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COMP 761: Lecture 9 – Graph Theory I
COMP 761: Lecture 9 – Graph Theory I David Rolnick September 23, 2020 David Rolnick COMP 761: Graph Theory I Sep 23, 2020 1 / 27 Problem In Königsberg (now called Kaliningrad) there are some bridges (shown below). Is it possible to cross over all of them in some order, without crossing any bridge more than once? (Please don’t post your ideas in the chat just yet, we’ll discuss the problem soon in class.) David Rolnick COMP 761: Graph Theory I Sep 23, 2020 2 / 27 Problem Set 2 will be due on Oct. 9 Vincent’s optional list of practice problems available soon on Slack (we can give feedback on your solutions, but they will not count towards a grade) Course Announcements David Rolnick COMP 761: Graph Theory I Sep 23, 2020 3 / 27 Vincent’s optional list of practice problems available soon on Slack (we can give feedback on your solutions, but they will not count towards a grade) Course Announcements Problem Set 2 will be due on Oct. 9 David Rolnick COMP 761: Graph Theory I Sep 23, 2020 3 / 27 Course Announcements Problem Set 2 will be due on Oct. 9 Vincent’s optional list of practice problems available soon on Slack (we can give feedback on your solutions, but they will not count towards a grade) David Rolnick COMP 761: Graph Theory I Sep 23, 2020 3 / 27 A graph G is defined by a set V of vertices and a set E of edges, where the edges are (unordered) pairs of vertices fv; wg. -
MTH 304: General Topology Semester 2, 2017-2018
MTH 304: General Topology Semester 2, 2017-2018 Dr. Prahlad Vaidyanathan Contents I. Continuous Functions3 1. First Definitions................................3 2. Open Sets...................................4 3. Continuity by Open Sets...........................6 II. Topological Spaces8 1. Definition and Examples...........................8 2. Metric Spaces................................. 11 3. Basis for a topology.............................. 16 4. The Product Topology on X × Y ...................... 18 Q 5. The Product Topology on Xα ....................... 20 6. Closed Sets.................................. 22 7. Continuous Functions............................. 27 8. The Quotient Topology............................ 30 III.Properties of Topological Spaces 36 1. The Hausdorff property............................ 36 2. Connectedness................................. 37 3. Path Connectedness............................. 41 4. Local Connectedness............................. 44 5. Compactness................................. 46 6. Compact Subsets of Rn ............................ 50 7. Continuous Functions on Compact Sets................... 52 8. Compactness in Metric Spaces........................ 56 9. Local Compactness.............................. 59 IV.Separation Axioms 62 1. Regular Spaces................................ 62 2. Normal Spaces................................ 64 3. Tietze's extension Theorem......................... 67 4. Urysohn Metrization Theorem........................ 71 5. Imbedding of Manifolds.......................... -
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). -
Clay Mathematics Institute 2005 James A
Contents Clay Mathematics Institute 2005 James A. Carlson Letter from the President 2 The Prize Problems The Millennium Prize Problems 3 Recognizing Achievement 2005 Clay Research Awards 4 CMI Researchers Summary of 2005 6 Workshops & Conferences CMI Programs & Research Activities Student Programs Collected Works James Arthur Archive 9 Raoul Bott Library CMI Profile Interview with Research Fellow 10 Maria Chudnovsky Feature Article Can Biology Lead to New Theorems? 13 by Bernd Sturmfels CMI Summer Schools Summary 14 Ricci Flow, 3–Manifolds, and Geometry 15 at MSRI Program Overview CMI Senior Scholars Program 17 Institute News Euclid and His Heritage Meeting 18 Appointments & Honors 20 CMI Publications Selected Articles by Research Fellows 27 Books & Videos 28 About CMI Profile of Bow Street Staff 30 CMI Activities 2006 Institute Calendar 32 2005 Euclid: www.claymath.org/euclid James Arthur Collected Works: www.claymath.org/cw/arthur Hanoi Institute of Mathematics: www.math.ac.vn Ramanujan Society: www.ramanujanmathsociety.org $.* $MBZ.BUIFNBUJDT*OTUJUVUF ".4 "NFSJDBO.BUIFNBUJDBM4PDJFUZ In addition to major,0O"VHVTU BUUIFTFDPOE*OUFSOBUJPOBM$POHSFTTPG.BUIFNBUJDJBOT ongoing activities such as JO1BSJT %BWJE)JMCFSUEFMJWFSFEIJTGBNPVTMFDUVSFJOXIJDIIFEFTDSJCFE the summer schools,UXFOUZUISFFQSPCMFNTUIBUXFSFUPQMBZBOJOnVFOUJBMSPMFJONBUIFNBUJDBM the Institute undertakes a 5IF.JMMFOOJVN1SJ[F1SPCMFNT SFTFBSDI"DFOUVSZMBUFS PO.BZ BUBNFFUJOHBUUIF$PMMÒHFEF number of smaller'SBODF UIF$MBZ.BUIFNBUJDT*OTUJUVUF $.* BOOPVODFEUIFDSFBUJPOPGB special projects -
HAMILTONICITY in CAYLEY GRAPHS and DIGRAPHS of FINITE ABELIAN GROUPS. Contents 1. Introduction. 1 2. Graph Theory: Introductory
HAMILTONICITY IN CAYLEY GRAPHS AND DIGRAPHS OF FINITE ABELIAN GROUPS. MARY STELOW Abstract. Cayley graphs and digraphs are introduced, and their importance and utility in group theory is formally shown. Several results are then pre- sented: firstly, it is shown that if G is an abelian group, then G has a Cayley digraph with a Hamiltonian cycle. It is then proven that every Cayley di- graph of a Dedekind group has a Hamiltonian path. Finally, we show that all Cayley graphs of Abelian groups have Hamiltonian cycles. Further results, applications, and significance of the study of Hamiltonicity of Cayley graphs and digraphs are then discussed. Contents 1. Introduction. 1 2. Graph Theory: Introductory Definitions. 2 3. Cayley Graphs and Digraphs. 2 4. Hamiltonian Cycles in Cayley Digraphs of Finite Abelian Groups 5 5. Hamiltonian Paths in Cayley Digraphs of Dedekind Groups. 7 6. Cayley Graphs of Finite Abelian Groups are Guaranteed a Hamiltonian Cycle. 8 7. Conclusion; Further Applications and Research. 9 8. Acknowledgements. 9 References 10 1. Introduction. The topic of Cayley digraphs and graphs exhibits an interesting and important intersection between the world of groups, group theory, and abstract algebra and the world of graph theory and combinatorics. In this paper, I aim to highlight this intersection and to introduce an area in the field for which many basic problems re- main open.The theorems presented are taken from various discrete math journals. Here, these theorems are analyzed and given lengthier treatment in order to be more accessible to those without much background in group or graph theory. -
The Monadic Second-Order Logic of Graphs Xvi: Canonical Graph Decompositions
Logical Methods in Computer Science Vol. 2 (2:2) 2006, pp. 1–46 Submitted Jun. 24, 2005 www.lmcs-online.org Published Mar. 23, 2006 THE MONADIC SECOND-ORDER LOGIC OF GRAPHS XVI: CANONICAL GRAPH DECOMPOSITIONS BRUNO COURCELLE LaBRI, Bordeaux 1 University, 33405 Talence, France e-mail address: [email protected] Abstract. This article establishes that the split decomposition of graphs introduced by Cunnigham, is definable in Monadic Second-Order Logic.This result is actually an instance of a more general result covering canonical graph decompositions like the modular decom- position and the Tutte decomposition of 2-connected graphs into 3-connected components. As an application, we prove that the set of graphs having the same cycle matroid as a given 2-connected graph can be defined from this graph by Monadic Second-Order formulas. 1. Introduction Hierarchical graph decompositions are useful for the construction of efficient algorithms, and also because they give structural descriptions of the considered graphs. Cunningham and Edmonds have proposed in [18] a general framework for defining decompositions of graphs, hypergraphs and matroids. This framework covers many types of decompositions. Of particular interest is the split decomposition of directed and undirected graphs defined by Cunningham in [17]. A hierarchical decomposition of a certain type is canonical if, up to technical details like vertex labellings, there is a unique decomposition of a given graph (or hypergraph, or matroid) of this type. To take well-known examples concerning graphs, the modular decom- position is canonical, whereas, except in particular cases, there is no useful canonical notion of tree-decomposition of minimal tree-width. -
Tree-Decomposition Graph Minor Theory and Algorithmic Implications
DIPLOMARBEIT Tree-Decomposition Graph Minor Theory and Algorithmic Implications Ausgeführt am Institut für Diskrete Mathematik und Geometrie der Technischen Universität Wien unter Anleitung von Univ.Prof. Dipl.-Ing. Dr.techn. Michael Drmota durch Miriam Heinz, B.Sc. Matrikelnummer: 0625661 Baumgartenstraße 53 1140 Wien Datum Unterschrift Preface The focus of this thesis is the concept of tree-decomposition. A tree-decomposition of a graph G is a representation of G in a tree-like structure. From this structure it is possible to deduce certain connectivity properties of G. Such information can be used to construct efficient algorithms to solve problems on G. Sometimes problems which are NP-hard in general are solvable in polynomial or even linear time when restricted to trees. Employing the tree-like structure of tree-decompositions these algorithms for trees can be adapted to graphs of bounded tree-width. This results in many important algorithmic applications of tree-decomposition. The concept of tree-decomposition also proves to be useful in the study of fundamental questions in graph theory. It was used extensively by Robertson and Seymour in their seminal work on Wagner’s conjecture. Their Graph Minors series of papers spans more than 500 pages and results in a proof of the graph minor theorem, settling Wagner’s conjecture in 2004. However, it is not only the proof of this deep and powerful theorem which merits mention. Also the concepts and tools developed for the proof have had a major impact on the field of graph theory. Tree-decomposition is one of these spin-offs. Therefore, we will study both its use in the context of graph minor theory and its several algorithmic implications. -
An Extensive on Graph English Language Bibliograp Theory and Its A
NATIONAL AERONAUTICS AND SPACE AD Technical Report 32-7473 An Extensive English Language Bibliograp on Graph Theory and Its A Narsingh De0 JET PROPULS N LABORATORY CALIFORNIA INSTITUTE OF TECHNOLOGY PASADENA, CALIFORNIA October 15,1969 NATIONAL AERONAUTICS AND SPACE ADMINISTRATION Technical Report 32-7473 An Extensive English Language Bibliography on Graph Theory and Its Applications Narsingh Deo JET PROPULSION LABORATORY CALIFORNIA INSTITUTE OF TECHNOLOGY PASADENA, CALIFORNIA October 15, 1969 Prepared Under Contract No. NAS 7-100 National Aeronautics and Space Administration Preface The work described in this report was performed under the cognizance of the Guidance and Control Division of the Jet Propulsion Laboratory. The author delivered a series of 16 lectures on Graph Theory and Its Applica- tion at Jet Propulsion Laboratory’s Applied Mathematics Seminar during Jan.- Mar., 1968. Since that time he has received numerous requests-from his col- leagues at JPL, from students and faculty at Gal Tech, and from outside-for bibliographies in theory and applications of graphs. This technical report is compiled chiefly to meet this need. As far as the author knows, the most extensive existing bibliography on the theory of linear graphs was compiled by A. A. Zykov in early 1963 for the sym- posium held at Smoleniee, Czechoslovakia in June 1963. This bibliography was an extension of an earlier bibliography by J. W. Moon and L. Moser. Although Zykov’s bibliography has served as an excellent source of informa- tion for research workers and students, it has its shortcomings. It is 6 years old and hence is in obvious need of updating. -
A Separator Theorem for Graphs with an Excluded Minor and Its
A Separator Theorem for Graphs with an Excluded Minor and its Applications (Extended Abstract) Noga Alon∗ Paul Seymoury Robin Thomasz Abstract Let G be an n-vertex graph with nonnegative weights whose sum is 1 assigned to its vertices, and with no minor isomorphic to a given h-vertex graph H. We prove that there is a set X of no more than h3=2n1=2 vertices of G whose deletion creates a graph in which the total weight of every connected component is at most 1=2. This extends significantly a well-known theorem of Lipton and Tarjan for planar graphs. We exhibit an algorithm which finds, given an n-vertex graph G with weights as above and an h-vertex graph H, either such a set X or a minor of G isomorphic to H. The algorithm runs in time O(h1=2n1=2m), where m is the number of edges of G plus the number of its vertices. Our results supply extensions of the many known applications of the Lipton-Tarjan separator theorem from the class of planar graphs (or that of graphs with bounded genus) to any class of graphs with an excluded minor. For example, it follows that for any fixed graph H , given a graph G with n vertices and with no H-minor one can approximate the size of the maximum independent set of G up to a relative error of 1=plog n in polynomial time, find that size exactly and find the chromatic number of G in time 2O(pn) and solve any sparse system of n linear equations in n unknowns whose sparsity structure corresponds to G in time O(n3=2). -
Pursuit on Graphs Contents 1
Pursuit on Graphs Contents 1. Introduction 2 1.1. The game 2 1.2. Examples 2 2. Lower bounds 4 2.1. A first idea 4 2.2. Aigner and Fromme 4 2.3. Easy generalisations of Aigner and Fromme 6 2.4. Graphs of larger girth 8 3. Upper Bounds 11 3.1. Main conjectures 11 3.2. The first non-trivial upper bound 12 3.3. An upper bound for graphs of large girth 14 3.4. A general upper bound 16 4. Random Graphs 19 4.1. Constant p 19 4.2. Variable p 20 4.3. The Zigzag Theorem 21 5. Cops and Fast Robber 27 5.1. Finding the correct bound 27 5.2. The construction 29 6. Conclusion 31 References 31 1 1. Introduction 1.1. The game. The aim of this essay is to give an overview of some topics concerning a game called Cops and Robbers, which was introduced independently by Nowakowski and Winkler [3] and Quillot [4]. Given a graph G, the game goes as follows. We have two players, one player controls some number k of cops and the other player controls the robber. First, the cops occupy some vertices of the graph, where more than one cop may occupy the same vertex. Then the robber, being fully aware of the cops' choices, chooses a vertex for himself 1. Afterwards the cops and the robber move in alternate rounds, with cops going first. At each step any cop or robber is allowed to move along an edge of G or remain stationary. -
General Topology. Part 1: First Concepts
A Review of General Topology. Part 1: First Concepts Wayne Aitken∗ March 2021 version This document gives the first definitions and results of general topology. It is the first document of a series which reviews the basics of general topology. Other topics such as Hausdorff spaces, metric spaces, connectedness, and compactness will be covered in further documents. General topology can be viewed as the mathematical study of continuity, con- nectedness, and related phenomena in a general setting. Such ideas first arise in particular settings such as the real line, Euclidean spaces (including infinite di- mensional spaces), and function spaces. An initial goal of general topology is to find an abstract setting that allows us to formulate results concerning continuity and related concepts (convergence, compactness, connectedness, and so forth) that arise in these more concrete settings. The basic definitions of general topology are due to Fr`echet and Hausdorff in the early 1900's. General topology is sometimes called point-set topology since it builds directly on set theory. This is in contrast to algebraic topology, which brings in ideas from abstract algebra to define algebraic invariants of spaces, and differential topology which considers topological spaces with additional structure allowing for the notion of differentiability (basic general topology only generalizes the notion of continuous functions, not the notion of dif- ferentiable function). We approach general topology here as a common foundation for many subjects in mathematics: more advanced topology, of course, including advanced point-set topology, differential topology, and algebraic topology; but also any part of analysis, differential geometry, Lie theory, and even algebraic and arith- metic geometry. -
Arxiv:1908.10457V1 [Math.CO] 27 Aug 2019
CLIQUE IMMERSION IN GRAPH PRODUCTS KAREN L. COLLINS, MEGAN E. HEENEHAN, AND JESSICA MCDONALD Abstract. Let G; H be graphs and G ∗ H represent a particular graph product of G and H. We define im(G) to be the largest t such that G has a Kt-immersion and ask: given im(G) = t and im(H) = r, how large is im(G ∗ H)? Best possible lower bounds are provided when ∗ is the Cartesian or lexicographic product, and a conjecture is offered for each of the direct and strong products, along with some partial results. 1. Introduction In this paper every graph is assumed to be simple. Formally, a pair of adjacent edges uv and vw in a graph are split off (or lifted) from their common vertex v by deleting the edges uv and vw, and adding the edge uw. Given graphs G; G0, we say that G has a G0-immersion if a graph isomorphic to G0 can be obtained from a subgraph of G by splitting off pairs of edges, and removing isolated vertices. We define the immersion number of a graph G, denoted im(G), to be the largest value t for which G has an Kt-immersion. We call the t vertices corresponding to those in the Kt-immersion the terminals of the immersion. Immersions have enjoyed increased interest in the last number of years (see eg. [4, 5, 6, 7, 8, 12, 16, 17, 18]). A major factor in this was Robertson and Seymour's [15] proof that graphs are well-quasi-ordered by immersion, published as part of their celebrated graph minors project (where they show that graphs are well-quasi-ordered by minors).