The Theory of Ends
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Pg**- Compact Spaces
International Journal of Mathematics Research. ISSN 0976-5840 Volume 9, Number 1 (2017), pp. 27-43 © International Research Publication House http://www.irphouse.com pg**- compact spaces Mrs. G. Priscilla Pacifica Assistant Professor, St.Mary’s College, Thoothukudi – 628001, Tamil Nadu, India. Dr. A. Punitha Tharani Associate Professor, St.Mary’s College, Thoothukudi –628001, Tamil Nadu, India. Abstract The concepts of pg**-compact, pg**-countably compact, sequentially pg**- compact, pg**-locally compact and pg**- paracompact are introduced, and several properties are investigated. Also the concept of pg**-compact modulo I and pg**-countably compact modulo I spaces are introduced and the relation between these concepts are discussed. Keywords: pg**-compact, pg**-countably compact, sequentially pg**- compact, pg**-locally compact, pg**- paracompact, pg**-compact modulo I, pg**-countably compact modulo I. 1. Introduction Levine [3] introduced the class of g-closed sets in 1970. Veerakumar [7] introduced g*- closed sets. P M Helen[5] introduced g**-closed sets. A.S.Mashhour, M.E Abd El. Monsef [4] introduced a new class of pre-open sets in 1982. Ideal topological spaces have been first introduced by K.Kuratowski [2] in 1930. In this paper we introduce 28 Mrs. G. Priscilla Pacifica and Dr. A. Punitha Tharani pg**-compact, pg**-countably compact, sequentially pg**-compact, pg**-locally compact, pg**-paracompact, pg**-compact modulo I and pg**-countably compact modulo I spaces and investigate their properties. 2. Preliminaries Throughout this paper(푋, 휏) and (푌, 휎) represent non-empty topological spaces of which no separation axioms are assumed unless otherwise stated. Definition 2.1 A subset 퐴 of a topological space(푋, 휏) is called a pre-open set [4] if 퐴 ⊆ 푖푛푡(푐푙(퐴) and a pre-closed set if 푐푙(푖푛푡(퐴)) ⊆ 퐴. -
Lectures on Quasi-Isometric Rigidity Michael Kapovich 1 Lectures on Quasi-Isometric Rigidity 3 Introduction: What Is Geometric Group Theory? 3 Lecture 1
Contents Lectures on quasi-isometric rigidity Michael Kapovich 1 Lectures on quasi-isometric rigidity 3 Introduction: What is Geometric Group Theory? 3 Lecture 1. Groups and Spaces 5 1. Cayley graphs and other metric spaces 5 2. Quasi-isometries 6 3. Virtual isomorphisms and QI rigidity problem 9 4. Examples and non-examples of QI rigidity 10 Lecture 2. Ultralimits and Morse Lemma 13 1. Ultralimits of sequences in topological spaces. 13 2. Ultralimits of sequences of metric spaces 14 3. Ultralimits and CAT(0) metric spaces 14 4. Asymptotic Cones 15 5. Quasi-isometries and asymptotic cones 15 6. Morse Lemma 16 Lecture 3. Boundary extension and quasi-conformal maps 19 1. Boundary extension of QI maps of hyperbolic spaces 19 2. Quasi-actions 20 3. Conical limit points of quasi-actions 21 4. Quasiconformality of the boundary extension 21 Lecture 4. Quasiconformal groups and Tukia's rigidity theorem 27 1. Quasiconformal groups 27 2. Invariant measurable conformal structure for qc groups 28 3. Proof of Tukia's theorem 29 4. QI rigidity for surface groups 31 Lecture 5. Appendix 33 1. Appendix 1: Hyperbolic space 33 2. Appendix 2: Least volume ellipsoids 35 3. Appendix 3: Different measures of quasiconformality 35 Bibliography 37 i Lectures on quasi-isometric rigidity Michael Kapovich IAS/Park City Mathematics Series Volume XX, XXXX Lectures on quasi-isometric rigidity Michael Kapovich Introduction: What is Geometric Group Theory? Historically (in the 19th century), groups appeared as automorphism groups of some structures: • Polynomials (field extensions) | Galois groups. • Vector spaces, possibly equipped with a bilinear form| Matrix groups. -
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). -
Topology and Robot Motion Planning
Topology and robot motion planning Mark Grant (University of Aberdeen) Maths Club talk 18th November 2015 Plan 1 What is Topology? Topological spaces Continuity Algebraic Topology 2 Topology and Robotics Configuration spaces End-effector maps Kinematics The motion planning problem What is Topology? What is Topology? It is the branch of mathematics concerned with properties of shapes which remain unchanged under continuous deformations. What is Topology? What is Topology? Like Geometry, but exact distances and angles don't matter. What is Topology? What is Topology? The name derives from Greek (τoπoζ´ means place and λoγoζ´ means study). Not to be confused with topography! What is Topology? Topological spaces Topological spaces Topological spaces arise naturally: I as configuration spaces of mechanical or physical systems; I as solution sets of differential equations; I in other branches of mathematics (eg, Geometry, Analysis or Algebra). M¨obiusstrip Torus Klein bottle What is Topology? Topological spaces Topological spaces A topological space consists of: I a set X of points; I a collection of subsets of X which are declared to be open. This collection must satisfy certain axioms (not given here). The collection of open sets is called a topology on X. It gives a notion of \nearness" of points. What is Topology? Topological spaces Topological spaces Usually the topology comes from a metric|a measure of distance between points. 2 For example, the plane R has a topology coming from the usual Euclidean metric. y y x x f(x; y) j x2 + y2 < 1g is open. f(x; y) j x2 + y2 ≤ 1g is not. -
Discrete Subspaces of Topological Spaces 1)
MATHEMATICS DISCRETE SUBSPACES OF TOPOLOGICAL SPACES 1) BY A. HAJNAL AND I. JUHASZ (Communicated by Prof. J. POPKEN at the meeting of October 29, 1966) §. l. Introduction Recently several papers appeared in the literature proving theorems of the following type. A topological space with "very many points" contains a discrete subspace with "many points". J. DE GROOT and B. A. EFIMOV proved in [2] and [4] that a Hausdorff space of power > exp exp exp m contains a discrete subspace of power >m. J. ISBELL proved in [3] a similar result for completely regular spaces. J. de Groot proved as well that for regular spaces R the assumption IRI > exp exp m is sufficient to imply the existence of a discrete subspace of potency > m. One of our main issues will be to improve this result and show that the same holds for Hausdorff spaces (see Theorems 2 and 3). Our Theorem 1 states that a Hausdorff space of density > exp m contains a discrete subspace of power >m. We give two different proofs for the main result already mentioned. The proof outlined for Theorem 3 is a slight improvement of de Groot's proof. The proof given for Theorem 2 is of purely combinatorial character. We make use of the ideas and some theorems of the so called set-theoretical partition calculus developed by P. ERDOS and R. RADO (see [5], [ 11 ]). Almost all the other results we prove are based on combinatorial theorems. For the convenience of the reader we always state these theorems in full detail. Our Theorem 4 states that if m is a strong limit cardinal which is the sum of No smaller cardinals, then every Hausdorff space of power m contains a discrete subspace of power m. -
Ends of Complexes Contents
Bruce Hughes Andrew Ranicki Vanderbilt University University of Edinburgh Ends of complexes Contents Introduction page ix Chapter summaries xxii Part one Topology at in¯nity 1 1 End spaces 1 2 Limits 13 3 Homology at in¯nity 29 4 Cellular homology 43 5 Homology of covers 56 6 Projective class and torsion 65 7 Forward tameness 75 8 Reverse tameness 92 9 Homotopy at in¯nity 97 10 Projective class at in¯nity 109 11 In¯nite torsion 122 12 Forward tameness is a homotopy pushout 137 Part two Topology over the real line 147 13 In¯nite cyclic covers 147 14 The mapping torus 168 15 Geometric ribbons and bands 173 16 Approximate ¯brations 187 17 Geometric wrapping up 197 18 Geometric relaxation 214 19 Homotopy theoretic twist glueing 222 20 Homotopy theoretic wrapping up and relaxation 244 Part three The algebraic theory 255 21 Polynomial extensions 255 22 Algebraic bands 263 23 Algebraic tameness 268 24 Relaxation techniques 288 25 Algebraic ribbons 300 26 Algebraic twist glueing 306 27 Wrapping up in algebraic K- and L-theory 318 vii viii Ends of complexes Part four Appendices 325 Appendix A. Locally ¯nite homology with local coe±cients 325 Appendix B. A brief history of end spaces 335 Appendix C. A brief history of wrapping up 338 References 341 Index 351 Introduction We take `complex' to mean both a CW (or simplicial) complex in topology and a chain complex in algebra. An `end' of a complex is a subcomplex with a particular type of in¯nite behaviour, involving non-compactness in topology and in¯nite generation in algebra. -
REVERSIBLE FILTERS 1. Introduction a Topological Space X Is Reversible
REVERSIBLE FILTERS ALAN DOW AND RODRIGO HERNANDEZ-GUTI´ ERREZ´ Abstract. A space is reversible if every continuous bijection of the space onto itself is a homeomorphism. In this paper we study the question of which countable spaces with a unique non-isolated point are reversible. By Stone duality, these spaces correspond to closed subsets in the Cech-Stoneˇ compact- ification of the natural numbers β!. From this, the following natural problem arises: given a space X that is embeddable in β!, is it possible to embed X in such a way that the associated filter of neighborhoods defines a reversible (or non-reversible) space? We give the solution to this problem in some cases. It is especially interesting whether the image of the required embedding is a weak P -set. 1. Introduction A topological space X is reversible if every time that f : X ! X is a continuous bijection, then f is a homeomorphism. This class of spaces was defined in [10], where some examples of reversible spaces were given. These include compact spaces, Euclidean spaces Rn (by the Brouwer invariance of domain theorem) and the space ! [ fpg, where p is an ultrafilter, as a subset of β!. This last example is of interest to us. Given a filter F ⊂ P(!), consider the space ξ(F) = ! [ fFg, where every point of ! is isolated and every neighborhood of F is of the form fFg [ A with A 2 F. Spaces of the form ξ(F) have been studied before, for example by Garc´ıa-Ferreira and Uzc´ategi([6] and [7]). -
16. Compactness
16. Compactness 1 Motivation While metrizability is the analyst's favourite topological property, compactness is surely the topologist's favourite topological property. Metric spaces have many nice properties, like being first countable, very separative, and so on, but compact spaces facilitate easy proofs. They allow you to do all the proofs you wished you could do, but never could. The definition of compactness, which we will see shortly, is quite innocuous looking. What compactness does for us is allow us to turn infinite collections of open sets into finite collections of open sets that do essentially the same thing. Compact spaces can be very large, as we will see in the next section, but in a strong sense every compact space acts like a finite space. This behaviour allows us to do a lot of hands-on, constructive proofs in compact spaces. For example, we can often take maxima and minima where in a non-compact space we would have to take suprema and infima. We will be able to intersect \all the open sets" in certain situations and end up with an open set, because finitely many open sets capture all the information in the whole collection. We will specifically prove an important result from analysis called the Heine-Borel theorem n that characterizes the compact subsets of R . This result is so fundamental to early analysis courses that it is often given as the definition of compactness in that context. 2 Basic definitions and examples Compactness is defined in terms of open covers, which we have talked about before in the context of bases but which we formally define here. -
A Primer on Homotopy Colimits
A PRIMER ON HOMOTOPY COLIMITS DANIEL DUGGER Contents 1. Introduction2 Part 1. Getting started 4 2. First examples4 3. Simplicial spaces9 4. Construction of homotopy colimits 16 5. Homotopy limits and some useful adjunctions 21 6. Changing the indexing category 25 7. A few examples 29 Part 2. A closer look 30 8. Brief review of model categories 31 9. The derived functor perspective 34 10. More on changing the indexing category 40 11. The two-sided bar construction 44 12. Function spaces and the two-sided cobar construction 49 Part 3. The homotopy theory of diagrams 52 13. Model structures on diagram categories 53 14. Cofibrant diagrams 60 15. Diagrams in the homotopy category 66 16. Homotopy coherent diagrams 69 Part 4. Other useful tools 76 17. Homology and cohomology of categories 77 18. Spectral sequences for holims and hocolims 85 19. Homotopy limits and colimits in other model categories 90 20. Various results concerning simplicial objects 94 Part 5. Examples 96 21. Homotopy initial and terminal functors 96 22. Homotopical decompositions of spaces 103 23. A survey of other applications 108 Appendix A. The simplicial cone construction 108 References 108 1 2 DANIEL DUGGER 1. Introduction This is an expository paper on homotopy colimits and homotopy limits. These are constructions which should arguably be in the toolkit of every modern algebraic topologist, yet there does not seem to be a place in the literature where a graduate student can easily read about them. Certainly there are many fine sources: [BK], [DwS], [H], [HV], [V1], [V2], [CS], [S], among others. -
Profunctors, Open Maps and Bisimulation
BRICS RS-04-22 Cattani & Winskel: Profunctors, Open Maps and Bisimulation BRICS Basic Research in Computer Science Profunctors, Open Maps and Bisimulation Gian Luca Cattani Glynn Winskel BRICS Report Series RS-04-22 ISSN 0909-0878 October 2004 Copyright c 2004, Gian Luca Cattani & Glynn Winskel. BRICS, Department of Computer Science University of Aarhus. All rights reserved. Reproduction of all or part of this work is permitted for educational or research use on condition that this copyright notice is included in any copy. See back inner page for a list of recent BRICS Report Series publications. Copies may be obtained by contacting: BRICS Department of Computer Science University of Aarhus Ny Munkegade, building 540 DK–8000 Aarhus C Denmark Telephone: +45 8942 3360 Telefax: +45 8942 3255 Internet: [email protected] BRICS publications are in general accessible through the World Wide Web and anonymous FTP through these URLs: http://www.brics.dk ftp://ftp.brics.dk This document in subdirectory RS/04/22/ Profunctors, Open Maps and Bisimulation∗ Gian Luca Cattani DS Data Systems S.p.A., Via Ugozzolo 121/A, I-43100 Parma, Italy. Email: [email protected]. Glynn Winskel University of Cambridge Computer Laboratory, Cambridge CB3 0FD, England. Email: [email protected]. October 2004 Abstract This paper studies fundamental connections between profunctors (i.e., dis- tributors, or bimodules), open maps and bisimulation. In particular, it proves that a colimit preserving functor between presheaf categories (corresponding to a profunctor) preserves open maps and open map bisimulation. Consequently, the composition of profunctors preserves open maps as 2-cells. -
1. Let X Be a Non-Empty Set. Let T1 and T2 Be Two Topologies on X Such That T1 Is
A 1 1. Let X be a non-empty set. Let T1 and T2 be two topologies on X such that T1 is strictly contained in T2. If I : (X,T1) o(X, T2) is identity map, then: (1) both I and I–1 are continuous (2) both I and I–1 are not continuous (3) I is continuous but I–1 is not continuous (4) I is not continuous but I–1 is continuous 2. The connected subset of real line with usual topology are --: (1) all intervals (2) only bounded intervals (3) only compact intervals (4) only semi-infinite intervals 3. Topological space X is locally path connected space- (1) if X is locally connected at each xX (2) if X is locally connected at some xX (3) if X is locally connected at each xX (4) None of these 4. The topology on real line R generated by left-open right closed intervals (a,b) is: (1) strictly coarser then usual topology (2) strictly finer than usual topology (3) not comparable with usual topology (4) same as the usual topology 60581/A P.T.O. A 2 5. Which of the following is not first countable? (1) discrete space (2) indiscrete space (3) cofinite topological space on R (4) metric space 6. Let X = {a,b,c} and T1= {I, {a}, {b,c}, X} X* = {x, y, z} and T2 = {I, {x}, {y,z}, X*} Then which of the following mapping from X to X* are continuous? (1) f(a) = x, f(b) = y, f(c) = z (2) g(a) = x, g(b) = y, g(c) = z (3) h(a) = z, h(b) = x, h(c) = y (4) both (1) and (2) 7. -
Discrete Topology and Geometry Algorithms for Quantitative Human Airway Trees Analysis Based on Computed Tomography Images Michal Postolski
Discrete topology and geometry algorithms for quantitative human airway trees analysis based on computed tomography images Michal Postolski To cite this version: Michal Postolski. Discrete topology and geometry algorithms for quantitative human airway trees analysis based on computed tomography images. Other. Université Paris-Est, 2013. English. NNT : 2013PEST1094. pastel-00977514 HAL Id: pastel-00977514 https://pastel.archives-ouvertes.fr/pastel-00977514 Submitted on 11 Apr 2014 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. PARIS-EST UNIVERSITY DOCTORAL SCHOOL MSTIC A thesis submitted in partial fulfillment for the degree of Doctor of Philosophy in Computer Science Presented by Michal Postolski Supervised by Michel Couprie and Dominik Sankowski Discrete Topology and Geometry Algorithms for Quantitative Human Airway Trees Analysis Based on Computed Tomography Images December 18, 2013 Committee in charge: Piotr Kulczycki (reviewer) Nicolas Normand (reviewer) Nicolas Passat (reviewer) Jan Sikora (reviewer) Michel Couprie Yukiko Kenmochi Andrzej Napieralski Dominik Sankowski To my brilliant wife. ii Title: Discrete Topology and Geometry Algorithms for Quantitative Human Airway Trees Analysis Based on Computed Tomography Images. Abstract: Computed tomography is a very useful technique which allow non-invasive diagnosis in many applications for example is used with success in industry and medicine.