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Anosov Diffeomorphism with a Horseshoe That Attracts Almost Any Point
DISCRETE AND CONTINUOUS doi:10.3934/dcds.2020017 DYNAMICAL SYSTEMS Volume 40, Number 1, January 2020 pp. 441–465 ANOSOV DIFFEOMORPHISM WITH A HORSESHOE THAT ATTRACTS ALMOST ANY POINT Christian Bonatti Institut de Math´ematiquesde Bourgogne, Universit´ede Bourgogne Dijon 21004, France Stanislav Minkov Brook Institute of Electronic Control Machines 119334, Moscow, Vavilova str., 24, Russia Alexey Okunev Loughborough University LE11 3TU, Loughborough, UK Ivan Shilin National Research University Higher School of Economics Faculty of Mathematics, 119048, Moscow, Usacheva str., 6, Russia (Communicated by Sylvain Crovisier) Abstract. We present an example of a C1 Anosov diffeomorphism of a two- torus with a physical measure such that its basin has full Lebesgue measure and its support is a horseshoe of zero measure. 1. Introduction. Consider a diffeomorphism F that preserves a probability mea- sure ν. The basin of ν is the set of all points x such that the sequence of measures n 1 δ := (δ + ··· + δ n−1 ) x n x F (x) converges to ν in the weak-∗ topology. A measure is called physical if its basin has positive Lebesgue measure. It is well known (see [3], [11], [12], or [1, x1:3]) that any transitive C2 Anosov diffeomorphism (note that all known Anosov diffeomorphisms are transitive) has a unique physical measure and • the basin of this measure has full Lebesgue measure, • the support of this measure coincides with the whole phase space. In C1 dynamics there are many phenomena that are impossible in C2. Bowen [2] has constructed an example of a C1 diffeomorphism of the plane with a thick horseshoe (i.e., a horseshoe with positive Lebesgue measure) and Robinson and Young [10] have embedded a thick horseshoe in a C1 Anosov diffeomorphism of T2 2010 Mathematics Subject Classification. -
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. -
Fractal Growth on the Surface of a Planet and in Orbit Around It
Wilfrid Laurier University Scholars Commons @ Laurier Physics and Computer Science Faculty Publications Physics and Computer Science 10-2014 Fractal Growth on the Surface of a Planet and in Orbit around It Ioannis Haranas Wilfrid Laurier University, [email protected] Ioannis Gkigkitzis East Carolina University, [email protected] Athanasios Alexiou Ionian University Follow this and additional works at: https://scholars.wlu.ca/phys_faculty Part of the Mathematics Commons, and the Physics Commons Recommended Citation Haranas, I., Gkigkitzis, I., Alexiou, A. Fractal Growth on the Surface of a Planet and in Orbit around it. Microgravity Sci. Technol. (2014) 26:313–325. DOI: 10.1007/s12217-014-9397-6 This Article is brought to you for free and open access by the Physics and Computer Science at Scholars Commons @ Laurier. It has been accepted for inclusion in Physics and Computer Science Faculty Publications by an authorized administrator of Scholars Commons @ Laurier. For more information, please contact [email protected]. 1 Fractal Growth on the Surface of a Planet and in Orbit around it 1Ioannis Haranas, 2Ioannis Gkigkitzis, 3Athanasios Alexiou 1Dept. of Physics and Astronomy, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3, Canada 2Departments of Mathematics and Biomedical Physics, East Carolina University, 124 Austin Building, East Fifth Street, Greenville, NC 27858-4353, USA 3Department of Informatics, Ionian University, Plateia Tsirigoti 7, Corfu, 49100, Greece Abstract: Fractals are defined as geometric shapes that exhibit symmetry of scale. This simply implies that fractal is a shape that it would still look the same even if somebody could zoom in on one of its parts an infinite number of times. -
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. -
Invariant Measures for Hyperbolic Dynamical Systems
Invariant measures for hyperbolic dynamical systems N. Chernov September 14, 2006 Contents 1 Markov partitions 3 2 Gibbs Measures 17 2.1 Gibbs states . 17 2.2 Gibbs measures . 33 2.3 Properties of Gibbs measures . 47 3 Sinai-Ruelle-Bowen measures 56 4 Gibbs measures for Anosov and Axiom A flows 67 5 Volume compression 86 6 SRB measures for general diffeomorphisms 92 This survey is devoted to smooth dynamical systems, which are in our context diffeomorphisms and smooth flows on compact manifolds. We call a flow or a diffeomorphism hyperbolic if all of its Lyapunov exponents are different from zero (except the one in the flow direction, which has to be 1 zero). This means that the tangent vectors asymptotically expand or con- tract exponentially fast in time. For many reasons, it is convenient to assume more than just asymptotic expansion or contraction, namely that the expan- sion and contraction of tangent vectors happens uniformly in time. Such hyperbolic systems are said to be uniformly hyperbolic. Historically, uniformly hyperbolic flows and diffeomorphisms were stud- ied as early as in mid-sixties: it was done by D. Anosov [2] and S. Smale [77], who introduced his Axiom A. In the seventies, Anosov and Axiom A dif- feomorphisms and flows attracted much attention from different directions: physics, topology, and geometry. This actually started in 1968 when Ya. Sinai constructed Markov partitions [74, 75] that allowed a symbolic representa- tion of the dynamics, which matched the existing lattice models in statistical mechanics. As a result, the theory of Gibbs measures for one-dimensional lat- tices was carried over to Anosov and Axiom A dynamical systems. -
Linear Response, Or Else
Linear response, or else Viviane Baladi Abstract. Consider a smooth one-parameter family t ft of dynamical systems ft, with t < ϵ. !→ | | Assume that for all t (or for many t close to t =0) the map ft admits a unique physical invariant probability measure µt. We say that linear response holds if t µt is differentiable at t =0(possibly !→ in the sense of Whitney), and if its derivative can be expressed as a function of f0, µ0, and ∂tft t=0. | The goal of this note is to present to a general mathematical audience recent results and open problems in the theory of linear response for chaotic dynamical systems, possibly with bifurcations. Mathematics Subject Classification (2010). Primary 37C40; Secondary 37D25, 37C30, 37E05. Keywords. Linear response, transfer operator, Ruelle operator, physical measure, SRB measure, bi- furcations, differentiable dynamical system, unimodal maps, expanding interval maps, hyperbolic dy- namical systems. 1. Introduction A discrete-time dynamical system is a self-map f : M M on a space M. To any point n → 0 x M is then associated its (future) orbit f (x) n Z+ where f (x)=x, and n∈ n 1 { | ∈ } f (x)=f − (f(x)), for n 1, represents the state of the system at time n, given the “ini- ≥ n tial condition” x. (If f is invertible, one can also consider the past orbit f − (x) n Z+ .) { | ∈ } In this text, we shall always assume that M is a compact differentiable manifold (possibly with boundary), with the Borel σ-algebra, endowed with a Riemannian structure and thus normalised Lebesgue measure. -
Arxiv:2003.06811V3 [Math.DS] 31 Mar 2021 Nsmcasclaayi Eg E [ See (E.G
ANOSOV DIFFEOMORPHISMS, ANISOTROPIC BV SPACES AND REGULARITY OF FOLIATIONS WAEL BAHSOUN AND CARLANGELO LIVERANI Abstract. Given any smooth Anosov map we construct a Banach space on which the associated transfer operator is quasi-compact. The peculiarity of such a space is that in the case of expanding maps it reduces exactly to the usual space of functions of bounded variation which has proven particularly successful in studying the statistical properties of piecewise expanding maps. Our approach is based on a new method of studying the absolute continuity of foliations which provides new information that could prove useful in treating hyperbolic systems with singularities. 1. Introduction Starting with the paper [BKL], there has been a growing interest in the pos- sibility to develop a functional analytic setting allowing the direct study of the transfer operator of a hyperbolic dynamical system. The papers [GL, GL1, BT, BT1, B1, B2, B3, B4, T1] have now produced quite satisfactory results for the case of Anosov diffeomorphisms (or, more generally, for uniformly hyperbolic basic sets). Important results, although the theory is not complete yet, have been ob- tained for flows [L, BuL, BuL2, GLP, FT2, DyZ, D17], group extensions and skew products ([F11, AGT]). Moreover, recently a strong relation with techniques used in semiclassical analysis (e.g. see [FR, FRS, FT1, FT2, DyZ]) has been unveiled. Also, one should mention the recent discovery of a deep relation with the theory of renormalization of parabolic systems [GL19]. In addition, such an approach has proven very effective in the study of perturbation of dynamical systems [KL1, KL3] and in the investigation of limit theorems [G10]. -
Equilibrium States and the Ergodic Theory of Anosov Diffeomorphisms
Rufus Bowen Equilibrium States and the Ergodic Theory of Anosov Diffeomorphisms New edition of Lect. Notes in Math. 470, Springer, 1975. April 14, 2013 Springer Preface The Greek and Roman gods, supposedly, resented those mortals endowed with superlative gifts and happiness, and punished them. The life and achievements of Rufus Bowen (1947{1978) remind us of this belief of the ancients. When Rufus died unexpectedly, at age thirty-one, from brain hemorrhage, he was a very happy and successful man. He had great charm, that he did not misuse, and superlative mathematical talent. His mathematical legacy is important, and will not be forgotten, but one wonders what he would have achieved if he had lived longer. Bowen chose to be simple rather than brilliant. This was the hard choice, especially in a messy subject like smooth dynamics in which he worked. Simplicity had also been the style of Steve Smale, from whom Bowen learned dynamical systems theory. Rufus Bowen has left us a masterpiece of mathematical exposition: the slim volume Equilibrium States and the Ergodic Theory of Anosov Diffeomorphisms (Springer Lecture Notes in Mathematics 470 (1975)). Here a number of results which were new at the time are presented in such a clear and lucid style that Bowen's monograph immediately became a classic. More than thirty years later, many new results have been proved in this area, but the volume is as useful as ever because it remains the best introduction to the basics of the ergodic theory of hyperbolic systems. The area discussed by Bowen came into existence through the merging of two apparently unrelated theories. -
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. -
What Are Lyapunov Exponents, and Why Are They Interesting?
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 54, Number 1, January 2017, Pages 79–105 http://dx.doi.org/10.1090/bull/1552 Article electronically published on September 6, 2016 WHAT ARE LYAPUNOV EXPONENTS, AND WHY ARE THEY INTERESTING? AMIE WILKINSON Introduction At the 2014 International Congress of Mathematicians in Seoul, South Korea, Franco-Brazilian mathematician Artur Avila was awarded the Fields Medal for “his profound contributions to dynamical systems theory, which have changed the face of the field, using the powerful idea of renormalization as a unifying principle.”1 Although it is not explicitly mentioned in this citation, there is a second unify- ing concept in Avila’s work that is closely tied with renormalization: Lyapunov (or characteristic) exponents. Lyapunov exponents play a key role in three areas of Avila’s research: smooth ergodic theory, billiards and translation surfaces, and the spectral theory of 1-dimensional Schr¨odinger operators. Here we take the op- portunity to explore these areas and reveal some underlying themes connecting exponents, chaotic dynamics and renormalization. But first, what are Lyapunov exponents? Let’s begin by viewing them in one of their natural habitats: the iterated barycentric subdivision of a triangle. When the midpoint of each side of a triangle is connected to its opposite vertex by a line segment, the three resulting segments meet in a point in the interior of the triangle. The barycentric subdivision of a triangle is the collection of 6 smaller triangles determined by these segments and the edges of the original triangle: Figure 1. Barycentric subdivision. Received by the editors August 2, 2016. -
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. -
WHAT IS a CHAOTIC ATTRACTOR? 1. Introduction J. Yorke Coined the Word 'Chaos' As Applied to Deterministic Systems. R. Devane
WHAT IS A CHAOTIC ATTRACTOR? CLARK ROBINSON Abstract. Devaney gave a mathematical definition of the term chaos, which had earlier been introduced by Yorke. We discuss issues involved in choosing the properties that characterize chaos. We also discuss how this term can be combined with the definition of an attractor. 1. Introduction J. Yorke coined the word `chaos' as applied to deterministic systems. R. Devaney gave the first mathematical definition for a map to be chaotic on the whole space where a map is defined. Since that time, there have been several different definitions of chaos which emphasize different aspects of the map. Some of these are more computable and others are more mathematical. See [9] a comparison of many of these definitions. There is probably no one best or correct definition of chaos. In this paper, we discuss what we feel is one of better mathematical definition. (It may not be as computable as some of the other definitions, e.g., the one by Alligood, Sauer, and Yorke.) Our definition is very similar to the one given by Martelli in [8] and [9]. We also combine the concepts of chaos and attractors and discuss chaotic attractors. 2. Basic definitions We start by giving the basic definitions needed to define a chaotic attractor. We give the definitions for a diffeomorphism (or map), but those for a system of differential equations are similar. The orbit of a point x∗ by F is the set O(x∗; F) = f Fi(x∗) : i 2 Z g. An invariant set for a diffeomorphism F is an set A in the domain such that F(A) = A.