Geometrical Theory of Dynamical Systems Is to Classify the Possible Behaviours and to find Ways to Determine the Most Important Qualitative Features of the System
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Approximating Stable and Unstable Manifolds in Experiments
PHYSICAL REVIEW E 67, 037201 ͑2003͒ Approximating stable and unstable manifolds in experiments Ioana Triandaf,1 Erik M. Bollt,2 and Ira B. Schwartz1 1Code 6792, Plasma Physics Division, Naval Research Laboratory, Washington, DC 20375 2Department of Mathematics and Computer Science, Clarkson University, P.O. Box 5815, Potsdam, New York 13699 ͑Received 5 August 2002; revised manuscript received 23 December 2002; published 12 March 2003͒ We introduce a procedure to reveal invariant stable and unstable manifolds, given only experimental data. We assume a model is not available and show how coordinate delay embedding coupled with invariant phase space regions can be used to construct stable and unstable manifolds of an embedded saddle. We show that the method is able to capture the fine structure of the manifold, is independent of dimension, and is efficient relative to previous techniques. DOI: 10.1103/PhysRevE.67.037201 PACS number͑s͒: 05.45.Ac, 42.60.Mi Many nonlinear phenomena can be explained by under- We consider a basin saddle of Eq. ͑1͒ which lies on the standing the behavior of the unstable dynamical objects basin boundary between a chaotic attractor and a period-four present in the dynamics. Dynamical mechanisms underlying periodic attractor. The chosen parameters are in a region in chaos may be described by examining the stable and unstable which the chaotic attractor disappears and only a periodic invariant manifolds corresponding to unstable objects, such attractor persists along with chaotic transients due to inter- as saddles ͓1͔. Applications of the manifold topology have secting stable and unstable manifolds of the basin saddle. -
Robust Transitivity of Singular Hyperbolic Attractors
Robust transitivity of singular hyperbolic attractors Sylvain Crovisier∗ Dawei Yangy January 22, 2020 Abstract Singular hyperbolicity is a weakened form of hyperbolicity that has been introduced for vector fields in order to allow non-isolated singularities inside the non-wandering set. A typical example of a singular hyperbolic set is the Lorenz attractor. However, in contrast to uniform hyperbolicity, singular hyperbolicity does not immediately imply robust topological properties, such as the transitivity. In this paper, we prove that open and densely inside the space of C1 vector fields of a compact manifold, any singular hyperbolic attractors is robustly transitive. 1 Introduction Lorenz [L] in 1963 studied some polynomial ordinary differential equations in R3. He found some strange attractor with the help of computers. By trying to understand the chaotic dynamics in Lorenz' systems, [ABS, G, GW] constructed some geometric abstract models which are called geometrical Lorenz attractors: these are robustly transitive non- hyperbolic chaotic attractors with singularities in three-dimensional manifolds. In order to study attractors containing singularities for general vector fields, Morales- Pacifico-Pujals [MPP] first gave the notion of singular hyperbolicity in dimension 3. This notion can be adapted to the higher dimensional case, see [BdL, CdLYZ, MM, ZGW]. In the absence of singularity, the singular hyperbolicity coincides with the usual notion of uniform hyperbolicity; in that case it has many nice dynamical consequences: spectral decomposition, stability, probabilistic description,... But there also exist open classes of vector fields exhibiting singular hyperbolic attractors with singularity: the geometrical Lorenz attractors are such examples. In order to have a description of the dynamics of arXiv:2001.07293v1 [math.DS] 21 Jan 2020 general flows, we thus need to develop a systematic study of the singular hyperbolicity in the presence of singularity. -
Hartman-Grobman and Stable Manifold Theorem
THE HARTMAN-GROBMAN AND STABLE MANIFOLD THEOREM SLOBODAN N. SIMIC´ This is a summary of some basic results in dynamical systems we discussed in class. Recall that there are two kinds of dynamical systems: discrete and continuous. A discrete dynamical system is map f : M → M of some space M.A continuous dynamical system (or flow) is a collection of maps φt : M → M, with t ∈ R, satisfying φ0(x) = x and φs+t(x) = φs(φt(x)), for all x ∈ M and s, t ∈ R. We call M the phase space. It is usually either a subset of a Euclidean space, a metric space or a smooth manifold (think of surfaces in 3-space). Similarly, f or φt are usually nice maps, e.g., continuous or differentiable. We will focus on smooth (i.e., differentiable any number of times) discrete dynamical systems. Let f : M → M be one such system. Definition 1. The positive or forward orbit of p ∈ M is the set 2 O+(p) = {p, f(p), f (p),...}. If f is invertible, we define the (full) orbit of p by k O(p) = {f (p): k ∈ Z}. We can interpret a point p ∈ M as the state of some physical system at time t = 0 and f k(p) as its state at time t = k. The phase space M is the set of all possible states of the system. The goal of the theory of dynamical systems is to understand the long-term behavior of “most” orbits. That is, what happens to f k(p), as k → ∞, for most initial conditions p ∈ M? The first step towards this goal is to understand orbits which have the simplest possible behavior, namely fixed and periodic ones. -
An Image Cryptography Using Henon Map and Arnold Cat Map
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 04 | Apr-2018 www.irjet.net p-ISSN: 2395-0072 An Image Cryptography using Henon Map and Arnold Cat Map. Pranjali Sankhe1, Shruti Pimple2, Surabhi Singh3, Anita Lahane4 1,2,3 UG Student VIII SEM, B.E., Computer Engg., RGIT, Mumbai, India 4Assistant Professor, Department of Computer Engg., RGIT, Mumbai, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - In this digital world i.e. the transmission of non- 2. METHODOLOGY physical data that has been encoded digitally for the purpose of storage Security is a continuous process via which data can 2.1 HENON MAP be secured from several active and passive attacks. Encryption technique protects the confidentiality of a message or 1. The Henon map is a discrete time dynamic system information which is in the form of multimedia (text, image, introduces by michel henon. and video).In this paper, a new symmetric image encryption 2. The map depends on two parameters, a and b, which algorithm is proposed based on Henon’s chaotic system with for the classical Henon map have values of a = 1.4 and byte sequences applied with a novel approach of pixel shuffling b = 0.3. For the classical values the Henon map is of an image which results in an effective and efficient chaotic. For other values of a and b the map may be encryption of images. The Arnold Cat Map is a discrete system chaotic, intermittent, or converge to a periodic orbit. that stretches and folds its trajectories in phase space. Cryptography is the process of encryption and decryption of 3. -
Chapter 3 Hyperbolicity
Chapter 3 Hyperbolicity 3.1 The stable manifold theorem In this section we shall mix two typical ideas of hyperbolic dynamical systems: the use of a linear approxi- mation to understand the behavior of nonlinear systems, and the examination of the behavior of the system along a reference orbit. The latter idea is embodied in the notion of stable set. Denition 3.1.1: Let (X, f) be a dynamical system on a metric space X. The stable set of a point x ∈ X is s ∈ k k Wf (x)= y X lim d f (y),f (x) =0 . k→∞ ∈ s In other words, y Wf (x) if and only if the orbit of y is asymptotic to the orbit of x. If no confusion will arise, we drop the index f and write just W s(x) for the stable set of x. Clearly, two stable sets either coincide or are disjoint; therefore X is the disjoint union of its stable sets. Furthermore, f W s(x) W s f(x) for any x ∈ X. The twin notion of unstable set for homeomorphisms is dened in a similar way: Denition 3.1.2: Let f: X → X be a homeomorphism of a metric space X. Then the unstable set of a ∈ point x X is u ∈ k k Wf (x)= y X lim d f (y),f (x) =0 . k→∞ u s In other words, Wf (x)=Wf1(x). Again, unstable sets of homeomorphisms give a partition of the space. On the other hand, stable sets and unstable sets (even of the same point) might intersect, giving rise to interesting dynamical phenomena. -
Hyperbolic Dynamical Systems, Chaos, and Smale's
Hyperbolic dynamical systems, chaos, and Smale's horseshoe: a guided tour∗ Yuxi Liu Abstract This document gives an illustrated overview of several areas in dynamical systems, at the level of beginning graduate students in mathematics. We start with Poincar´e's discovery of chaos in the three-body problem, and define the Poincar´esection method for studying dynamical systems. Then we discuss the long-term behavior of iterating a n diffeomorphism in R around a fixed point, and obtain the concept of hyperbolicity. As an example, we prove that Arnold's cat map is hyperbolic. Around hyperbolic fixed points, we discover chaotic homoclinic tangles, from which we extract a source of the chaos: Smale's horseshoe. Then we prove that the behavior of the Smale horseshoe is the same as the binary shift, reducing the problem to symbolic dynamics. We conclude with applications to physics. 1 The three-body problem 1.1 A brief history The first thing Newton did, after proposing his law of gravity, is to calculate the orbits of two mass points, M1;M2 moving under the gravity of each other. It is a basic exercise in mechanics to show that, relative to one of the bodies M1, the orbit of M2 is a conic section (line, ellipse, parabola, or hyperbola). The second thing he did was to calculate the orbit of three mass points, in order to study the sun-earth-moon system. Here immediately he encountered difficulty. And indeed, the three body problem is extremely difficult, and the n-body problem is even more so. -
Transformations)
TRANSFORMACJE (TRANSFORMATIONS) Transformacje (Transformations) is an interdisciplinary refereed, reviewed journal, published since 1992. The journal is devoted to i.a.: civilizational and cultural transformations, information (knowledge) societies, global problematique, sustainable development, political philosophy and values, future studies. The journal's quasi-paradigm is TRANSFORMATION - as a present stage and form of development of technology, society, culture, civilization, values, mindsets etc. Impacts and potentialities of change and transition need new methodological tools, new visions and innovation for theoretical and practical capacity-building. The journal aims to promote inter-, multi- and transdisci- plinary approach, future orientation and strategic and global thinking. Transformacje (Transformations) are internationally available – since 2012 we have a licence agrement with the global database: EBSCO Publishing (Ipswich, MA, USA) We are listed by INDEX COPERNICUS since 2013 I TRANSFORMACJE(TRANSFORMATIONS) 3-4 (78-79) 2013 ISSN 1230-0292 Reviewed journal Published twice a year (double issues) in Polish and English (separate papers) Editorial Staff: Prof. Lech W. ZACHER, Center of Impact Assessment Studies and Forecasting, Kozminski University, Warsaw, Poland ([email protected]) – Editor-in-Chief Prof. Dora MARINOVA, Sustainability Policy Institute, Curtin University, Perth, Australia ([email protected]) – Deputy Editor-in-Chief Prof. Tadeusz MICZKA, Institute of Cultural and Interdisciplinary Studies, University of Silesia, Katowice, Poland ([email protected]) – Deputy Editor-in-Chief Dr Małgorzata SKÓRZEWSKA-AMBERG, School of Law, Kozminski University, Warsaw, Poland ([email protected]) – Coordinator Dr Alina BETLEJ, Institute of Sociology, John Paul II Catholic University of Lublin, Poland Dr Mirosław GEISE, Institute of Political Sciences, Kazimierz Wielki University, Bydgoszcz, Poland (also statistical editor) Prof. -
Invariant Manifolds and Their Interactions
Understanding the Geometry of Dynamics: Invariant Manifolds and their Interactions Hinke M. Osinga Department of Mathematics, University of Auckland, Auckland, New Zealand Abstract Dynamical systems theory studies the behaviour of time-dependent processes. For example, simulation of a weather model, starting from weather conditions known today, gives information about the weather tomorrow or a few days in advance. Dynamical sys- tems theory helps to explain the uncertainties in those predictions, or why it is pretty much impossible to forecast the weather more than a week ahead. In fact, dynamical sys- tems theory is a geometric subject: it seeks to identify critical boundaries and appropriate parameter ranges for which certain behaviour can be observed. The beauty of the theory lies in the fact that one can determine and prove many characteristics of such bound- aries called invariant manifolds. These are objects that typically do not have explicit mathematical expressions and must be found with advanced numerical techniques. This paper reviews recent developments and illustrates how numerical methods for dynamical systems can stimulate novel theoretical advances in the field. 1 Introduction Mathematical models in the form of systems of ordinary differential equations arise in numer- ous areas of science and engineering|including laser physics, chemical reaction dynamics, cell modelling and control engineering, to name but a few; see, for example, [12, 14, 35] as en- try points into the extensive literature. Such models are used to help understand how different types of behaviour arise under a variety of external or intrinsic influences, and also when system parameters are changed; examples include finding the bursting threshold for neurons, determin- ing the structural stability limit of a building in an earthquake, or characterising the onset of synchronisation for a pair of coupled lasers. -
Dynamical Systems Theory
Dynamical Systems Theory Bjorn¨ Birnir Center for Complex and Nonlinear Dynamics and Department of Mathematics University of California Santa Barbara1 1 c 2008, Bjorn¨ Birnir. All rights reserved. 2 Contents 1 Introduction 9 1.1 The 3 Body Problem . .9 1.2 Nonlinear Dynamical Systems Theory . 11 1.3 The Nonlinear Pendulum . 11 1.4 The Homoclinic Tangle . 18 2 Existence, Uniqueness and Invariance 25 2.1 The Picard Existence Theorem . 25 2.2 Global Solutions . 35 2.3 Lyapunov Stability . 39 2.4 Absorbing Sets, Omega-Limit Sets and Attractors . 42 3 The Geometry of Flows 51 3.1 Vector Fields and Flows . 51 3.2 The Tangent Space . 58 3.3 Flow Equivalance . 60 4 Invariant Manifolds 65 5 Chaotic Dynamics 75 5.1 Maps and Diffeomorphisms . 75 5.2 Classification of Flows and Maps . 81 5.3 Horseshoe Maps and Symbolic Dynamics . 84 5.4 The Smale-Birkhoff Homoclinic Theorem . 95 5.5 The Melnikov Method . 96 5.6 Transient Dynamics . 99 6 Center Manifolds 103 3 4 CONTENTS 7 Bifurcation Theory 109 7.1 Codimension One Bifurcations . 110 7.1.1 The Saddle-Node Bifurcation . 111 7.1.2 A Transcritical Bifurcation . 113 7.1.3 A Pitchfork Bifurcation . 115 7.2 The Poincare´ Map . 118 7.3 The Period Doubling Bifurcation . 119 7.4 The Hopf Bifurcation . 121 8 The Period Doubling Cascade 123 8.1 The Quadradic Map . 123 8.2 Scaling Behaviour . 130 8.2.1 The Singularly Supported Strange Attractor . 138 A The Homoclinic Orbits of the Pendulum 141 List of Figures 1.1 The rotation of the Sun and Jupiter in a plane around a common center of mass and the motion of a comet perpendicular to the plane. -
Computation of Stable and Unstable Manifolds of Hyperbolic Trajectories in Two-Dimensional, Aperiodically Time-Dependent Vector fields Ana M
Physica D 182 (2003) 188–222 Computation of stable and unstable manifolds of hyperbolic trajectories in two-dimensional, aperiodically time-dependent vector fields Ana M. Mancho a, Des Small a, Stephen Wiggins a,∗, Kayo Ide b a School of Mathematics, University of Bristol, University Walk, Bristol, BS8 1TW, UK b Department of Atmospheric Sciences, and Institute of Geophysics and Planetary Physics, UCLA, Los Angeles, CA 90095-1565, USA Received 14 October 2002; received in revised form 29 January 2003; accepted 31 March 2003 Communicated by E. Kostelich Abstract In this paper, we develop two accurate and fast algorithms for the computation of the stable and unstable manifolds of hyperbolic trajectories of two-dimensional, aperiodically time-dependent vector fields. First we develop a benchmark method in which all the trajectories composing the manifold are integrated from the neighborhood of the hyperbolic trajectory. This choice, although very accurate, is not fast and has limited usage. A faster and more powerful algorithm requires the insertion of new points in the manifold as it evolves in time. Its numerical implementation requires a criterion for determining when to insert those points in the manifold, and an interpolation method for determining where to insert them. We compare four different point insertion criteria and four different interpolation methods. We discuss the computational requirements of all of these methods. We find two of the four point insertion criteria to be accurate and robust. One is a variant of a criterion originally proposed by Hobson. The other is a slight variant of a method due to Dritschel and Ambaum arising from their studies of contour dynamics. -
Bifurcations, Center Manifolds, and Periodic Solutions
Bifurcations, Center Manifolds, and Periodic Solutions David E. Gilsinn National Institute of Standards and Technology 100 Bureau Drive, Stop 8910 Gaithersburg, MD 20899-8910 [email protected] Summary. Nonlinear time delay differential equations are well known to have arisen in models in physiology, biology and population dynamics. These delay differ- ential equations usually have parameters in their formulation. How the nature of the solutions change as the parameters vary is crucial to understanding the underlying physical processes. When the delay differential equation is reduced, at an equilibrium point, to leading linear terms and the remaining nonlinear terms, the eigenvalues of the leading coefficients indicate the nature of the solutions in the neighborhood of the equilibrium point. If there are any eigenvalues with zero real parts, periodic so- lutions can arise. One way in which this can happen is through a bifurcation process called a Hopf bifurcation in which a parameter passes through a critical value and the solutions change from equilibrium solutions to periodic solutions. This chap- ter describes a method of decomposing the delay differential equation into a form that isolates the study of the periodic solutions arising from a Hopf bifurcation to the study of a reduced size differential equation on a surface, called a center man- ifold. The method will be illustrated by a Hopf bifurcation that arises in machine tool dynamics, which leads to a machining instability called regenerative chatter. Keywords: Center manifolds, delay differential equations, exponential polynomi- als, Hopf bifurcation, limit cycle, machine tool chatter, normal form, semigroup of operators, subcritical bifurcation. 1 Background With the advent of new technologies for measurement instrumentation, it has become possible to detect time delays in feedback signals that affect a physical system’s performance. -
Arxiv:1809.00924V2 [Math.DS] 14 Jul 2019 at the Origin to the Eigenspace Corresponding to the the Pair of Imaginary Eigenvalues
GLOBAL PERSISTENCE OF LYAPUNOV-SUBCENTER-MANIFOLDS AS SPECTRAL SUBMANIFOLDS UNDER DISSIPATIVE PERTURBATIONS RAFAEL DE LA LLAVE AND FLORIAN KOGELBAUER Abstract. For a nondegenerate analytic system with a conserved quantity, a classic result by Lyapunov guarantees the existence of an analytic manifold of periodic orbits tangent to any two-dimensional, elliptic eigenspace of a fixed point satisfying nonresonance conditions. These two dimensional manifolds are referred to as Lyapunov Subcenter Manifolds (LSM). Numerical and experimental observations in the nonlinear vibrations literature suggest that LSM's often persist under autonomous, dissipative perturbations. These perturbed manifolds are useful since they provide information of the asymptotics of the convergence to equilibrium. In this paper, we formulate and prove precise mathematical results on the persistence of LSMs under dissipation. We show that, for Hamiltonian systems under mild non- degeneracy conditions on the perturbation, for small enough dissipation, there are analytic invariant manifolds of the perturbed system that approximate (in the analytic sense) the LSM in a fixed neighborhood. We provide examples that show that some non-degeneracy conditions on the perturbations are needed for the results to hold true. We also study the dependence of the manifolds on the dissipation parameter. If " is the dissipation parameter, we show that the manifolds are real analytic in (−"0;"0) n f0g 1 and C in (−"0;"0). We construct explicit asymptotic expansions in powers of " (which presumably