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The Riemann Mapping Theorem Christopher J. Bishop
The Riemann Mapping Theorem Christopher J. Bishop C.J. Bishop, Mathematics Department, SUNY at Stony Brook, Stony Brook, NY 11794-3651 E-mail address: [email protected] 1991 Mathematics Subject Classification. Primary: 30C35, Secondary: 30C85, 30C62 Key words and phrases. numerical conformal mappings, Schwarz-Christoffel formula, hyperbolic 3-manifolds, Sullivan’s theorem, convex hulls, quasiconformal mappings, quasisymmetric mappings, medial axis, CRDT algorithm The author is partially supported by NSF Grant DMS 04-05578. Abstract. These are informal notes based on lectures I am giving in MAT 626 (Topics in Complex Analysis: the Riemann mapping theorem) during Fall 2008 at Stony Brook. We will start with brief introduction to conformal mapping focusing on the Schwarz-Christoffel formula and how to compute the unknown parameters. In later chapters we will fill in some of the details of results and proofs in geometric function theory and survey various numerical methods for computing conformal maps, including a method of my own using ideas from hyperbolic and computational geometry. Contents Chapter 1. Introduction to conformal mapping 1 1. Conformal and holomorphic maps 1 2. M¨obius transformations 16 3. The Schwarz-Christoffel Formula 20 4. Crowding 27 5. Power series of Schwarz-Christoffel maps 29 6. Harmonic measure and Brownian motion 39 7. The quasiconformal distance between polygons 48 8. Schwarz-Christoffel iterations and Davis’s method 56 Chapter 2. The Riemann mapping theorem 67 1. The hyperbolic metric 67 2. Schwarz’s lemma 69 3. The Poisson integral formula 71 4. A proof of Riemann’s theorem 73 5. Koebe’s method 74 6. -
On Isometries on Some Banach Spaces: Part I
Introduction Isometries on some important Banach spaces Hermitian projections Generalized bicircular projections Generalized n-circular projections On isometries on some Banach spaces { something old, something new, something borrowed, something blue, Part I Dijana Iliˇsevi´c University of Zagreb, Croatia Recent Trends in Operator Theory and Applications Memphis, TN, USA, May 3{5, 2018 Recent work of D.I. has been fully supported by the Croatian Science Foundation under the project IP-2016-06-1046. Dijana Iliˇsevi´c On isometries on some Banach spaces Introduction Isometries on some important Banach spaces Hermitian projections Generalized bicircular projections Generalized n-circular projections Something old, something new, something borrowed, something blue is referred to the collection of items that helps to guarantee fertility and prosperity. Dijana Iliˇsevi´c On isometries on some Banach spaces Introduction Isometries on some important Banach spaces Hermitian projections Generalized bicircular projections Generalized n-circular projections Isometries Isometries are maps between metric spaces which preserve distance between elements. Definition Let (X ; j · j) and (Y; k · k) be two normed spaces over the same field. A linear map ': X!Y is called a linear isometry if k'(x)k = jxj; x 2 X : We shall be interested in surjective linear isometries on Banach spaces. One of the main problems is to give explicit description of isometries on a particular space. Dijana Iliˇsevi´c On isometries on some Banach spaces Introduction Isometries on some important Banach spaces Hermitian projections Generalized bicircular projections Generalized n-circular projections Isometries Isometries are maps between metric spaces which preserve distance between elements. Definition Let (X ; j · j) and (Y; k · k) be two normed spaces over the same field. -
Computing the Complexity of the Relation of Isometry Between Separable Banach Spaces
Computing the complexity of the relation of isometry between separable Banach spaces Julien Melleray Abstract We compute here the Borel complexity of the relation of isometry between separable Banach spaces, using results of Gao, Kechris [1] and Mayer-Wolf [4]. We show that this relation is Borel bireducible to the universal relation for Borel actions of Polish groups. 1 Introduction Over the past fteen years or so, the theory of complexity of Borel equivalence relations has been a very active eld of research; in this paper, we compute the complexity of a relation of geometric nature, the relation of (linear) isom- etry between separable Banach spaces. Before stating precisely our result, we begin by quickly recalling the basic facts and denitions that we need in the following of the article; we refer the reader to [3] for a thorough introduction to the concepts and methods of descriptive set theory. Before going on with the proof and denitions, it is worth pointing out that this article mostly consists in putting together various results which were already known, and deduce from them after an easy manipulation the complexity of the relation of isometry between separable Banach spaces. Since this problem has been open for a rather long time, it still seems worth it to explain how this can be done, and give pointers to the literature. Still, it seems to the author that this will be mostly of interest to people with a knowledge of descriptive set theory, so below we don't recall descriptive set-theoretic notions but explain quickly what Lipschitz-free Banach spaces are and how that theory works. -
Isometries and the Plane
Chapter 1 Isometries of the Plane \For geometry, you know, is the gate of science, and the gate is so low and small that one can only enter it as a little child. (W. K. Clifford) The focus of this first chapter is the 2-dimensional real plane R2, in which a point P can be described by its coordinates: 2 P 2 R ;P = (x; y); x 2 R; y 2 R: Alternatively, we can describe P as a complex number by writing P = (x; y) = x + iy 2 C: 2 The plane R comes with a usual distance. If P1 = (x1; y1);P2 = (x2; y2) 2 R2 are two points in the plane, then p 2 2 d(P1;P2) = (x2 − x1) + (y2 − y1) : Note that this is consistent withp the complex notation. For P = x + iy 2 C, p 2 2 recall that jP j = x + y = P P , thus for two complex points P1 = x1 + iy1;P2 = x2 + iy2 2 C, we have q d(P1;P2) = jP2 − P1j = (P2 − P1)(P2 − P1) p 2 2 = j(x2 − x1) + i(y2 − y1)j = (x2 − x1) + (y2 − y1) ; where ( ) denotes the complex conjugation, i.e. x + iy = x − iy. We are now interested in planar transformations (that is, maps from R2 to R2) that preserve distances. 1 2 CHAPTER 1. ISOMETRIES OF THE PLANE Points in the Plane • A point P in the plane is a pair of real numbers P=(x,y). d(0,P)2 = x2+y2. • A point P=(x,y) in the plane can be seen as a complex number x+iy. -
Isometry and Automorphisms of Constant Dimension Codes
Isometry and Automorphisms of Constant Dimension Codes Isometry and Automorphisms of Constant Dimension Codes Anna-Lena Trautmann Institute of Mathematics University of Zurich \Crypto and Coding" Z¨urich, March 12th 2012 1 / 25 Isometry and Automorphisms of Constant Dimension Codes Introduction 1 Introduction 2 Isometry of Random Network Codes 3 Isometry and Automorphisms of Known Code Constructions Spread codes Lifted rank-metric codes Orbit codes 2 / 25 isometry classes are equivalence classes automorphism groups of linear codes are useful for decoding automorphism groups are canonical representative of orbit codes Isometry and Automorphisms of Constant Dimension Codes Introduction Motivation constant dimension codes are used for random network coding 3 / 25 automorphism groups of linear codes are useful for decoding automorphism groups are canonical representative of orbit codes Isometry and Automorphisms of Constant Dimension Codes Introduction Motivation constant dimension codes are used for random network coding isometry classes are equivalence classes 3 / 25 automorphism groups are canonical representative of orbit codes Isometry and Automorphisms of Constant Dimension Codes Introduction Motivation constant dimension codes are used for random network coding isometry classes are equivalence classes automorphism groups of linear codes are useful for decoding 3 / 25 Isometry and Automorphisms of Constant Dimension Codes Introduction Motivation constant dimension codes are used for random network coding isometry classes are equivalence classes automorphism groups of linear codes are useful for decoding automorphism groups are canonical representative of orbit codes 3 / 25 Definition Subspace metric: dS(U; V) = dim(U + V) − dim(U\V) Injection metric: dI (U; V) = max(dim U; dim V) − dim(U\V) Isometry and Automorphisms of Constant Dimension Codes Introduction Random Network Codes Definition n n The projective geometry P(Fq ) is the set of all subspaces of Fq . -
The Chazy XII Equation and Schwarz Triangle Functions
Symmetry, Integrability and Geometry: Methods and Applications SIGMA 13 (2017), 095, 24 pages The Chazy XII Equation and Schwarz Triangle Functions Oksana BIHUN and Sarbarish CHAKRAVARTY Department of Mathematics, University of Colorado, Colorado Springs, CO 80918, USA E-mail: [email protected], [email protected] Received June 21, 2017, in final form December 12, 2017; Published online December 25, 2017 https://doi.org/10.3842/SIGMA.2017.095 Abstract. Dubrovin [Lecture Notes in Math., Vol. 1620, Springer, Berlin, 1996, 120{348] showed that the Chazy XII equation y000 − 2yy00 + 3y02 = K(6y0 − y2)2, K 2 C, is equivalent to a projective-invariant equation for an affine connection on a one-dimensional complex manifold with projective structure. By exploiting this geometric connection it is shown that the Chazy XII solution, for certain values of K, can be expressed as y = a1w1 +a2w2 +a3w3 where wi solve the generalized Darboux{Halphen system. This relationship holds only for certain values of the coefficients (a1; a2; a3) and the Darboux{Halphen parameters (α; β; γ), which are enumerated in Table2. Consequently, the Chazy XII solution y(z) is parametrized by a particular class of Schwarz triangle functions S(α; β; γ; z) which are used to represent the solutions wi of the Darboux{Halphen system. The paper only considers the case where α + β +γ < 1. The associated triangle functions are related among themselves via rational maps that are derived from the classical algebraic transformations of hypergeometric functions. The Chazy XII equation is also shown to be equivalent to a Ramanujan-type differential system for a triple (P;^ Q;^ R^). -
Isometry Test for Coordinate Transformations Sudesh Kumar Arora
Isometry test for coordinate transformations Sudesh Kumar Arora Isometry test for coordinate transformations Sudesh Kumar Arora∗y Date January 30, 2020 Abstract A simple scheme is developed to test whether a given coordinate transformation of the metric tensor is an isometry or not. The test can also be used to predict the time dilation caused by any type of motion for a given space-time metric. Keywords and phrases: general relativity; coordinate transformation; diffeomorphism; isometry; symmetries. 1 Introduction Isometry is any coordinate transformation which preserves the distances. In special relativity, Minkowski metric has Poincare as the group of isometries, and the corresponding coordinate transformations leave the physical properties of the metric like distance invariant. In general relativity any infinitesimal trans- formation along Killing vector fields is an isometry. These are infinitesimal transformations generated by one parameter x0µ = xµ + V µ (1) Here V (x) = V µ@µ can be thought of like a vector field with components given as dx0µ V µ(x) = (x) (2) d All coordinate transformations generated such can be checked for isometry by calculating Lie deriva- tive of the metric tensors along the vector field V . If the Lie derivative vanishes then the transformation is an isometry (1; 2) and vector field V is called Killing Vector field. Killing vector fields are used to study the symmetries of the space-time metrics and the associated conserved quantities. But there are some challenges in using Killing equations for checking isometry. Coordinate transformations which are either discrete (not generated by the one-parameter ) or not possible to define as integral curves of a vectors field cannot be checked for isometry using this scheme. -
What Is Symmetry? What Is an Isometry?
2. SYMMETRY IN GEOMETRY 2.1. Isometries What is Symmetry? You probably have an intuitive idea of what symme- try means and can recognise it in various guises. For example, you can hopefully see that the letters N, O and M are symmetric, while the letter R is not. But probably, you can’t define in a mathematically pre- cise way what it means to be symmetric — this is something we’re going to address. Symmetry occurs very often in nature, a particular example being in the human body, as demonstrated by Leonardo da Vinci’s drawing of the Vitruvian Man on the right.1 The symmetry in the picture arises since it looks essentially the same when we flip it over. A particularly important observation about the drawing is that the distance from the Vitruvian Man’s left index finger to his left elbow is the same as the distance from his right index finger to his right elbow. Similarly, the distance from the Vitruvian Man’s left knee to his left eye is the same as the distance from his right knee to his right eye. We could go on and on writing down statements like this, but the point I’m trying to get at is that our intuitive notion of sym- metry — at least in geometry — is somehow tied up with the notion of distance. What is an Isometry? The flip in the previous discussion was a particular function which took points in the picture to other points in the picture. In particular, it did this in such a way that two points which were a certain distance apart would get mapped to two points which were the same distance apart. -
ISOMETRIES of Rn 1. Introduction an Isometry of R N Is A
ISOMETRIES OF Rn KEITH CONRAD 1. Introduction An isometry of Rn is a function h: Rn ! Rn that preserves the distance between vectors: jjh(v) − h(w)jj = jjv − wjj n p 2 2 for all v and w in R , where jj(x1; : : : ; xn)jj = x1 + ··· + xn. Example 1.1. The identity transformation: id(v) = v for all v 2 Rn. Example 1.2. Negation: − id(v) = −v for all v 2 Rn. n Example 1.3. Translation: fixing u 2 R , let tu(v) = v + u. Easily jjtu(v) − tu(w)jj = jjv − wjj. Example 1.4. Rotations around points and reflections across lines in the plane are isome- tries of R2. Formulas for these isometries will be given in Example 3.3 and Section4. The effects of a translation, rotation (around the origin) and reflection across a line in R2 are pictured below on sample line segments. The composition of two isometries of Rn is an isometry. Is every isometry invertible? It is clear that the three kinds of isometries pictured above (translations, rotations, reflections) are each invertible (translate by the negative vector, rotate by the opposite angle, reflect a second time across the same line). In Section2, we show the close link between isometries and the dot product on Rn, which is more convenient to use than distances due to its algebraic properties. Section3 is about the matrices that act as isometries on on Rn, called orthogonal matrices. Section 4 describes the isometries of R and R2 geometrically. In AppendixA, we will look more closely at reflections in Rn. -
Conjugacy Classification of Quaternionic M¨Obius Transformations
CONJUGACY CLASSIFICATION OF QUATERNIONIC MOBIUS¨ TRANSFORMATIONS JOHN R. PARKER AND IAN SHORT Abstract. It is well known that the dynamics and conjugacy class of a complex M¨obius transformation can be determined from a simple rational function of the coef- ficients of the transformation. We study the group of quaternionic M¨obius transforma- tions and identify simple rational functions of the coefficients of the transformations that determine dynamics and conjugacy. 1. Introduction The motivation behind this paper is the classical theory of complex M¨obius trans- formations. A complex M¨obiustransformation f is a conformal map of the extended complex plane of the form f(z) = (az + b)(cz + d)−1, where a, b, c and d are complex numbers such that the quantity σ = ad − bc is not zero (we sometimes write σ = σf in order to avoid ambiguity). There is a homomorphism from SL(2, C) to the group a b of complex M¨obiustransformations which takes the matrix ( c d ) to the map f. This homomorphism is surjective because the coefficients of f can always be scaled so that σ = 1. The collection of all complex M¨obius transformations for which σ takes the value 1 forms a group which can be identified with PSL(2, C). A member f of PSL(2, C) is simple if it is conjugate in PSL(2, C) to an element of PSL(2, R). The map f is k–simple if it may be expressed as the composite of k simple transformations but no fewer. Let τ = a + d (and likewise we write τ = τf where necessary). -
The Generic Isometry and Measure Preserving Homeomorphism Are Conjugate to Their Powers
THE GENERIC ISOMETRY AND MEASURE PRESERVING HOMEOMORPHISM ARE CONJUGATE TO THEIR POWERS CHRISTIAN ROSENDAL Abstract. It is known that there is a comeagre set of mutually conjugate measure preserving homeomorphisms of Cantor space equipped with the coin- flipping probability measure, i.e., Haar measure. We show that the generic measure preserving homeomorphism is moreover conjugate to all of its pow- ers. It follows that the generic measure preserving homeomorphism extends to an action of (Q; +) by measure preserving homeomorphisms, and, in fact, to an action of the locally compact ring A of finite ad`eles. Similarly, S. Solecki has proved that there is a comeagre set of mutually conjugate isometries of the rational Urysohn metric space. We prove that these are all conjugate with their powers and therefore also embed into Q-actions. In fact, we extend these actions to actions of A as in the case of measure preserving homeomorphisms. We also consider a notion of topological similarity in Polish groups and use this to give simplified proofs of the meagreness of conjugacy classes in the automorphism group of the standard probability space and in the isometry group of the Urysohn metric space. Contents 1. Introduction 1 2. Powers of generic measure preserving homeomorphisms 4 2.1. Free amalgams of measured Boolean algebras 4 2.2. Roots of measure preserving homeomorphisms 6 2.3. The ring of finite ad`eles 9 2.4. Actions of A by measure preserving homeomorphisms 12 3. Powers of generic isometries 15 3.1. Free amalgams of metric spaces 15 3.2. Roots of isometries 15 3.3. -
Conformal Mapping Solution of Laplace's Equation on a Polygon
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Computational and Applied Mathematics 14 (1986) 227-249 227 North-Holland Conformal mapping solution of Laplace’s equation on a polygon with oblique derivative boundary conditions Lloyd N. TREFETHEN * Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, U.S.A. Ruth J. WILLIAMS ** Department of Mathematics, University of California at San Diego, La Jolla, CA 92093, U.S.A. Received 6 July 1984 Abstract: We consider Laplace’s equation in a polygonal domain together with the boundary conditions that along each side, the derivative in the direction at a specified oblique angle from the normal should be zero. First we prove that solutions to this problem can always be constructed by taking the real part of an analytic function that maps the domain onto another region with straight sides oriented according to the angles given in the boundary conditions. Then we show that this procedure can be carried out successfully in practice by the numerical calculation of Schwarz-Christoffel transformations. The method is illustrated by application to a Hall effect problem in electronics, and to a reflected Brownian motion problem motivated by queueing theory. Keywor& Laplace equation, conformal mapping, Schwarz-Christoffel map, oblique derivative, Hall effect, Brownian motion, queueing theory. Mathematics Subject CIassi/ication: 3OC30, 35525, 60K25, 65EO5, 65N99. 1. The oblique derivative problem and conformal mapping Let 52 by a polygonal domain in the complex plane C, by which we mean a possibly unbounded simply connected open subset of C whose boundary aa consists of a finite number of straight lines, rays, and line segments.