Fixing Numbers of Graphs and Groups Courtney Gibbons Hamilton College, [email protected]
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Mathematicians Fleeing from Nazi Germany
Mathematicians Fleeing from Nazi Germany Mathematicians Fleeing from Nazi Germany Individual Fates and Global Impact Reinhard Siegmund-Schultze princeton university press princeton and oxford Copyright 2009 © by Princeton University Press Published by Princeton University Press, 41 William Street, Princeton, New Jersey 08540 In the United Kingdom: Princeton University Press, 6 Oxford Street, Woodstock, Oxfordshire OX20 1TW All Rights Reserved Library of Congress Cataloging-in-Publication Data Siegmund-Schultze, R. (Reinhard) Mathematicians fleeing from Nazi Germany: individual fates and global impact / Reinhard Siegmund-Schultze. p. cm. Includes bibliographical references and index. ISBN 978-0-691-12593-0 (cloth) — ISBN 978-0-691-14041-4 (pbk.) 1. Mathematicians—Germany—History—20th century. 2. Mathematicians— United States—History—20th century. 3. Mathematicians—Germany—Biography. 4. Mathematicians—United States—Biography. 5. World War, 1939–1945— Refuges—Germany. 6. Germany—Emigration and immigration—History—1933–1945. 7. Germans—United States—History—20th century. 8. Immigrants—United States—History—20th century. 9. Mathematics—Germany—History—20th century. 10. Mathematics—United States—History—20th century. I. Title. QA27.G4S53 2008 510.09'04—dc22 2008048855 British Library Cataloging-in-Publication Data is available This book has been composed in Sabon Printed on acid-free paper. ∞ press.princeton.edu Printed in the United States of America 10 987654321 Contents List of Figures and Tables xiii Preface xvii Chapter 1 The Terms “German-Speaking Mathematician,” “Forced,” and“Voluntary Emigration” 1 Chapter 2 The Notion of “Mathematician” Plus Quantitative Figures on Persecution 13 Chapter 3 Early Emigration 30 3.1. The Push-Factor 32 3.2. The Pull-Factor 36 3.D. -
Arxiv:1907.00626V1 [Math.RT] 1 Jul 2019 Ru Srltdt Hto H Rp.Nml,W Prove: We Namely, 1.1
REPRESENTABILITY OF PERMUTATION REPRESENTATIONS ON COALGEBRAS AND THE ISOMORPHISM PROBLEM CRISTINA COSTOYA, DAVID MENDEZ,´ AND ANTONIO VIRUEL Abstract. Let G be a group and let ρ: G → Sym(V ) be a permutation representation of G on a set V . We prove that there is a faithful G-coalgebra C such that G arises as the image of the restriction of Aut(C) to G(C), the set of grouplike elements of C. Furthermore, we show that V can be regarded as a subset of G(C) invariant through the G-action, and that the composition of the inclusion G ֒→ Aut(C) with the restriction Aut(C) → Sym(V ) is precisely ρ. We use these results to prove that isomorphism classes of certain families of groups can be distinguished through the coalgebras on which they act faithfully. 1. Introduction Given X an object in a category C, the study of its automorphism group, Aut(X), is a difficult task. In fact, even deciding which groups arise as the automorphism groups of objects in C is far from trivial, see [13]. Nonetheless, it is also rewarding, as it can be expected that distinguished objects have distinguished automorphism groups, which in turn may give valuable information regarding the object X. Not only that, but if we know the automorphism groups of enough objects in C, we can also draw conclusions regarding the category itself. One clear example of this comes from representation theory, as the automorphism groups of the objects of a category tell us a lot about which groups may act on which objects. -
Graph Automorphism Groups
Graph Automorphism Groups Robert A. Beeler, Ph.D. East Tennessee State University February 23, 2018 Robert A. Beeler, Ph.D. (East Tennessee State University)Graph Automorphism Groups February 23, 2018 1 / 1 What is a graph? A graph G =(V , E) is a set of vertices, V , together with as set of edges, E. For our purposes, each edge will be an unordered pair of distinct vertices. a e b d c V (G)= {a, b, c, d, e} E(G)= {ab, ae, bc, be, cd, de} Robert A. Beeler, Ph.D. (East Tennessee State University)Graph Automorphism Groups February 23, 2018 2 / 1 Graph Automorphisms A graph automorphism is simply an isomorphism from a graph to itself. In other words, an automorphism on a graph G is a bijection φ : V (G) → V (G) such that uv ∈ E(G) if and only if φ(u)φ(v) ∈ E(G). Note that graph automorphisms preserve adjacency. In layman terms, a graph automorphism is a symmetry of the graph. Robert A. Beeler, Ph.D. (East Tennessee State University)Graph Automorphism Groups February 23, 2018 3 / 1 An Example Consider the following graph: a d b c Robert A. Beeler, Ph.D. (East Tennessee State University)Graph Automorphism Groups February 23, 2018 4 / 1 An Example (Part 2) One automorphism simply maps every vertex to itself. This is the identity automorphism. a a d b d b c 7→ c e =(a)(b)(c)(d) Robert A. Beeler, Ph.D. (East Tennessee State University)Graph Automorphism Groups February 23, 2018 5 / 1 An Example (Part 3) One automorphism switches vertices a and c. -
An Introduction to Algebraic Graph Theory
An Introduction to Algebraic Graph Theory Cesar O. Aguilar Department of Mathematics State University of New York at Geneseo Last Update: March 25, 2021 Contents 1 Graphs 1 1.1 What is a graph? ......................... 1 1.1.1 Exercises .......................... 3 1.2 The rudiments of graph theory .................. 4 1.2.1 Exercises .......................... 10 1.3 Permutations ........................... 13 1.3.1 Exercises .......................... 19 1.4 Graph isomorphisms ....................... 21 1.4.1 Exercises .......................... 30 1.5 Special graphs and graph operations .............. 32 1.5.1 Exercises .......................... 37 1.6 Trees ................................ 41 1.6.1 Exercises .......................... 45 2 The Adjacency Matrix 47 2.1 The Adjacency Matrix ...................... 48 2.1.1 Exercises .......................... 53 2.2 The coefficients and roots of a polynomial ........... 55 2.2.1 Exercises .......................... 62 2.3 The characteristic polynomial and spectrum of a graph .... 63 2.3.1 Exercises .......................... 70 2.4 Cospectral graphs ......................... 73 2.4.1 Exercises .......................... 84 3 2.5 Bipartite Graphs ......................... 84 3 Graph Colorings 89 3.1 The basics ............................. 89 3.2 Bounds on the chromatic number ................ 91 3.3 The Chromatic Polynomial .................... 98 3.3.1 Exercises ..........................108 4 Laplacian Matrices 111 4.1 The Laplacian and Signless Laplacian Matrices .........111 4.1.1 -
Discriminating Power of Centrality Measures (Working Paper)
Discriminating Power of Centrality Measures (working paper) M. Puck Rombach∗ Mason A. Porterz July 27, 2018 Abstract The calculation of centrality measures is common practice in the study of networks, as they attempt to quantify the importance of individual vertices, edges, or other components. Different centralities attempt to measure importance in different ways. In this paper, we examine a conjecture posed by E. Estrada regarding the ability of several measures to distinguish the vertices of networks. Estrada conjectured [9, 12] that if all vertices of a graph have the same subgraph centrality, then all vertices must also have the same degree, eigenvector, closeness, and betweenness centralities. We provide a counterexample for the latter two centrality measures and propose a revised conjecture. 1 Introduction Many problems in the study of networks focus on flows along the edges of a network [20]. Although flows such as the transportation of physical objects or the spread of disease are conservative, the flow of information tends to diminish as it moves through a network, and the influence of one vertex on another decreases with increasing network distance between them [17]. Such considerations have sparked an interest in network communicability, in which a arXiv:1305.3146v1 [cs.SI] 14 May 2013 perturbation of one vertex is felt by the other vertices with differing intensities [10]. These intensities depend on all paths between a pair of vertices, though longer paths have smaller influence. This idea is expressed in a general communicability function 1 n X X k ci = ck(A )ij ; (1) k=0 j=1 ∗Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, [email protected] yOxford Centre for Industrial and Applied Mathematics, Mathematical Institute and CABDyN Complex- ity Centre, University of Oxford, [email protected] 1 where A is the adjacency matrix|whose entries are 1 if vertices i and j are connected to each other and 0 if they are not|and n is the total number of vertices in the network. -
Package 'Igraph'
Package ‘igraph’ February 28, 2013 Version 0.6.5-1 Date 2013-02-27 Title Network analysis and visualization Author See AUTHORS file. Maintainer Gabor Csardi <[email protected]> Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization,centrality indices and much more. Depends stats Imports Matrix Suggests igraphdata, stats4, rgl, tcltk, graph, Matrix, ape, XML,jpeg, png License GPL (>= 2) URL http://igraph.sourceforge.net SystemRequirements gmp, libxml2 NeedsCompilation yes Repository CRAN Date/Publication 2013-02-28 07:57:40 R topics documented: igraph-package . .5 aging.prefatt.game . .8 alpha.centrality . 10 arpack . 11 articulation.points . 15 as.directed . 16 1 2 R topics documented: as.igraph . 18 assortativity . 19 attributes . 21 autocurve.edges . 23 barabasi.game . 24 betweenness . 26 biconnected.components . 28 bipartite.mapping . 29 bipartite.projection . 31 bonpow . 32 canonical.permutation . 34 centralization . 36 cliques . 39 closeness . 40 clusters . 42 cocitation . 43 cohesive.blocks . 44 Combining attributes . 48 communities . 51 community.to.membership . 55 compare.communities . 56 components . 57 constraint . 58 contract.vertices . 59 conversion . 60 conversion between igraph and graphNEL graphs . 62 convex.hull . 63 decompose.graph . 64 degree . 65 degree.sequence.game . 66 dendPlot . 67 dendPlot.communities . 68 dendPlot.igraphHRG . 70 diameter . 72 dominator.tree . 73 Drawing graphs . 74 dyad.census . 80 eccentricity . 81 edge.betweenness.community . 82 edge.connectivity . 84 erdos.renyi.game . 86 evcent . 87 fastgreedy.community . 89 forest.fire.game . 90 get.adjlist . 92 get.edge.ids . 93 get.incidence . 94 get.stochastic . -
Automorphism Groups of Simple Graphs
AUTOMORPHISM GROUPS OF SIMPLE GRAPHS LUKE RODRIGUEZ Abstract Group and graph theory both provide interesting and meaninful ways of examining relationships between elements of a given set. In this paper we investigate connections between the two. This investigation begins with automorphism groups of common graphs and an introduction of Frucht's Theorem, followed by an in-depth examination of the automorphism groups of generalized Petersen graphs and cubic Hamiltonian graphs in LCF notation. In conclusion, we examine how Frucht's Theorem applies to the specific case of cubic Hamiltonian graphs. 1. Group Theory Fundamentals In the field of Abstract Algebra, one of the fundamental concepts is that of combining particular sets with operations on their elements and studying the resulting behavior. This allows us to consider a set in a more complete way than if we were just considering their elements themselves outside of the context in which they interact. For example, we might be interested in how the set of all integers modulo m behaves under addition, or how the elements of a more abstract set S behave under some set of permutations defined on the elements of S. Both of these are examples of a group. Definition 1.1. A group is a set S together with an operation ◦ such that: (1) For all a; b 2 S, the element a ◦ b = c has the property that c 2 S. (2) For all a; b; c 2 S, the equality a ◦ (b ◦ c) = (a ◦ b) ◦ c holds. (3) There exists an element e 2 S such that a ◦ e = e ◦ a = a for all a 2 S. -
Automorphism Group of Graphs (Supplemental Material for Intro to Graph Theory)
Automorphism Group of Graphs (Supplemental Material for Intro to Graph Theory) Robert A. Beeler∗ January 15, 2018 1 Introduction and Preliminary Results In this supplement, we will assume that all graphs are undirected graphs with no loops or multiple edges. In graph theory, we talk about graph isomor- phisms. As a reminder, an isomorphism between graphs G and H is a bijec- tion φ : V (G) → V (H) such that uv ∈ E(G) if and only if φ(u)φ(v) ∈ E(H). A graph automorphism is simply an isomorphism from a graph to itself. In other words, an automorphism on a graph G is a bijection φ : V (G) → V (G) such that uv ∈ E(G) if and only if φ(u)φ(v) ∈ E(G). This definition gener- alizes to digraphs, multigraphs, and graph with loops. Let Aut(G) denote the set of all automorphisms on a graph G. Note that this forms a group under function composition. In other words, (i) Aut(G) is closed under function composition. (ii) Function composition is associative on Aut(G). This follows from the fact that function composition is associative in general. (iii) There is an identity element in Aut(G). This is mapping e(v) = v for all v ∈ V (G). ∗Department of Mathematics and Statistics, East Tennessee State University, Johnson City, TN 37614-1700 USA email: [email protected] 1 2 a c d b d b c a e α a c b d b d c a β αβ Figure 1: A graph and its automorphisms (iv) For every σ ∈ Aut(G), there is an inverse element σ−1 ∈ Aut(G). -
Characterization of Perfect Matching Transitive Graphs
Electronic Journal of Graph Theory and Applications 6 (2) (2018), 362–370 Characterization of perfect matching transitive graphs Ju Zhou Department of Mathematics Kutztown University of Pennsylvania Kutztown, PA 19530, USA [email protected] Abstract A graph G is perfect matching transitive, shortly PM-transitive, if for any two perfect matchings M and N of G, there is an automorphism f : V (G) 7! V (G) such that fe(M) = N, where fe(uv) = f(u)f(v). In this paper, the author proposed the definition of PM-transitive, verified PM-transitivity of some symmetric graphs, constructed several families of PM-transitive graphs which are neither vertex-transitive nor edge-transitive, and discussed PM-transitivity of generalized Petersen graphs. Keywords: vertex-transitive, edge-transitive, symmetric, PM-transitive Mathematics Subject Classification : 68R10, 05C60 DOI: 10.5614/ejgta.2018.6.2.15 1. Introduction An automorphism of a graph is a form of symmetry in which the graph is mapped onto it- self while preserving the edge-vertex connectivity. Formally, an automorphism of a graph G = (V (G);E(G)) is a permutation f of the vertex set V (G), such that the pair of vertices uv is an edge of G if and only if f(u)f(v) is also an edge of G. That is, it is a graph isomorphism from G to itself. Every graph automorphism f induces a map fe : E(G) 7! E(G) such that fe(uv) = f(u)f(v). For any vertex set X ⊆ V (G) and edge set M ⊆ E(G), denote f(X) = ff(v): v 2 Xg and Received: 20 March 2018, Revised: 2 September 2018, Accepted: 27 September 2018. -
(V, E ) Be a Graph and Let F Be a Function That Assigns to Each Vertex of F:V(G) → {1,2,.....K} Such That for V to a Set of Values from the Set {1,2
BALANCED DOMINATION NUMBER OF SPECIAL GRAPHS 1S.CHRISTILDA and 2P.NAMASIVAYAM 1Department of Mathematics, Sadakathullah Appa College, Tirunelveli – 627011, Tamil Nadu, INDIA. E-mail: [email protected] 2PG and Research Department of Mathematics, The MDT Hindu College, Tirunelveli – 627010, Tamil Nadu, INDIA. ABSTRACT INTRODUCTION Let G= (V, E) be a graph. A Subset D of V is called a dominating Let G = (V, E ) be a graph and let f set of G if every vertex in V-D is be a function that assigns to each adjacent to atleast one vertex in D. The Domination number γ (G) of G is the vertex of V to a set of values from cardinality of the minimum dominating set of G. Let the set {1,2,.......k} that is, G = (V, E ) be a graph and let f be a function that assigns to each vertex of f:V(G) → {1,2,.....k} such that for V to a set of values from the set {1,2,.......k} that is, f:V(G) → each u,v ϵ V(G), f(u)≠f(v), if u is {1,2,.....k} such that for each u,v V(G), f(u) ≠ f(v), if u is adjacent to v in adjacent to v in G. Then the set D G. Then the dominating set D V (G) V (G) is called a balanced is called a balanced dominating set if In this dominating set if paper, we investigate the balanced domination number for some special graphs. Keywords: balanced, domination, The special graph balanced domination number Mathematics subject classification: 05C69 is the minimum cardinality of the balanced weak balanced dominating set dominating set. -
Degree (Graph Theory) from Wikipedia, the Free Encyclopedia Contents
Degree (graph theory) From Wikipedia, the free encyclopedia Contents 1 Degree (graph theory) 1 1.1 Handshaking lemma .......................................... 1 1.2 Degree sequence ............................................ 2 1.3 Special values ............................................. 3 1.4 Global properties ........................................... 3 1.5 See also ................................................ 4 1.6 Notes ................................................. 4 1.7 References ............................................... 4 2 Graph operations 5 2.1 Unary operations ........................................... 5 2.1.1 Elementary operations .................................... 5 2.1.2 Advanced operations ..................................... 5 2.2 Binary operations ........................................... 5 2.3 Notes ................................................. 6 3 Regular graph 7 3.1 Existence ............................................... 7 3.2 Algebraic properties .......................................... 7 3.3 Generation .............................................. 8 3.4 See also ................................................ 8 3.5 References .............................................. 8 3.6 External links ............................................. 8 3.7 Text and image sources, contributors, and licenses .......................... 9 3.7.1 Text .............................................. 9 3.7.2 Images ............................................ 9 3.7.3 Content license ....................................... -
Constructions for Cubic Graphs with Large Girth
Constructions for cubic graphs with large girth Norman Biggs Department of Mathematics London School of Economics Houghton St., London WC2A 2AE, UK [email protected] Submitted: October 11, 1997; Accepted: August 31, 1998 Abstract The aim of this paper is to give a coherent account of the problem of constructing cubic graphs with large girth. There is a well-defined integer µ0(g), the smallest number of vertices for which a cubic graph with girth at least g exists, and furthermore, the minimum value µ0(g) is attained by a graph whose girth is exactly g.Thevaluesofµ0(g)when 3 ≤ g ≤ 8 have been known for over thirty years. For these values of g each minimal graph is unique and, apart from the case g =7, a simple lower bound is attained. This paper is mainly concerned with what happens when g ≥ 9, where the situation is quite different. Here it is known that the simple lower bound is attained if and only if g =12. A number of techniques are described, with emphasis on the construction of families of graphs {Gi} for which the number of vertices ni and the girth gi are such that cgi ni ≤ 2 for some finite constant c. The optimum value of c is known to lie between 0.5 and 0.75. At the end of the paper there is a selection of open questions, several of them containing suggestions which might lead to improvements in the known results. There are also some historical notes on the current-best graphs for girth up to 36.