Introduction. One of the Basic Questions in Dynamical 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. -
Fine Structure of Hyperbolic Diffeomorphisms, by A. A. Pinto, D
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 48, Number 1, January 2011, Pages 131–136 S 0273-0979(2010)01284-2 Article electronically published on May 24, 2010 Fine structure of hyperbolic diffeomorphisms,byA.A.Pinto,D.Rand,andF.Fer- reira, Springer Monographs in Mathematics, Springer-Verlag, Berlin, Heidelberg, 2009, xvi+354 pp., ISBN 978-3-540-87524-6, hardcover, US$129.00 The main theme of the book Fine Structures of Hyperbolic Diffeomorphisms,by Pinto, Rand and Ferreira, is the rigidity and flexibility of two-dimensional diffeo- morphisms on hyperbolic basic sets and properties of invariant measures that are related to the geometry of these invariant sets. In his remarkable article [23], Smale sets the foundations of the modern theory of dynamical systems. He defines the fundamental notion of hyperbolicity and relates it to structural stability. Let f be a smooth (at least C1) diffeomorphism of a compact manifold M. A hyperbolic set for f is a closed f-invariant subset Λ ⊂ M such that the tangent bundle of the manifold over Λ splits as a direct sum of two subbundles that are invariant under the derivative, and the derivative of the iterates of the map expands exponentially one of the bundles (the unstable bundle) and contracts exponentially the stable subbundle. These bundles are in general only continuous, but they are integrable. Through each point x ∈ Λ, there exists a one-to-one immersed submanifold W s(x), the stable manifold of x.This submanifold is tangent to the stable bundle at each point of intersection with Λ and is characterized by the fact that the orbit of each point y ∈ W s(x)isasymptotic to the orbit of x, and, in fact, the distance between f n(y)tof n(x)converges to zero exponentially fast. -
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. -
Nonlocally Maximal Hyperbolic Sets for Flows
Brigham Young University BYU ScholarsArchive Theses and Dissertations 2015-06-01 Nonlocally Maximal Hyperbolic Sets for Flows Taylor Michael Petty Brigham Young University - Provo Follow this and additional works at: https://scholarsarchive.byu.edu/etd Part of the Mathematics Commons BYU ScholarsArchive Citation Petty, Taylor Michael, "Nonlocally Maximal Hyperbolic Sets for Flows" (2015). Theses and Dissertations. 5558. https://scholarsarchive.byu.edu/etd/5558 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. Nonlocally Maximal Hyperbolic Sets for Flows Taylor Michael Petty A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Todd Fisher, Chair Lennard F. Bakker Christopher P. Grant Department of Mathematics Brigham Young University June 2015 Copyright c 2015 Taylor Michael Petty All Rights Reserved abstract Nonlocally Maximal Hyperbolic Sets for Flows Taylor Michael Petty Department of Mathematics, BYU Master of Science In 2004, Fisher constructed a map on a 2-disc that admitted a hyperbolic set not contained in any locally maximal hyperbolic set. Furthermore, it was shown that this was an open property, and that it was embeddable into any smooth manifold of dimension greater than one. In the present work we show that analogous results hold for flows. Specifically, on any smooth manifold with dimension greater than or equal to three there exists an open set of flows such that each flow in the open set contains a hyperbolic set that is not contained in a locally maximal one. -
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. -
5 Bifurcation and Centre Manifold
5 Bifurcation and centre manifold For the general ODEx ˙ = f(x) near its stationary point x∗, we learned early that if none of the eigenvalues of the Jacobian Df(x∗) has a real part zero, then the behaviour ofx ˙ = f(x) is determined by its linearised systemy ˙ = Df(x∗)y with y x x∗. What happens if the ≈ − Jacobian matrix Df(x∗) has eigenvalues with zero real part? If some eigenvalues have zero real part, nonlinear terms are expected to play a role, and the behaviour could change accordingly. The study of these qualitative changes in the behaviours (mainly stability/instability of stationary points and periodic orbits), subject to changes in certain parameters, is call bifurcation theory. Since the stability/instability of fixed points is indicated precisely by the real part of the eigenvalues, we are going to see how these eigenvalues pass the imaginary axis, as the parameter changes. Example 5.1. Consider the following two systems x˙ = µx + ωy, (a)x ˙ = µx, (b) y˙ = ωx + µy. ( − It is easy to see that, the eigenvalue λ(µ)= µ in (a), and λ(µ)= µ iω in (b). The stability ± is changed when µ crosses zero. More general scenario is shown in Figure 5.1. λ(µ) Imλ λ(µ) iω µ Reλ iω − λ∗(µ) Figure 5.1: Left figure: real eigenvalue passing through zero as a function of µ; Right figure: complex eigenvalues passing through the imaginary axis (think of the eigenvalues as parametrised curves in the complex plane). 5.1 Centre manifold theorem We learned Stable Manifold Theorem earlier, which states that the structure of the system near a hyperbolic fixed point does not change when nonlinear terms are added. -
Weak Mixing for Interval Exchange Transformations and Translation Flows
WEAK MIXING FOR INTERVAL EXCHANGE TRANSFORMATIONS AND TRANSLATION FLOWS ARTUR AVILA AND GIOVANNI FORNI Abstract. We show that a typical interval exchange transformation is either weak mixing or an irrational rotation. We also conclude that a typical translation flow on a surface of genus g ≥ 2 (with prescribed singularity types) is weak mixing. 1. Introduction Let d ≥ 2andletπ be an irreducible permutation of {1, ..., d},thatis,π{1, ..., k} = {1, ..., k}, d 1 ≤ k<d.Givenλ ∈ R+, we define an interval exchange transformation (i.e.t.) f = f(λ, π)inthe usual way: we take the interval d (1.1) I = I(λ, π)= 0, λi i=1 break it into subintervals (1.2) Ii = Ii(λ, π)= λj, λj , 1 ≤ i ≤ d, j<i j≤i and rearrange the Ii according to π.Inotherwords,f : I → I is given by (1.3) x → x + λj − λj ,x∈ Ii. π(j)<π(i) j<i We are interested in the ergodic properties of i.e.t.’s. Obviously, they preserve Lebesgue measure. The fundamental work of Masur [M] and Veech [V1] established that almost every i.e.t. is uniquely d ergodic (this means that for every irreducible π and for almost every λ ∈ R+, f(λ, π) is uniquely ergodic). The question of weak mixing is much more delicate. Obviously, if π is a rotation of {1, ..., d} then f(λ, π) is conjugate to a rotation of the circle, and so f(λ, π) is not weak mixing for every d λ ∈ R+. After the work of Katok and Stepin [KS] (who treated the case of three intervals), Veech [V3] established almost sure weak mixing for infinitely many irreducible permutations π,andasked whether this should hold for all irreducible permutations π which are not rotations.