Vector Calculus and the Topology of Domains in 3-Space, II Jason Cantarella, Dennis Deturck and Herman Gluck

Total Page:16

File Type:pdf, Size:1020Kb

Vector Calculus and the Topology of Domains in 3-Space, II Jason Cantarella, Dennis Deturck and Herman Gluck Vector Calculus and the Topology of Domains in 3-Space, II Jason Cantarella, Dennis DeTurck and Herman Gluck 1. Introduction Suppose you have a vector field defined only on the boundary of a compact domain in 3-space. How can you tell whether your vector field can be extended throughout the domain so that it is divergence-free? Or curl-free? Or both? Or have specified divergence? Or specified curl? Or both? To answer these questions, you need to understand the relationship between the calculus of vector fields and the topology of their domains of definition. The Hodge Decomposition Theorem, which was discussed and proved in the first paper of this two-part series [12], provides the key by decomposing the space of vector fields on the domain into five mutually orthogonal subspaces which are topologically and an- alytically meaningful. Our goal in this paper is to show how this theorem can be used to derive the basic boundary-value theorems for vector fields, which in turn will answer the questions above. As we shall see, each of these questions can be restated as a problem in partial differential equations, and it will be essential for us to identify appropriate boundary conditions so that a solution will exist and be unique, or so that the set of solutions is parametrized in a meaningful way. In particular, we will consider the problem of finding an unknown vector field V on Ω whose curl and/or divergence are specified in advance. If just one of these is given, then the value of V on the boundary of Ω is also specified. If both the curl and divergence are given, then either the parallel or normal component of V along ∂Ω is specified. Appropriate integrability conditions must be imposed in each case. The resulting theorems provide us with a very natural follow-up to, and application of, the Hodge Decomposition Theorem. 1 2 cantarella, deturck, and gluck 2. The Hodge Decomposition Theorem To begin, we state the Hodge Decomposition Theorem, explain the conditions in the theorem, and give a brief outline of its proof. For further details, including examples of vector fields that belong to each of the five summands and a discussion of absolute and relative homology of domains in 3-space, see [12]. Let Ω be a compact domain in 3-space with smooth boundary ∂Ω. Let VF(Ω) be the infinite-dimensional vector space of all smooth vector fields in Ω, on which we 2 · use the L inner product V,W = Ω V W d(vol). In this paper, “smooth” always means “all partial derivatives of all orders exist and are continuous”. HODGE DECOMPOSITION THEOREM. The space VF(Ω) is the direct sum of five mutually orthogonal subspaces: VF(Ω) = FK ⊕ HK ⊕ CG ⊕ HG ⊕ GG with ker curl =HK⊕ CG ⊕ HG ⊕ GG im grad =CG⊕ HG ⊕ GG im curl =FK⊕ HK ⊕ CG ker div =FK⊕ HK ⊕ CG ⊕ HG, where FK=fluxless knots = {∇ · V =0,V· n =0, all interior fluxes = 0}, HK=harmonic knots = {∇ · V =0, ∇×V = 0,V· n =0}, CG=curly gradients = {V = ∇ϕ, ∇·V =0, all boundary fluxes = 0}, HG=harmonic gradients = {V = ∇ϕ, ∇·V =0,ϕlocally constant on ∂Ω}, GG=grounded gradients = {V = ∇ϕ, ϕ|∂Ω =0}, and furthermore, ∼ ∼ ∼ genus of ∂Ω HK = H1(Ω; R) = H2(Ω,∂Ω; R) = R ∼ ∼ ∼ (# components of ∂Ω) − (# components of Ω) HG = H2(Ω; R) = H1(Ω,∂Ω; R) = R . Consider the subspace of VF(Ω) consisting of all divergence-free vector fields on Ω that are tangent to ∂Ω. These vector fields are used to represent incompressible fluid flows within fixed boundaries, and magnetic fields inside plasma containment devices; see [4], [6], [7], [23], [31],and[33]. When a problem in geometric knot theory is transformed to one in fluid dynamics, the knot is thickened to a tubular neighborhood of itself, and then represented by an incompressible fluid flow (sometimes called a fluid knot) in this neighborhood, much like blood pumping miraculously through an arterial loop; see [3], [26, 27, 29] and our paper [9]. With this last application in mind, we define K = knots = {V ∈ VF(Ω) : ∇·V =0,V· n =0}, where n is the unit outward normal to the boundary of Ω, and where the condition ∇·V = 0 holds throughout Ω, while V · n = 0 holds only on its boundary. In general, vector calculus and the topology of domains in 3-space, ii 3 when we state conditions for our vector fields using n, they are understood to apply only on the boundary of Ω. At the same time, we define G = gradients = {V ∈ VF(Ω) : V = ∇ϕ} for some smooth real-valued function ϕ defined on Ω. Proposition 1. The space VF(Ω) is the direct sum of two orthogonal subspaces: VF(Ω) = K ⊕ G . The Hodge Decomposition Theorem provides a further decomposition of K into an orthogonal direct sum of two subspaces, and of G into an orthogonal direct sum of three subspaces. We start by decomposing the subspace K. Let Σ stand generically for any smooth orientable surface in Ω whose boundary ∂Σ lies in the boundary ∂Ω of the domain Ω. We call Σ a cross-sectional surface and write (Σ,∂Σ) ⊂ (Ω,∂Ω). We orient Σ by choosing one of its two unit normal vector fields n. Then, for any vector field V on Ω, we define the flux of V through Σtobe the value of the integral Φ= V · n d(area). Σ Assume that V is divergence-free and tangent to ∂Ω. Then the value of this flux depends only on the homology class of Σ in the relative homology group H2(Ω,∂Ω; R). For example, if Ω is an n-holed solid torus, this homology group is generated by disjoint oriented cross-sectional disks Σ1,Σ2,..., Σn, positioned so that cutting Ω along these disks will produce a simply-connected region, as in Figure 1. The fluxes fig 2 Φ1,Φ2,...,Φn of V through these disks determine the flux of V through any other from H1 cross-sectional surface. If the flux of V through every cross-sectional surface vanishes, then we say all interior fluxes = 0, and define FK = fluxless knots = {V ∈ VF(Ω) : ∇·V =0,V · n =0, all interior fluxes = 0}. Next we define HK = harmonic knots = {V ∈ VF(Ω) : ∇·V =0, ∇×V = 0,V· n =0}. We showed in [12] that HK is isomorphic to the homology group H1(Ω, R)and also, via Poincar´e duality, to the relative homology group H2(Ω,∂Ω; R). This is a finite-dimensional vector space, with dimension equal to the (total) genus of ∂Ω, which is obtained by adding the genera of the boundary components of the domain Ω. 4 cantarella, deturck, and gluck Proposition 2.ThesubspaceK is the direct sum of two orthogonal subspaces: K =FK⊕ HK . Now we decompose the subspace G of gradient vector fields. Define DFG = divergence-free gradients = {V ∈ VF(Ω) : V = ∇ϕ, ∇·V =0}, which is the subspace of gradients of harmonic functions, and GG = grounded gradients = {V ∈ VF(Ω) : V = ∇ϕ, ϕ|∂Ω =0}, which is the subspace of gradients of functions that vanish on the boundary of Ω. Proposition 3.ThesubspaceG is the direct sum of two orthogonal subspaces: G =DFG⊕ GG . Now we decompose the subspace DFG of divergence-free gradient vector fields. If V is a vector field defined on Ω, we will say that all boundary fluxes of V are zero, if the flux of V through each component of ∂Ω is zero. Note that in general this is a stronger condition than saying that the flux of V through the boundary of each component of Ω is zero. This latter condition is used in Proposition 6. We define CG = curly gradients = {V ∈ VF(Ω) : V = ∇ϕ, ∇·V =0, all boundary fluxes = 0}. We call CG the subspace of curly gradients because these are the only gradient vector fields that lie in the image of curl. Finally, we define the subspace HG = harmonic gradients = {V ∈ VF(Ω) : V = ∇ϕ, ∇·V =0,ϕlocally constant on ∂Ω}, meaning that ϕ is constant on each component of ∂Ω. HG is isomorphic to the homology group H2(Ω; R) and also, via Poincar´e dual- ity, to the relative homology group H1(Ω,∂Ω; R). This is a finite-dimensional vector space, with one generator for each component of ∂Ω, and one relation for each com- ponent of Ω. Hence, its dimension is equal to the number of components of ∂Ωminus the number of components of Ω. Proposition 4.ThesubspaceDFG is the direct sum of two orthogonal subspaces: DFG = CG ⊕ HG . With Propositions 1 through 4 in hand, the Hodge decomposition of VF(Ω), VF(Ω) = FK ⊕ HK ⊕ CG ⊕ HG ⊕ GG, vector calculus and the topology of domains in 3-space, ii 5 follows immediately. The related expressions for the kernels of curl and div,andthe images of grad and curl are also fairly direct consequences, as shown in [12]. We pause to record some observations from [12] that contrast harmonic knots with harmonic gradients. Harmonic knots are smooth vector fields in Ω which are divergence-free, curl-free, and tangent to the boundary of Ω. A harmonic knot is completely determined by the values of its circulation around a set of curves in Ω that generate H1(Ω; R), or alternatively, by its fluxes through a set of surfaces that generate H2(Ω,∂Ω; R). Harmonic gradients, on the other hand, are smooth vector fields in Ω which are divergence-free, curl-free, and orthogonal to the boundary of Ω.
Recommended publications
  • Basic Properties of Filter Convergence Spaces
    Basic Properties of Filter Convergence Spaces Barbel¨ M. R. Stadlery, Peter F. Stadlery;z;∗ yInstitut fur¨ Theoretische Chemie, Universit¨at Wien, W¨ahringerstraße 17, A-1090 Wien, Austria zThe Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA ∗Address for corresponce Abstract. This technical report summarized facts from the basic theory of filter convergence spaces and gives detailed proofs for them. Many of the results collected here are well known for various types of spaces. We have made no attempt to find the original proofs. 1. Introduction Mathematical notions such as convergence, continuity, and separation are, at textbook level, usually associated with topological spaces. It is possible, however, to introduce them in a much more abstract way, based on axioms for convergence instead of neighborhood. This approach was explored in seminal work by Choquet [4], Hausdorff [12], Katˇetov [14], Kent [16], and others. Here we give a brief introduction to this line of reasoning. While the material is well known to specialists it does not seem to be easily accessible to non-topologists. In some cases we include proofs of elementary facts for two reasons: (i) The most basic facts are quoted without proofs in research papers, and (ii) the proofs may serve as examples to see the rather abstract formalism at work. 2. Sets and Filters Let X be a set, P(X) its power set, and H ⊆ P(X). The we define H∗ = fA ⊆ Xj(X n A) 2= Hg (1) H# = fA ⊆ Xj8Q 2 H : A \ Q =6 ;g The set systems H∗ and H# are called the conjugate and the grill of H, respectively.
    [Show full text]
  • Topology and Data
    BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 46, Number 2, April 2009, Pages 255–308 S 0273-0979(09)01249-X Article electronically published on January 29, 2009 TOPOLOGY AND DATA GUNNAR CARLSSON 1. Introduction An important feature of modern science and engineering is that data of various kinds is being produced at an unprecedented rate. This is so in part because of new experimental methods, and in part because of the increase in the availability of high powered computing technology. It is also clear that the nature of the data we are obtaining is significantly different. For example, it is now often the case that we are given data in the form of very long vectors, where all but a few of the coordinates turn out to be irrelevant to the questions of interest, and further that we don’t necessarily know which coordinates are the interesting ones. A related fact is that the data is often very high-dimensional, which severely restricts our ability to visualize it. The data obtained is also often much noisier than in the past and has more missing information (missing data). This is particularly so in the case of biological data, particularly high throughput data from microarray or other sources. Our ability to analyze this data, both in terms of quantity and the nature of the data, is clearly not keeping pace with the data being produced. In this paper, we will discuss how geometry and topology can be applied to make useful contributions to the analysis of various kinds of data.
    [Show full text]
  • A TEXTBOOK of TOPOLOGY Lltld
    SEIFERT AND THRELFALL: A TEXTBOOK OF TOPOLOGY lltld SEI FER T: 7'0PO 1.OG 1' 0 I.' 3- Dl M E N SI 0 N A I. FIRERED SPACES This is a volume in PURE AND APPLIED MATHEMATICS A Series of Monographs and Textbooks Editors: SAMUELEILENBERG AND HYMANBASS A list of recent titles in this series appears at the end of this volunie. SEIFERT AND THRELFALL: A TEXTBOOK OF TOPOLOGY H. SEIFERT and W. THRELFALL Translated by Michael A. Goldman und S E I FE R T: TOPOLOGY OF 3-DIMENSIONAL FIBERED SPACES H. SEIFERT Translated by Wolfgang Heil Edited by Joan S. Birman and Julian Eisner @ 1980 ACADEMIC PRESS A Subsidiary of Harcourr Brace Jovanovich, Publishers NEW YORK LONDON TORONTO SYDNEY SAN FRANCISCO COPYRIGHT@ 1980, BY ACADEMICPRESS, INC. ALL RIGHTS RESERVED. NO PART OF THIS PUBLICATION MAY BE REPRODUCED OR TRANSMITTED IN ANY FORM OR BY ANY MEANS, ELECTRONIC OR MECHANICAL, INCLUDING PHOTOCOPY, RECORDING, OR ANY INFORMATION STORAGE AND RETRIEVAL SYSTEM, WITHOUT PERMISSION IN WRITING FROM THE PUBLISHER. ACADEMIC PRESS, INC. 11 1 Fifth Avenue, New York. New York 10003 United Kingdom Edition published by ACADEMIC PRESS, INC. (LONDON) LTD. 24/28 Oval Road, London NWI 7DX Mit Genehmigung des Verlager B. G. Teubner, Stuttgart, veranstaltete, akin autorisierte englische Ubersetzung, der deutschen Originalausgdbe. Library of Congress Cataloging in Publication Data Seifert, Herbert, 1897- Seifert and Threlfall: A textbook of topology. Seifert: Topology of 3-dimensional fibered spaces. (Pure and applied mathematics, a series of mono- graphs and textbooks ; ) Translation of Lehrbuch der Topologic. Bibliography: p. Includes index. 1.
    [Show full text]
  • General Topology
    General Topology Tom Leinster 2014{15 Contents A Topological spaces2 A1 Review of metric spaces.......................2 A2 The definition of topological space.................8 A3 Metrics versus topologies....................... 13 A4 Continuous maps........................... 17 A5 When are two spaces homeomorphic?................ 22 A6 Topological properties........................ 26 A7 Bases................................. 28 A8 Closure and interior......................... 31 A9 Subspaces (new spaces from old, 1)................. 35 A10 Products (new spaces from old, 2)................. 39 A11 Quotients (new spaces from old, 3)................. 43 A12 Review of ChapterA......................... 48 B Compactness 51 B1 The definition of compactness.................... 51 B2 Closed bounded intervals are compact............... 55 B3 Compactness and subspaces..................... 56 B4 Compactness and products..................... 58 B5 The compact subsets of Rn ..................... 59 B6 Compactness and quotients (and images)............. 61 B7 Compact metric spaces........................ 64 C Connectedness 68 C1 The definition of connectedness................... 68 C2 Connected subsets of the real line.................. 72 C3 Path-connectedness.......................... 76 C4 Connected-components and path-components........... 80 1 Chapter A Topological spaces A1 Review of metric spaces For the lecture of Thursday, 18 September 2014 Almost everything in this section should have been covered in Honours Analysis, with the possible exception of some of the examples. For that reason, this lecture is longer than usual. Definition A1.1 Let X be a set. A metric on X is a function d: X × X ! [0; 1) with the following three properties: • d(x; y) = 0 () x = y, for x; y 2 X; • d(x; y) + d(y; z) ≥ d(x; z) for all x; y; z 2 X (triangle inequality); • d(x; y) = d(y; x) for all x; y 2 X (symmetry).
    [Show full text]
  • DEFINITIONS and THEOREMS in GENERAL TOPOLOGY 1. Basic
    DEFINITIONS AND THEOREMS IN GENERAL TOPOLOGY 1. Basic definitions. A topology on a set X is defined by a family O of subsets of X, the open sets of the topology, satisfying the axioms: (i) ; and X are in O; (ii) the intersection of finitely many sets in O is in O; (iii) arbitrary unions of sets in O are in O. Alternatively, a topology may be defined by the neighborhoods U(p) of an arbitrary point p 2 X, where p 2 U(p) and, in addition: (i) If U1;U2 are neighborhoods of p, there exists U3 neighborhood of p, such that U3 ⊂ U1 \ U2; (ii) If U is a neighborhood of p and q 2 U, there exists a neighborhood V of q so that V ⊂ U. A topology is Hausdorff if any distinct points p 6= q admit disjoint neigh- borhoods. This is almost always assumed. A set C ⊂ X is closed if its complement is open. The closure A¯ of a set A ⊂ X is the intersection of all closed sets containing X. A subset A ⊂ X is dense in X if A¯ = X. A point x 2 X is a cluster point of a subset A ⊂ X if any neighborhood of x contains a point of A distinct from x. If A0 denotes the set of cluster points, then A¯ = A [ A0: A map f : X ! Y of topological spaces is continuous at p 2 X if for any open neighborhood V ⊂ Y of f(p), there exists an open neighborhood U ⊂ X of p so that f(U) ⊂ V .
    [Show full text]
  • Combinatorial Topology
    Chapter 6 Basics of Combinatorial Topology 6.1 Simplicial and Polyhedral Complexes In order to study and manipulate complex shapes it is convenient to discretize these shapes and to view them as the union of simple building blocks glued together in a “clean fashion”. The building blocks should be simple geometric objects, for example, points, lines segments, triangles, tehrahedra and more generally simplices, or even convex polytopes. We will begin by using simplices as building blocks. The material presented in this chapter consists of the most basic notions of combinatorial topology, going back roughly to the 1900-1930 period and it is covered in nearly every algebraic topology book (certainly the “classics”). A classic text (slightly old fashion especially for the notation and terminology) is Alexandrov [1], Volume 1 and another more “modern” source is Munkres [30]. An excellent treatment from the point of view of computational geometry can be found is Boissonnat and Yvinec [8], especially Chapters 7 and 10. Another fascinating book covering a lot of the basics but devoted mostly to three-dimensional topology and geometry is Thurston [41]. Recall that a simplex is just the convex hull of a finite number of affinely independent points. We also need to define faces, the boundary, and the interior of a simplex. Definition 6.1 Let be any normed affine space, say = Em with its usual Euclidean norm. Given any n+1E affinely independentpoints a ,...,aE in , the n-simplex (or simplex) 0 n E σ defined by a0,...,an is the convex hull of the points a0,...,an,thatis,thesetofallconvex combinations λ a + + λ a ,whereλ + + λ =1andλ 0foralli,0 i n.
    [Show full text]
  • Papers on Topology Analysis Situs and Its Five Supplements
    Papers on Topology Analysis Situs and Its Five Supplements Henri Poincaré Translated by John Stillwell American Mathematical Society London Mathematical Society Papers on Topology Analysis Situs and Its Five Supplements https://doi.org/10.1090/hmath/037 • SOURCES Volume 37 Papers on Topology Analysis Situs and Its Five Supplements Henri Poincaré Translated by John Stillwell Providence, Rhode Island London, England Editorial Board American Mathematical Society London Mathematical Society Joseph W. Dauben Jeremy J. Gray Peter Duren June Barrow-Green Robin Hartshorne Tony Mann, Chair Karen Parshall, Chair Edmund Robertson 2000 Mathematics Subject Classification. Primary 01–XX, 55–XX, 57–XX. Front cover photograph courtesy of Laboratoire d’Histoire des Sciences et de Philosophie—Archives Henri Poincar´e(CNRS—Nancy-Universit´e), http://poincare.univ-nancy2.fr. For additional information and updates on this book, visit www.ams.org/bookpages/hmath-37 Library of Congress Cataloging-in-Publication Data Poincar´e, Henri, 1854–1912. Papers on topology : analysis situs and its five supplements / Henri Poincar´e ; translated by John Stillwell. p. cm. — (History of mathematics ; v. 37) Includes bibliographical references and index. ISBN 978-0-8218-5234-7 (alk. paper) 1. Algebraic topology. I. Title. QA612 .P65 2010 514.2—22 2010014958 Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy a chapter for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given. Republication, systematic copying, or multiple reproduction of any material in this publication is permitted only under license from the American Mathematical Society.
    [Show full text]
  • Topology of Differentiable Manifolds
    TOPOLOGY OF DIFFERENTIABLE MANIFOLDS D. MART´INEZ TORRES Contents 1. Introduction 1 1.1. Topology 2 1.2. Manifolds 3 2. More definitions and basic results 5 2.1. Submanifold vs. embedding 7 2.2. The tangent bundle of a Cr-manifold, r ≥ 1. 7 2.3. Transversality and submanifolds 9 2.4. Topology with Cr-functions. 9 2.5. Manifolds with boundary 13 2.6. 1-dimensional manifolds 16 3. Function spaces 19 4. Approximations 27 5. Sard's theorem and transversality 32 5.1. Transversality 35 6. Tubular neighborhoods, homotopies and isotopies 36 6.1. Homotopies, isotopies and linearizations 38 6.2. Linearizations 39 7. Degree, intersection number and Euler characteristic 42 7.1. Orientations 42 7.2. The degree of a map 43 7.3. Intersection number and Euler characteristic 45 7.4. Vector fields 46 8. Isotopies and gluings and Morse theory 47 8.1. Gluings 48 8.2. Morse functions 49 8.3. More on k-handles and smoothings 57 9. 2 and 3 dimensional compact oriented manifolds 60 9.1. Compact, oriented surfaces 60 9.2. Compact, oriented three manifolds 64 9.3. Heegard decompositions 64 9.4. Lens spaces 65 9.5. Higher genus 66 10. Exercises 66 References 67 1. Introduction Let us say a few words about the two key concepts in the title of the course, topology and differentiable manifolds. 1 2 D. MART´INEZ TORRES 1.1. Topology. It studies topological spaces and continuous maps among them, i.e. the category TOP with objects topological spaces and arrows continuous maps.
    [Show full text]
  • Algebraic Topology
    Algebraic Topology Len Evens Rob Thompson Northwestern University City University of New York Contents Chapter 1. Introduction 5 1. Introduction 5 2. Point Set Topology, Brief Review 7 Chapter 2. Homotopy and the Fundamental Group 11 1. Homotopy 11 2. The Fundamental Group 12 3. Homotopy Equivalence 18 4. Categories and Functors 20 5. The fundamental group of S1 22 6. Some Applications 25 Chapter 3. Quotient Spaces and Covering Spaces 33 1. The Quotient Topology 33 2. Covering Spaces 40 3. Action of the Fundamental Group on Covering Spaces 44 4. Existence of Coverings and the Covering Group 48 5. Covering Groups 56 Chapter 4. Group Theory and the Seifert{Van Kampen Theorem 59 1. Some Group Theory 59 2. The Seifert{Van Kampen Theorem 66 Chapter 5. Manifolds and Surfaces 73 1. Manifolds and Surfaces 73 2. Outline of the Proof of the Classification Theorem 80 3. Some Remarks about Higher Dimensional Manifolds 83 4. An Introduction to Knot Theory 84 Chapter 6. Singular Homology 91 1. Homology, Introduction 91 2. Singular Homology 94 3. Properties of Singular Homology 100 4. The Exact Homology Sequence{ the Jill Clayburgh Lemma 109 5. Excision and Applications 116 6. Proof of the Excision Axiom 120 3 4 CONTENTS 7. Relation between π1 and H1 126 8. The Mayer-Vietoris Sequence 128 9. Some Important Applications 131 Chapter 7. Simplicial Complexes 137 1. Simplicial Complexes 137 2. Abstract Simplicial Complexes 141 3. Homology of Simplicial Complexes 143 4. The Relation of Simplicial to Singular Homology 147 5. Some Algebra. The Tensor Product 152 6.
    [Show full text]
  • Geometry and Topology SHP Spring ’17
    Geometry and Topology SHP Spring '17 Henry Liu Last updated: April 29, 2017 Contents 0 About Mathematics 3 1 Surfaces 4 1.1 Examples of surfaces . 4 1.2 Equivalence of surfaces . 5 1.3 Distinguishing between surfaces . 7 1.4 Planar Models . 9 1.5 Cutting and Pasting . 11 1.6 Orientability . 14 1.7 Word representations . 16 1.8 Classification of surfaces . 19 2 Manifolds 20 2.1 Examples of manifolds . 21 2.2 Constructing new manifolds . 23 2.3 Distinguishing between manifolds . 25 2.4 Homotopy and homotopy groups . 27 2.5 Classification of manifolds . 30 3 Differential Topology 31 3.1 Topological degree . 33 3.2 Brouwer's fixed point theorem . 34 3.3 Application: Nash's equilibrium theorem . 36 3.4 Borsuk{Ulam theorem . 39 3.5 Poincar´e{Hopftheorem . 41 4 Geometry 44 4.1 Geodesics . 45 4.2 Gaussian curvature . 47 4.3 Gauss{Bonnet theorem . 51 1 5 Knot theory 54 5.1 Invariants and Reidemeister moves . 55 5.2 The Jones polynomial . 57 5.3 Chiral knots and crossing number . 60 A Appendix: Group theory 61 2 0 About Mathematics The majority of this course aims to introduce all of you to the many wonderfully interesting ideas underlying the study of geometry and topology in modern mathematics. But along the way, I want to also give you a sense of what \being a mathematician" and \doing mathematics" is really about. There are three main qualities that distinguish professional mathematicians: 1. the ability to correctly understand, make, and prove precise, unambiguous logical statements (often using a lot of jargon); 2.
    [Show full text]
  • On a New Convergence in Topological Spaces Received March 5, 2019; Accepted October 28, 2019
    Open Math. 2019; 17:1716–1723 Open Mathematics Research Article Xiao-jun Ruan and Xiao-quan Xu* On a new convergence in topological spaces https://doi.org/10.1515/math-2019-0123 Received March 5, 2019; accepted October 28, 2019 Abstract: In this paper, we introduce a new way-below relation in T0 topological spaces based on cuts and give the concepts of SI2-continuous spaces and weakly irreducible topologies. It is proved that a space is SI2-continuous if and only if its weakly irreducible topology is completely distributive under inclusion order. Finally, we introduce the concept of D-convergence and show that a space is SI2-continuous if and only if its D-convergence with respect to the topology τSI2 (X) is topological. In general, a space is SI-continuous if and only if its D-convergence with respect to the topology τSI(X) is topological. Keywords: s2-continuous poset, weakly irreducible topology, SI2-continuous space, D-convergence MSC: 06B35, 06B75, 54F05 1 Introduction Domain theory which arose from computer science and logic, started as an outgrowth of theories of order. Rapidly progress in this domain required many materials on topologies (see [1–3]). Conversely, it is well known that given a topological space one can also dene order structures (see [3–6]). At the 6th International Symposium in Domain Theory, J.D. Lawson emphasized the need to develop the core of domain theory directly in T0 topological spaces instead of posets. Moreover, it was pointed out that several results in domain theory can be lifted from the context of posets to T0 topological spaces (see [5, 6]).
    [Show full text]
  • Topology (H) Lecture 4 Lecturer: Zuoqin Wang Time: March 18, 2021
    Topology (H) Lecture 4 Lecturer: Zuoqin Wang Time: March 18, 2021 CONVERGENCE AND CONTINUITY 1. Convergence in topological spaces { Convergence. As we have mentioned, topological structure is created to extend the conceptions of convergence and continuous map to more general setting. It is easy to define the conception of convergence of a sequence in any topological spaces.Intuitively, xn ! x0 means \for any neighborhood N of x0, eventually the sequence xn's will enter and stay in N". Translating this into the language of open sets, we can write Definition 1.1 (convergence). Let (X; T ) be a topological space. Suppose xn 2 X and x0 2 X: We say xn converges to x0, denoted by xn ! x0, if for any neighborhood A of x0, there exists N > 0 such that xn 2 A for all n > N. Remark 1.2. According to the definition of neighborhood, it is easy to see that xn ! x0 in (X; T ) if and only if for any open set U containing x0, there exists N > 0 such that xn 2 U for all n > N. To get a better understanding, let's examine the convergence in simple spaces: Example 1.3. (Convergence in the metric topology) The convergence in metric topology is the same as the metric convergence: xn !x0 ()8">0, 9N >0 s.t. d(xn; x0)<" for all n>N. Example 1.4. (Convergence in the discrete topology) Since every open ball B(x; 1) = fxg, it is easy to see xn ! x0 if and only if there exists N such that xn = x0 for all n > N.
    [Show full text]