Discrete Chaos, Second Edition
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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. -
The Topological Entropy Conjecture
mathematics Article The Topological Entropy Conjecture Lvlin Luo 1,2,3,4 1 Arts and Sciences Teaching Department, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China; [email protected] or [email protected] 2 School of Mathematical Sciences, Fudan University, Shanghai 200433, China 3 School of Mathematics, Jilin University, Changchun 130012, China 4 School of Mathematics and Statistics, Xidian University, Xi’an 710071, China Abstract: For a compact Hausdorff space X, let J be the ordered set associated with the set of all finite open covers of X such that there exists nJ, where nJ is the dimension of X associated with ¶. Therefore, we have Hˇ p(X; Z), where 0 ≤ p ≤ n = nJ. For a continuous self-map f on X, let a 2 J be f an open cover of X and L f (a) = fL f (U)jU 2 ag. Then, there exists an open fiber cover L˙ f (a) of X induced by L f (a). In this paper, we define a topological fiber entropy entL( f ) as the supremum of f ent( f , L˙ f (a)) through all finite open covers of X = fL f (U); U ⊂ Xg, where L f (U) is the f-fiber of − U, that is the set of images f n(U) and preimages f n(U) for n 2 N. Then, we prove the conjecture log r ≤ entL( f ) for f being a continuous self-map on a given compact Hausdorff space X, where r is the maximum absolute eigenvalue of f∗, which is the linear transformation associated with f on the n L Cechˇ homology group Hˇ ∗(X; Z) = Hˇ i(X; Z). -
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. -
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. -
Topological Invariance of the Sign of the Lyapunov Exponents in One-Dimensional Maps
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 134, Number 1, Pages 265–272 S 0002-9939(05)08040-8 Article electronically published on August 19, 2005 TOPOLOGICAL INVARIANCE OF THE SIGN OF THE LYAPUNOV EXPONENTS IN ONE-DIMENSIONAL MAPS HENK BRUIN AND STEFANO LUZZATTO (Communicated by Michael Handel) Abstract. We explore some properties of Lyapunov exponents of measures preserved by smooth maps of the interval, and study the behaviour of the Lyapunov exponents under topological conjugacy. 1. Statement of results In this paper we consider C3 interval maps f : I → I,whereI is a compact interval. We let C denote the set of critical points of f: c ∈C⇔Df(c)=0.We shall always suppose that C is finite and that each critical point is non-flat: for each ∈C ∈ ∞ 1 ≤ |f(x)−f(c)| ≤ c ,thereexist = (c) [2, )andK such that K |x−c| K for all x = c.LetM be the set of ergodic Borel f-invariant probability measures. For every µ ∈M, we define the Lyapunov exponent λ(µ)by λ(µ)= log |Df|dµ. Note that log |Df|dµ < +∞ is automatic since Df is bounded. However we can have log |Df|dµ = −∞ if c ∈Cis a fixed point and µ is the Dirac-δ measure on c. It follows from [15, 1] that this is essentially the only way in which log |Df| can be non-integrable: if µ(C)=0,then log |Df|dµ > −∞. The sign, more than the actual value, of the Lyapunov exponent can have signif- icant implications for the dynamics. A positive Lyapunov exponent, for example, indicates sensitivity to initial conditions and thus “chaotic” dynamics of some kind. -
Writing the History of Dynamical Systems and Chaos
Historia Mathematica 29 (2002), 273–339 doi:10.1006/hmat.2002.2351 Writing the History of Dynamical Systems and Chaos: View metadata, citation and similar papersLongue at core.ac.uk Dur´ee and Revolution, Disciplines and Cultures1 brought to you by CORE provided by Elsevier - Publisher Connector David Aubin Max-Planck Institut fur¨ Wissenschaftsgeschichte, Berlin, Germany E-mail: [email protected] and Amy Dahan Dalmedico Centre national de la recherche scientifique and Centre Alexandre-Koyre,´ Paris, France E-mail: [email protected] Between the late 1960s and the beginning of the 1980s, the wide recognition that simple dynamical laws could give rise to complex behaviors was sometimes hailed as a true scientific revolution impacting several disciplines, for which a striking label was coined—“chaos.” Mathematicians quickly pointed out that the purported revolution was relying on the abstract theory of dynamical systems founded in the late 19th century by Henri Poincar´e who had already reached a similar conclusion. In this paper, we flesh out the historiographical tensions arising from these confrontations: longue-duree´ history and revolution; abstract mathematics and the use of mathematical techniques in various other domains. After reviewing the historiography of dynamical systems theory from Poincar´e to the 1960s, we highlight the pioneering work of a few individuals (Steve Smale, Edward Lorenz, David Ruelle). We then go on to discuss the nature of the chaos phenomenon, which, we argue, was a conceptual reconfiguration as -
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. -
Multiple Periodic Solutions and Fractal Attractors of Differential Equations with N-Valued Impulses
mathematics Article Multiple Periodic Solutions and Fractal Attractors of Differential Equations with n-Valued Impulses Jan Andres Department of Mathematical Analysis and Applications of Mathematics, Faculty of Science, Palacký University, 17. listopadu 12, 771 46 Olomouc, Czech Republic; [email protected] Received: 10 September 2020; Accepted: 30 September 2020; Published: 3 October 2020 Abstract: Ordinary differential equations with n-valued impulses are examined via the associated Poincaré translation operators from three perspectives: (i) the lower estimate of the number of periodic solutions on the compact subsets of Euclidean spaces and, in particular, on tori; (ii) weakly locally stable (i.e., non-ejective in the sense of Browder) invariant sets; (iii) fractal attractors determined implicitly by the generating vector fields, jointly with Devaney’s chaos on these attractors of the related shift dynamical systems. For (i), the multiplicity criteria can be effectively expressed in terms of the Nielsen numbers of the impulsive maps. For (ii) and (iii), the invariant sets and attractors can be obtained as the fixed points of topologically conjugated operators to induced impulsive maps in the hyperspaces of the compact subsets of the original basic spaces, endowed with the Hausdorff metric. Five illustrative examples of the main theorems are supplied about multiple periodic solutions (Examples 1–3) and fractal attractors (Examples 4 and 5). Keywords: impulsive differential equations; n-valued maps; Hutchinson-Barnsley operators; multiple periodic solutions; topological fractals; Devaney’s chaos on attractors; Poincaré operators; Nielsen number MSC: 28A20; 34B37; 34C28; Secondary 34C25; 37C25; 58C06 1. Introduction The theory of impulsive differential equations and inclusions has been systematically developed (see e.g., the monographs [1–4], and the references therein), among other things, especially because of many practical applications (see e.g., References [1,4–11]). -
Arxiv:1812.04689V1 [Math.DS] 11 Dec 2018 Fasltigipisteeitneo W Oitos Into Foliations, Two Years
FOLIATIONS AND CONJUGACY, II: THE MENDES CONJECTURE FOR TIME-ONE MAPS OF FLOWS JORGE GROISMAN AND ZBIGNIEW NITECKI Abstract. A diffeomorphism f: R2 →R2 in the plane is Anosov if it has a hyperbolic splitting at every point of the plane. The two known topo- logical conjugacy classes of such diffeomorphisms are linear hyperbolic automorphisms and translations (the existence of Anosov structures for plane translations was originally shown by W. White). P. Mendes con- jectured that these are the only topological conjugacy classes for Anosov diffeomorphisms in the plane. We prove that this claim holds when the Anosov diffeomorphism is the time-one map of a flow, via a theorem about foliations invariant under a time one map. 1. Introduction A diffeomorphism f: M →M of a compact manifold M is called Anosov if it has a global hyperbolic splitting of the tangent bundle. Such diffeomor- phisms have been studied extensively in the past fifty years. The existence of a splitting implies the existence of two foliations, into stable (resp. unsta- ble) manifolds, preserved by the diffeomorphism, such that the map shrinks distances along the stable leaves, while its inverse does so for the unstable ones. Anosov diffeomorphisms of compact manifolds have strong recurrence properties. The existence of an Anosov structure when M is compact is independent of the Riemann metric used to define it, and the foliations are invariants of topological conjugacy. By contrast, an Anosov structure on a non-compact manifold is highly dependent on the Riemann metric, and the recurrence arXiv:1812.04689v1 [math.DS] 11 Dec 2018 properties observed in the compact case do not hold in general. -
Quasiconformal Homeomorphisms in Dynamics, Topology, and Geometry
Proceedings of the International Congress of Mathematicians Berkeley, California, USA, 1986 Quasiconformal Homeomorphisms in Dynamics, Topology, and Geometry DENNIS SULLIVAN Dedicated to R. H. Bing This paper has four parts. Each part involves quasiconformal homeomor phisms. These can be defined between arbitrary metric spaces: <p: X —* Y is Ä'-quasiconformal (or K qc) if zjf \ _ r SUP 1^0*0 ~ Piv) wnere \x - y\ = r and x is fixed r_>o inf \<p(x) — <p(y)\ where \x — y\ = r and x is fixed is at most K where | | means distance. Between open sets in Euclidean space, H(x) < K implies <p has many interesting analytic properties. (See Gehring's lecture at this congress.) In the first part we discuss Feigenbaum's numerical discoveries in one-dimen sional iteration problems. Quasiconformal conjugacies can be used to define a useful coordinate independent distance between real analytic dynamical systems which is decreased by Feigenbaum's renormalization operator. In the second part we discuss de Rham, Atiyah-Singer, and Yang-Mills the ory in its foundational aspect on quasiconformal manifolds. The discussion (which is joint work with Simon Donaldson) connects with Donaldson's work and Freedman's work to complete a nice picture in the structure of manifolds— each topological manifold has an essentially unique quasiconformal structure in all dimensions—except four (Sullivan [21]). In dimension 4 both parts of the statement are false (Donaldson and Sullivan [3]). In the third part we discuss the C-analytic classification of expanding analytic transformations near fractal invariant sets. The infinite dimensional Teichmüller ^spare-ofnsuch=systemrìs^embedded=in^ for the transformation on the fractal. -
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. -
Mostly Conjugate: Relating Dynamical Systems — Beyond Homeomorphism
Mostly Conjugate: Relating Dynamical Systems — Beyond Homeomorphism Joseph D. Skufca1, ∗ and Erik M. Bollt1, † 1 Department of Mathematics, Clarkson University, Potsdam, New York (Dated: April 24, 2006) A centerpiece of Dynamical Systems is comparison by an equivalence relationship called topolog- ical conjugacy. Current state of the field is that, generally, there is no easy way to determine if two systems are conjugate or to explicitly find the conjugacy between systems that are known to be equivalent. We present a new and highly generalizable method to produce conjugacy functions based on a functional fixed point iteration scheme. In specific cases, we prove that although the conjugacy function is strictly increasing, it is a.e. differentiable, with derivative 0 everywhere that it exists — a Lebesgue singular function. When applied to non-conjugate dynamical systems, we show that the fixed point iteration scheme still has a limit point, which is a function we now call a “commuter” — a non-homeomorphic change of coordinates translating between dissimilar systems. This translation is natural to the concepts of dynamical systems in that it matches the systems within the language of their orbit structures. We introduce methods to compare nonequivalent sys- tems by quantifying how much the commuter functions fails to be a homeomorphism, an approach that gives more respect to the dynamics than the traditional comparisons based on normed linear spaces, such as L2. Our discussion includes fundamental issues as a principled understanding of the degree to which a “toy model” might be representative of a more complicated system, an important concept to clarify since it is often used loosely throughout science.