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Progress in the analysis of experimental chaos through periodic orbits

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TLDR
In this article, the analysis of chaotic systems can be considerably improved with the knowledge of their periodic-orbit structure, which has led to an extension of the conventional Bloch-Kirchhoff equations of motion, to the construction of approximate generating partitions, and to an efficient control of the chaotic system around various unstable periodic orbits.
Abstract
The understanding of chaotic systems can be considerably improved with the knowledge of their periodic-orbit structure. The identification of the low-order unstable periodic orbits embedded in a strange attractor induces a hierarchical organization of the dynamics which is invariant under smooth coordinate changes. The applicability of this technique is by no means limited to analytical or numerical calculations, but has been recently extended to experimental time series. As a specific example, the authors review some of the major results obtained on a nuclear-magnetic-resonance laser which have led to an extension of the conventional (Bloch-Kirchhoff) equations of motion, to the construction of approximate generating partitions, and to an efficient control of the chaotic system around various unstable periodic orbits. The determination of the symbolic dynamics, with the precision achieved by recording all unstable cycles up to order 9, improves the topological and metric characterization of a heteroclinic crisis. The periodic-orbit approach permits detailed study of chaotic motion, thereby leading to an improved classification scheme which subsumes the older ones, based on estimates of scalar quantities such as fractal dimensions and metric entropies.

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Citations
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Journal ArticleDOI

Interdisciplinary application of nonlinear time series methods

TL;DR: In this paper, the authors report on the application of field measurements of time series methods developed on the basis of the theory of deterministic chaos and discuss the implications for deterministic modeling.
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Data based identification and prediction of nonlinear and complex dynamical systems

TL;DR: The recent advances in this forefront and rapidly evolving field of reconstructing nonlinear and complex dynamical systems from measured data or time series are reviewed, aiming to cover topics such as compressive sensing, noised-induced dynamical mapping, perturbations, reverse engineering, synchronization, inner composition alignment, global silencing and Granger Causality.
Journal ArticleDOI

Data Based Identification and Prediction of Nonlinear and Complex Dynamical Systems

TL;DR: The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics.
Journal ArticleDOI

Colloquium : Statistical mechanics and thermodynamics at strong coupling: Quantum and classical

TL;DR: In this article, the authors provide an account of how the thermal equilibrium of a system is influenced by the presence of a thermal bath and give a view of both classical and quantum aspects providing an understanding on the particularities of the quantum case.
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Resurrection of crushed magnetization and chaotic dynamics in solution NMR spectroscopy.

TL;DR: It is shown experimentally and theoretically that two readily observed effects in solution nuclear magnetic resonance (NMR)-radiation damping and the dipolar field-combine to generate bizarre spin dynamics (including chaotic evolution) even with extraordinarily simple sequences.
References
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Journal ArticleDOI

Deterministic nonperiodic flow

TL;DR: In this paper, it was shown that nonperiodic solutions are ordinarily unstable with respect to small modifications, so that slightly differing initial states can evolve into considerably different states, and systems with bounded solutions are shown to possess bounded numerical solutions.
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Ergodic theory of chaos and strange attractors

TL;DR: A review of the main mathematical ideas and their concrete implementation in analyzing experiments can be found in this paper, where the main subjects are the theory of dimensions (number of excited degrees of freedom), entropy (production of information), and characteristic exponents (describing sensitivity to initial conditions).
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Characterization of Strange Attractors

TL;DR: In this article, a measure of strange attractors is introduced which offers a practical algorithm to determine their character from the time series of a single observable, and the relation of this measure to fractal dimension and information-theoretic entropy is discussed.
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Geometry from a Time Series

TL;DR: In this paper, the existence of low-dimensional chaotic dynamical systems describing turbulent fluid flow was determined experimentally by reconstructing phase-space pictures from the observation of a single coordinate of any dissipative dynamical system and determining the dimensionality of the system's attractor.
Journal ArticleDOI

A universal instability of many-dimensional oscillator systems

Boris Chirikov
- 01 May 1979 - 
TL;DR: In this article, the authors demonstrate the mechanism for a universal instability, the Arnold diffusion, which occurs in the oscillating systems having more than two degrees of freedom, which results in an irregular, or stochastic, motion of the system as if the latter were influenced by a random perturbation even though, in fact, the motion is governed by purely dynamical equations.