorfman

We describe some highlights in the theory of chaos, that started with Poincare (1899). Generic systems have both ordered and chaotic domains. Chaos appears mainly near un- stable periodic orbits. Large chaotic domains are due to resonance…

Chaotic Dynamics · Physics 2018-07-26 George Contopoulos

We consider a system of weak* closed sets of finite-dimensional distributions. We show that a corresponding system of random variables can be defined on a probability space with a probability measure determined up to some set of measures,…

Probability · Mathematics 2016-11-02 Victor Ivanenko , Illia Pasichnichenko

There has been a long-standing and at times fractious debate whether complex and large systems can be stable. In ecology, the so-called `diversity-stability debate' arose because mathematical analyses of ecosystem stability were either…

Dynamical Systems · Mathematics 2015-09-02 Paul Kirk , Delphine M. Y. Rolando , Adam L. MacLean , Michael P. H. Stumpf

Transport in Hamiltonian systems with weak chaotic perturbations has been much studied in the past. In this paper, we introduce a new class of problems: transport in Hamiltonian systems with slowly changing phase space structure that are…

Chaotic Dynamics · Physics 2019-10-02 Freddy Bouchet , Eric Woillez

The applicability of machine learning for predicting chaotic dynamics relies heavily upon the data used in the training stage. Chaotic time series obtained by numerically solving ordinary differential equations embed a complicated noise of…

Data Analysis, Statistics and Probability · Physics 2021-10-13 Igor A Khovanov

Systems whose time evolutions are entirely deterministic can nevertheless be studied probabilistically, i.e. in terms of the evolution of probability distributions rather than individual trajectories. This approach is central to the…

Dynamical Systems · Mathematics 2019-09-06 S. Richard Taylor

Symbolic dynamics has proven to be an invaluable tool in analyzing the mechanisms that lead to unpredictability and random behavior in nonlinear dynamical systems. Surprisingly, a discrete partition of continuous state space can produce a…

Machine Learning · Computer Science 2007-07-13 Christopher C. Strelioff , James P. Crutchfield

A phenomenon of weak transient chaos is discussed that is caused by sub-exponential divergence of trajectories in the basin of a non-chaotic attractor. Such a regime is not easy to detect, because conventional characteristics, such as the…

Chaotic Dynamics · Physics 2016-05-19 Valentin S. Afraimovich , Alexander B. Neiman

Chaotic dynamics can be quite heterogeneous in the sense that in some regions the dynamics are unstable in more directions than in other regions. When trajectories wander between these regions, the dynamics is complicated. We say a chaotic…

Dynamical Systems · Mathematics 2022-10-10 Yoshitaka Saiki , Hiroki Takahasi , James A. Yorke

Many complex phenomena, from weather systems to heartbeat rhythm patterns, are effectively modeled as low-dimensional dynamical systems. Such systems may behave chaotically under certain conditions, and so the ability to detect chaos based…

Machine Learning · Computer Science 2021-06-17 Hagai Rappeport , Irit Levin Reisman , Naftali Tishby , Nathalie Q. Balaban
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