The Orbit Method and Its Applications Vignon Oussa Dalhousie
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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. -
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. -
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. -
Attractors and Orbit-Flip Homoclinic Orbits for Star Flows
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 141, Number 8, August 2013, Pages 2783–2791 S 0002-9939(2013)11535-2 Article electronically published on April 12, 2013 ATTRACTORS AND ORBIT-FLIP HOMOCLINIC ORBITS FOR STAR FLOWS C. A. MORALES (Communicated by Bryna Kra) Abstract. We study star flows on closed 3-manifolds and prove that they either have a finite number of attractors or can be C1 approximated by vector fields with orbit-flip homoclinic orbits. 1. Introduction The notion of attractor deserves a fundamental place in the modern theory of dynamical systems. This assertion, supported by the nowadays classical theory of turbulence [27], is enlightened by the recent Palis conjecture [24] about the abun- dance of dynamical systems with finitely many attractors absorbing most positive trajectories. If confirmed, such a conjecture means the understanding of a great part of dynamical systems in the sense of their long-term behaviour. Here we attack a problem which goes straight to the Palis conjecture: The fini- tude of the number of attractors for a given dynamical system. Such a problem has been solved positively under certain circunstances. For instance, we have the work by Lopes [16], who, based upon early works by Ma˜n´e [18] and extending pre- vious ones by Liao [15] and Pliss [25], studied the structure of the C1 structural stable diffeomorphisms and proved the finitude of attractors for such diffeomor- phisms. His work was largely extended by Ma˜n´e himself in the celebrated solution of the C1 stability conjecture [17]. On the other hand, the Japanesse researchers S. -
ORBIT EQUIVALENCE of ERGODIC GROUP ACTIONS These Are Partial Lecture Notes from a Topics Graduate Class Taught at UCSD in Fall 2
1 ORBIT EQUIVALENCE OF ERGODIC GROUP ACTIONS ADRIAN IOANA These are partial lecture notes from a topics graduate class taught at UCSD in Fall 2019. 1. Group actions, equivalence relations and orbit equivalence 1.1. Standard spaces. A Borel space (X; BX ) is a pair consisting of a topological space X and its σ-algebra of Borel sets BX . If the topology on X can be chosen to the Polish (i.e., separable, metrizable and complete), then (X; BX ) is called a standard Borel space. For simplicity, we will omit the σ-algebra and write X instead of (X; BX ). If (X; BX ) and (Y; BY ) are Borel spaces, then a map θ : X ! Y is called a Borel isomorphism if it is a bijection and θ and θ−1 are Borel measurable. Note that a Borel bijection θ is automatically a Borel isomorphism (see [Ke95, Corollary 15.2]). Definition 1.1. A standard probability space is a measure space (X; BX ; µ), where (X; BX ) is a standard Borel space and µ : BX ! [0; 1] is a σ-additive measure with µ(X) = 1. For simplicity, we will write (X; µ) instead of (X; BX ; µ). If (X; µ) and (Y; ν) are standard probability spaces, a map θ : X ! Y is called a measure preserving (m.p.) isomorphism if it is a Borel isomorphism and −1 measure preserving: θ∗µ = ν, where θ∗µ(A) = µ(θ (A)), for any A 2 BY . Example 1.2. The following are standard probability spaces: (1) ([0; 1]; λ), where [0; 1] is endowed with the Euclidean topology and its Lebegue measure λ. -
C*-Algebras and Kirillov's Coadjoint Orbit Method
C∗-ALGEBRAS AND KIRILLOV'S COADJOINT ORBIT METHOD DAVID SCHWEIN One of the main goals of representation theory is to understand the unitary dual of a topological group, that is, the set of irreducible unitary representations. Much of modern number theory, for instance, is concerned with describing the unitary duals of various reduc- tive groups over a local field or the adeles, and here our understanding of the representation theory is far from complete. For a different class of groups, the nilpotent Lie groups, A. A. Kirillov gave in the mid- nineteenth century [Kir62] a simple and transparent description of the unitary dual: it is the orbit space under the coadjoint action of the Lie group on the dual of its Lie algebra. The goal of this article, notes for a talk, is to explain Kirillov's result and illustrate it with the Heisenberg group, following Kirillov's excellent and approachable book on the subject [Kir04]. We begin with an introductory section on the unitary dual of a C∗-algebra, the proper setting (currently) for unitary representations of locally compact groups, following Dixmier's exhaustive monograph on C∗-algebras [Dix77]. 1. C∗-algebras and the unitary dual The theory of unitary representations of locally compact topological groups, for instance, reductive p-adic groups, is a special case of the more general theory of representations of C∗-algebras. In this section we review the representation theory of C∗-algebras and see how it specializes to that of topological groups. 1.1. Definitions and examples. A Banach algebra is a Banach space A equipped with an algebra structure with respect to which the norm is sub-multiplicative: ka · bk ≤ kak · kbk; a; b 2 A: We do note require Banach algebras to be unital, and in fact, we will see shortly that there are many natural examples that are not unital. -
Infinitely Renormalizable Quadratic Polynomials 1
TRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 352, Number 11, Pages 5077{5091 S 0002-9947(00)02514-9 Article electronically published on July 12, 2000 INFINITELY RENORMALIZABLE QUADRATIC POLYNOMIALS YUNPING JIANG Abstract. We prove that the Julia set of a quadratic polynomial which ad- mits an infinite sequence of unbranched, simple renormalizations with complex bounds is locally connected. The method in this study is three-dimensional puzzles. 1. Introduction Let P (z)=z2 + c be a quadratic polynomial where z is a complex variable and c is a complex parameter. The filled-in Julia set K of P is, by definition, the set of points z which remain bounded under iterations of P .TheJulia set J of P is the boundary of K. A central problem in the study of the dynamical system generated by P is to understand the topology of a Julia set J, in particular, the local connectivity for a connected Julia set. A connected set J in the complex plane is said to be locally connected if for every point p in J and every neighborhood U of p there is a neighborhood V ⊆ U such that V \ J is connected. We first give the definition of renormalizability. A quadratic-like map F : U ! V is a holomorphic, proper, degree two branched cover map, whereT U and V are ⊂ 1 −n two domains isomorphic to a disc and U V .ThenKF = n=0 F (U)and JF = @KF are the filled-in Julia set and the Julia set of F , respectively. We only consider those quadratic-like maps whose Julia sets are connected. -
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 . -
On Orbit Equivalence of Quasiconformal Anosov Flows Yong Fang
On orbit equivalence of quasiconformal Anosov flows Yong Fang To cite this version: Yong Fang. On orbit equivalence of quasiconformal Anosov flows. 2005. hal-00004412 HAL Id: hal-00004412 https://hal.archives-ouvertes.fr/hal-00004412 Preprint submitted on 10 Mar 2005 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. On Orbit Equivalence of Quasiconformal Anosov Flows Yong Fang U.M.R. 7501 du C.N.R.S, Institut de Recherche Math´ematique Avanc´ee, 7 rue Ren´eDescartes, 67084 Strasbourg C´edex, France (e-mail : [email protected]) Abstract – We classify up to C∞ orbit equivalence the volume-preserving quasiconformal Anosov flows whose strong stable and strong unstable distri- butions are at least three-dimensional. If one of the strong distributions is two-dimensional, then we get a partial classification. Using these classifica- tion results, we obtain the following rigidity result : Let Φ the the orbit foliation of the geodesic flow of a closed hyperbolic manifold of dimension at least three. Let Ψ be another C∞ one-dimensional foliation. If Φ is C1 conjuguate to Ψ, then Φ is C∞ conjuguate to Ψ. -
Fractal-Bits
fractal-bits Claude Heiland-Allen 2012{2019 Contents 1 buddhabrot/bb.c . 3 2 buddhabrot/bbcolourizelayers.c . 10 3 buddhabrot/bbrender.c . 18 4 buddhabrot/bbrenderlayers.c . 26 5 buddhabrot/bound-2.c . 33 6 buddhabrot/bound-2.gnuplot . 34 7 buddhabrot/bound.c . 35 8 buddhabrot/bs.c . 36 9 buddhabrot/bscolourizelayers.c . 37 10 buddhabrot/bsrenderlayers.c . 45 11 buddhabrot/cusp.c . 50 12 buddhabrot/expectmu.c . 51 13 buddhabrot/histogram.c . 57 14 buddhabrot/Makefile . 58 15 buddhabrot/spectrum.ppm . 59 16 buddhabrot/tip.c . 59 17 burning-ship-series-approximation/BossaNova2.cxx . 60 18 burning-ship-series-approximation/BossaNova.hs . 81 19 burning-ship-series-approximation/.gitignore . 90 20 burning-ship-series-approximation/Makefile . 90 21 .gitignore . 90 22 julia/.gitignore . 91 23 julia-iim/julia-de.c . 91 24 julia-iim/julia-iim.c . 94 25 julia-iim/julia-iim-rainbow.c . 94 26 julia-iim/julia-lsm.c . 98 27 julia-iim/Makefile . 100 28 julia/j-render.c . 100 29 mandelbrot-delta-cl/cl-extra.cc . 110 30 mandelbrot-delta-cl/delta.cl . 111 31 mandelbrot-delta-cl/Makefile . 116 32 mandelbrot-delta-cl/mandelbrot-delta-cl.cc . 117 33 mandelbrot-delta-cl/mandelbrot-delta-cl-exp.cc . 134 34 mandelbrot-delta-cl/README . 139 35 mandelbrot-delta-cl/render-library.sh . 142 36 mandelbrot-delta-cl/sft-library.txt . 142 37 mandelbrot-laurent/DM.gnuplot . 146 38 mandelbrot-laurent/Laurent.hs . 146 39 mandelbrot-laurent/Main.hs . 147 40 mandelbrot-series-approximation/args.h . 148 41 mandelbrot-series-approximation/emscripten.cpp . 150 42 mandelbrot-series-approximation/index.html . -
News on Quadratic Polynomials
Snapshots of modern mathematics № 2/2017 from Oberwolfach News on quadratic polynomials Lukas Pottmeyer Many problems in mathematics have remained un- solved because of missing links between mathemati- cal disciplines, such as algebra, geometry, analysis, or number theory. Here we introduce a recently discov- ered result concerning quadratic polynomials, which uses a bridge between algebra and analysis. We study the iterations of quadratic polynomials, obtained by computing the value of a polynomial for a given num- ber and feeding the outcome into the exact same poly- nomial again. These iterations of polynomials have interesting applications, such as in fractal theory. 1 Introduction Around the year 825, the Persian mathematician Muhammad al-Khwarizmi wrote his book Al-Kit¯abal-muhta.sar f¯i h. is¯abal-ğabr wa-’l-muq¯abala 1 (The Compendious Book on Calculation by Completion and Balancing). In his work he explains in detail how to solve equations of the form 3 x2 + 5 x = 1. (1) The ability to solve such equations was important already at that time. For example, these equations arose in disputes of inheritance and legacies. Nowadays, 1 You may be familiar with some of these words: The word al-ğabr is the origin of the word algebra and the name al-Khwarizmi gave rise to the word algorithm. 1 every high school student is familiar with the general formula for the solution p 2 of (1). The two solutions of (1) are x± = −5/6 ± (5/6) + 1/3. Given that we have been able to solve these equations without much difficul- ties for almost 1200 years, it may be surprising that we want to study something (seemingly) simple as quadratic equations in a report on modern mathematics.