ERGODIC and SPECTRAL PROPERTIES an Interval Exchange
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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). -
Ergodic Theory
MATH41112/61112 Ergodic Theory Charles Walkden 4th January, 2018 MATH4/61112 Contents Contents 0 Preliminaries 2 1 An introduction to ergodic theory. Uniform distribution of real se- quences 4 2 More on uniform distribution mod 1. Measure spaces. 13 3 Lebesgue integration. Invariant measures 23 4 More examples of invariant measures 38 5 Ergodic measures: definition, criteria, and basic examples 43 6 Ergodic measures: Using the Hahn-Kolmogorov Extension Theorem to prove ergodicity 53 7 Continuous transformations on compact metric spaces 62 8 Ergodic measures for continuous transformations 72 9 Recurrence 83 10 Birkhoff’s Ergodic Theorem 89 11 Applications of Birkhoff’s Ergodic Theorem 99 12 Solutions to the Exercises 108 1 MATH4/61112 0. Preliminaries 0. Preliminaries 0.1 Contact details § The lecturer is Dr Charles Walkden, Room 2.241, Tel: 0161 275 5805, Email: [email protected]. My office hour is: Monday 2pm-3pm. If you want to see me at another time then please email me first to arrange a mutually convenient time. 0.2 Course structure § This is a reading course, supported by one lecture per week. I have split the notes into weekly sections. You are expected to have read through the material before the lecture, and then go over it again afterwards in your own time. In the lectures I will highlight the most important parts, explain the statements of the theorems and what they mean in practice, and point out common misunderstandings. As a general rule, I will not normally go through the proofs in great detail (but they are examinable unless indicated otherwise). -
MA427 Ergodic Theory
MA427 Ergodic Theory Course Notes (2012-13) 1 Introduction 1.1 Orbits Let X be a mathematical space. For example, X could be the unit interval [0; 1], a circle, a torus, or something far more complicated like a Cantor set. Let T : X ! X be a function that maps X into itself. Let x 2 X be a point. We can repeatedly apply the map T to the point x to obtain the sequence: fx; T (x);T (T (x));T (T (T (x))); : : : ; :::g: We will often write T n(x) = T (··· (T (T (x)))) (n times). The sequence of points x; T (x);T 2(x);::: is called the orbit of x. We think of applying the map T as the passage of time. Thus we think of T (x) as where the point x has moved to after time 1, T 2(x) is where the point x has moved to after time 2, etc. Some points x 2 X return to where they started. That is, T n(x) = x for some n > 1. We say that such a point x is periodic with period n. By way of contrast, points may move move densely around the space X. (A sequence is said to be dense if (loosely speaking) it comes arbitrarily close to every point of X.) If we take two points x; y of X that start very close then their orbits will initially be close. However, it often happens that in the long term their orbits move apart and indeed become dramatically different. -
Conformal Fractals – Ergodic Theory Methods
Conformal Fractals – Ergodic Theory Methods Feliks Przytycki Mariusz Urba´nski May 17, 2009 2 Contents Introduction 7 0 Basic examples and definitions 15 1 Measure preserving endomorphisms 25 1.1 Measurespacesandmartingaletheorem . 25 1.2 Measure preserving endomorphisms, ergodicity . .. 28 1.3 Entropyofpartition ........................ 34 1.4 Entropyofendomorphism . 37 1.5 Shannon-Mcmillan-Breimantheorem . 41 1.6 Lebesguespaces............................ 44 1.7 Rohlinnaturalextension . 48 1.8 Generalized entropy, convergence theorems . .. 54 1.9 Countabletoonemaps.. .. .. .. .. .. .. .. .. .. 58 1.10 Mixingproperties . .. .. .. .. .. .. .. .. .. .. 61 1.11 Probabilitylawsand Bernoulliproperty . 63 Exercises .................................. 68 Bibliographicalnotes. 73 2 Compact metric spaces 75 2.1 Invariantmeasures . .. .. .. .. .. .. .. .. .. .. 75 2.2 Topological pressure and topological entropy . ... 83 2.3 Pressureoncompactmetricspaces . 87 2.4 VariationalPrinciple . 89 2.5 Equilibrium states and expansive maps . 94 2.6 Functionalanalysisapproach . 97 Exercises ..................................106 Bibliographicalnotes. 109 3 Distance expanding maps 111 3.1 Distance expanding open maps, basic properties . 112 3.2 Shadowingofpseudoorbits . 114 3.3 Spectral decomposition. Mixing properties . 116 3.4 H¨older continuous functions . 122 3 4 CONTENTS 3.5 Markov partitions and symbolic representation . 127 3.6 Expansive maps are expanding in some metric . 134 Exercises .................................. 136 Bibliographicalnotes. 138 4 -
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 -
AN INTRODUCTION to DYNAMICAL BILLIARDS Contents 1
AN INTRODUCTION TO DYNAMICAL BILLIARDS SUN WOO PARK 2 Abstract. Some billiard tables in R contain crucial references to dynamical systems but can be analyzed with Euclidean geometry. In this expository paper, we will analyze billiard trajectories in circles, circular rings, and ellipses as well as relate their charactersitics to ergodic theory and dynamical systems. Contents 1. Background 1 1.1. Recurrence 1 1.2. Invariance and Ergodicity 2 1.3. Rotation 3 2. Dynamical Billiards 4 2.1. Circle 5 2.2. Circular Ring 7 2.3. Ellipse 9 2.4. Completely Integrable 14 Acknowledgments 15 References 15 Dynamical billiards exhibits crucial characteristics related to dynamical systems. Some billiard tables in R2 can be understood with Euclidean geometry. In this ex- pository paper, we will analyze some of the billiard tables in R2, specifically circles, circular rings, and ellipses. In the first section we will present some preliminary background. In the second section we will analyze billiard trajectories in the afore- mentioned billiard tables and relate their characteristics with dynamical systems. We will also briefly discuss the notion of completely integrable billiard mappings and Birkhoff's conjecture. 1. Background (This section follows Chapter 1 and 2 of Chernov [1] and Chapter 3 and 4 of Rudin [2]) In this section, we define basic concepts in measure theory and ergodic theory. We will focus on probability measures, related theorems, and recurrent sets on certain maps. The definitions of probability measures and σ-algebra are in Chapter 1 of Chernov [1]. 1.1. Recurrence. Definition 1.1. Let (X,A,µ) and (Y ,B,υ) be measure spaces. -
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]). -
Ergodic Theory, Fractal Tops and Colour Stealing 1
ERGODIC THEORY, FRACTAL TOPS AND COLOUR STEALING MICHAEL BARNSLEY Abstract. A new structure that may be associated with IFS and superIFS is described. In computer graphics applications this structure can be rendered using a new algorithm, called the “colour stealing”. 1. Ergodic Theory and Fractal Tops The goal of this lecture is to describe informally some recent realizations and work in progress concerning IFS theory with application to the geometric modelling and assignment of colours to IFS fractals and superfractals. The results will be described in the simplest setting of a single IFS with probabilities, but many generalizations are possible, most notably to superfractals. Let the iterated function system (IFS) be denoted (1.1) X; f1, ..., fN ; p1,...,pN . { } This consists of a finite set of contraction mappings (1.2) fn : X X,n=1, 2, ..., N → acting on the compact metric space (1.3) (X,d) with metric d so that for some (1.4) 0 l<1 ≤ we have (1.5) d(fn(x),fn(y)) l d(x, y) ≤ · for all x, y X.Thepn’s are strictly positive probabilities with ∈ (1.6) pn =1. n X The probability pn is associated with the map fn. We begin by reviewing the two standard structures (one and two)thatare associated with the IFS 1.1, namely its set attractor and its measure attractor, with emphasis on the Collage Property, described below. This property is of particular interest for geometrical modelling and computer graphics applications because it is the key to designing IFSs with attractor structures that model given inputs. -
Dynamical Systems and Ergodic Theory
MATH36206 - MATHM6206 Dynamical Systems and Ergodic Theory Teaching Block 1, 2017/18 Lecturer: Prof. Alexander Gorodnik PART III: LECTURES 16{30 course web site: people.maths.bris.ac.uk/∼mazag/ds17/ Copyright c University of Bristol 2010 & 2016. This material is copyright of the University. It is provided exclusively for educational purposes at the University and is to be downloaded or copied for your private study only. Chapter 3 Ergodic Theory In this last part of our course we will introduce the main ideas and concepts in ergodic theory. Ergodic theory is a branch of dynamical systems which has strict connections with analysis and probability theory. The discrete dynamical systems f : X X studied in topological dynamics were continuous maps f on metric spaces X (or more in general, topological→ spaces). In ergodic theory, f : X X will be a measure-preserving map on a measure space X (we will see the corresponding definitions below).→ While the focus in topological dynamics was to understand the qualitative behavior (for example, periodicity or density) of all orbits, in ergodic theory we will not study all orbits, but only typical1 orbits, but will investigate more quantitative dynamical properties, as frequencies of visits, equidistribution and mixing. An example of a basic question studied in ergodic theory is the following. Let A X be a subset of O+ ⊂ the space X. Consider the visits of an orbit f (x) to the set A. If we consider a finite orbit segment x, f(x),...,f n−1(x) , the number of visits to A up to time n is given by { } Card 0 k n 1, f k(x) A . -
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. -
Ergodic Theory Approach to Chaos: Remarks and Computational Aspects
Int. J. Appl. Math. Comput. Sci., 2012, Vol. 22, No. 2, 259–267 DOI: 10.2478/v10006-012-0019-4 ERGODIC THEORY APPROACH TO CHAOS: REMARKS AND COMPUTATIONAL ASPECTS ∗ ∗∗ PAWEŁ J. MITKOWSKI ,WOJCIECH MITKOWSKI ∗ Faculty of Electrical Engineering, Automatics, Computer Science and Electronics AGH University of Science and Technology, al. Mickiewicza 30/B-1, 30-059 Cracow, Poland e-mail: [email protected] ∗∗Department of Automatics AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland e-mail: [email protected] We discuss basic notions of the ergodic theory approach to chaos. Based on simple examples we show some characteristic features of ergodic and mixing behaviour. Then we investigate an infinite dimensional model (delay differential equation) of erythropoiesis (red blood cell production process) formulated by Lasota. We show its computational analysis on the pre- viously presented theory and examples. Our calculations suggest that the infinite dimensional model considered possesses an attractor of a nonsimple structure, supporting an invariant mixing measure. This observation verifies Lasota’s conjecture concerning nontrivial ergodic properties of the model. Keywords: ergodic theory, chaos, invariant measures, attractors, delay differential equations. 1. Introduction man, 2001). Transformations (or flows) with an invariant measure display three main levels of irregular behaviour, In the literature concerning dynamical systems we can i.e., (ranging from the lowest to the highest) ergodicity, find many definitions of chaos in various approaches mixing and exactness. Between ergodicity and mixing we (Rudnicki, 2004; Devaney, 1987; Bronsztejn et al., 2004). can also distinguish light mixing, mild mixing and weak Our central issue here will be the ergodic theory appro- mixing (Lasota and Mackey, 1994; Silva, 2010) and, on ach.