The Automorphism Group of the Halved Cube
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Algebraic Graph Theory: Automorphism Groups and Cayley Graphs
Algebraic Graph Theory: Automorphism Groups and Cayley graphs Glenna Toomey April 2014 1 Introduction An algebraic approach to graph theory can be useful in numerous ways. There is a relatively natural intersection between the fields of algebra and graph theory, specifically between group theory and graphs. Perhaps the most natural connection between group theory and graph theory lies in finding the automorphism group of a given graph. However, by studying the opposite connection, that is, finding a graph of a given group, we can define an extremely important family of vertex-transitive graphs. This paper explores the structure of these graphs and the ways in which we can use groups to explore their properties. 2 Algebraic Graph Theory: The Basics First, let us determine some terminology and examine a few basic elements of graphs. A graph, Γ, is simply a nonempty set of vertices, which we will denote V (Γ), and a set of edges, E(Γ), which consists of two-element subsets of V (Γ). If fu; vg 2 E(Γ), then we say that u and v are adjacent vertices. It is often helpful to view these graphs pictorially, letting the vertices in V (Γ) be nodes and the edges in E(Γ) be lines connecting these nodes. A digraph, D is a nonempty set of vertices, V (D) together with a set of ordered pairs, E(D) of distinct elements from V (D). Thus, given two vertices, u, v, in a digraph, u may be adjacent to v, but v is not necessarily adjacent to u. This relation is represented by arcs instead of basic edges. -
How Symmetric Are Real-World Graphs? a Large-Scale Study
S S symmetry Article How Symmetric Are Real-World Graphs? A Large-Scale Study Fabian Ball * and Andreas Geyer-Schulz Karlsruhe Institute of Technology, Institute of Information Systems and Marketing, Kaiserstr. 12, 76131 Karlsruhe, Germany; [email protected] * Correspondence: [email protected]; Tel.: +49-721-608-48404 Received: 22 December 2017; Accepted: 10 January 2018; Published: 16 January 2018 Abstract: The analysis of symmetry is a main principle in natural sciences, especially physics. For network sciences, for example, in social sciences, computer science and data science, only a few small-scale studies of the symmetry of complex real-world graphs exist. Graph symmetry is a topic rooted in mathematics and is not yet well-received and applied in practice. This article underlines the importance of analyzing symmetry by showing the existence of symmetry in real-world graphs. An analysis of over 1500 graph datasets from the meta-repository networkrepository.com is carried out and a normalized version of the “network redundancy” measure is presented. It quantifies graph symmetry in terms of the number of orbits of the symmetry group from zero (no symmetries) to one (completely symmetric), and improves the recognition of asymmetric graphs. Over 70% of the analyzed graphs contain symmetries (i.e., graph automorphisms), independent of size and modularity. Therefore, we conclude that real-world graphs are likely to contain symmetries. This contribution is the first larger-scale study of symmetry in graphs and it shows the necessity of handling symmetry in data analysis: The existence of symmetries in graphs is the cause of two problems in graph clustering we are aware of, namely, the existence of multiple equivalent solutions with the same value of the clustering criterion and, secondly, the inability of all standard partition-comparison measures of cluster analysis to identify automorphic partitions as equivalent. -
On the Group-Theoretic Properties of the Automorphism Groups of Various Graphs
ON THE GROUP-THEORETIC PROPERTIES OF THE AUTOMORPHISM GROUPS OF VARIOUS GRAPHS CHARLES HOMANS Abstract. In this paper we provide an introduction to the properties of one important connection between the theories of groups and graphs, that of the group formed by the automorphisms of a given graph. We provide examples of important results in graph theory that can be understood through group theory and vice versa, and conclude with a treatment of Frucht's theorem. Contents 1. Introduction 1 2. Fundamental Definitions, Concepts, and Theorems 2 3. Example 1: The Orbit-Stabilizer Theorem and its Application to Graph Automorphisms 4 4. Example 2: On the Automorphism Groups of the Platonic Solid Skeleton Graphs 4 5. Example 3: A Tight Bound on the Product of the Chromatic Number and Independence Number of Vertex-Transitive Graphs 6 6. Frucht's Theorem 7 7. Acknowledgements 9 8. References 9 1. Introduction Groups and graphs are two highly important kinds of structures studied in math- ematics. Interestingly, the theory of groups and the theory of graphs are deeply connected. In this paper, we examine one particular such connection: that which emerges from the observation that the automorphisms of any given graph form a group under composition. In section 2, we provide a framework for understanding the material discussed in the paper. In sections 3, 4, and 5, we demonstrate how important results in group theory illuminate some properties of automorphism groups, how the geo- metric properties of particular embeddings of graphs can be used to determine the structure of the automorphism groups of all embeddings of those graphs, and how the automorphism group can be used to determine fundamental truths about the structure of the graph. -
Construction of Strongly Regular Graphs Having an Automorphism Group of Composite Order
Volume 15, Number 1, Pages 22{41 ISSN 1715-0868 CONSTRUCTION OF STRONGLY REGULAR GRAPHS HAVING AN AUTOMORPHISM GROUP OF COMPOSITE ORDER DEAN CRNKOVIC´ AND MARIJA MAKSIMOVIC´ Abstract. In this paper we outline a method for constructing strongly regular graphs from orbit matrices admitting an automorphism group of composite order. In 2011, C. Lam and M. Behbahani introduced the concept of orbit matrices of strongly regular graphs and developed an algorithm for the construction of orbit matrices of strongly regu- lar graphs with a presumed automorphism group of prime order, and construction of corresponding strongly regular graphs. The method of constructing strongly regular graphs developed and employed in this paper is a generalization of that developed by C. Lam and M. Behba- hani. Using this method we classify SRGs with parameters (49,18,7,6) having an automorphism group of order six. Eleven of the SRGs with parameters (49,18,7,6) constructed in that way are new. We obtain an additional 385 new SRGs(49,18,7,6) by switching. Comparing the con- structed graphs with previously known SRGs with these parameters, we conclude that up to isomorphism there are at least 727 SRGs with parameters (49,18,7,6). Further, we show that there are no SRGs with parameters (99,14,1,2) having an automorphism group of order six or nine, i.e. we rule out automorphism groups isomorphic to Z6, S3, Z9, or E9. 1. Introduction One of the main problems in the theory of strongly regular graphs (SRGs) is constructing and classifying SRGs with given parameters. -
A New Approach to the Snake-In-The-Box Problem
462 ECAI 2012 Luc De Raedt et al. (Eds.) © 2012 The Author(s). This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License. doi:10.3233/978-1-61499-098-7-462 A New Approach to the Snake-In-The-Box Problem David Kinny1 Abstract. The “Snake-In-The-Box” problem, first described more Research on the SIB problem initially focused on applications in than 50 years ago, is a hard combinatorial search problem whose coding [14]. Coils are spread-k circuit codes for k =2, in which solutions have many practical applications. Until recently, techniques n-words k or more positions apart in the code differ in at least k based on Evolutionary Computation have been considered the state- bit positions [12]. (The well-known Gray codes are spread-1 circuit of-the-art for solving this deterministic maximization problem, and codes.) Longest snakes and coils provide the maximum number of held most significant records. This paper reviews the problem and code words for a given word size (i.e., hypercube dimension). prior solution techniques, then presents a new technique, based on A related application is in encoding schemes for analogue-to- Monte-Carlo Tree Search, which finds significantly better solutions digital converters including shaft (rotation) encoders. Longest SIB than prior techniques, is considerably faster, and requires no tuning. codes provide greatest resolution, and single bit errors are either recognised as such or map to an adjacent codeword causing an off- 1 INTRODUCTION by-one error. -
Degree in Mathematics
Degree in Mathematics Title: An Experimental Study of the Minimum Linear Colouring Arrangement Problem. Author: Montserrat Brufau Vidal Advisor: Maria José Serna Iglesias Department: Computer Science Department Academic year: 2016-2017 ii An experimental study of the Minimum Linear Colouring Arrangement Problem Author: Montserrat Brufau Vidal Advisor: Maria Jos´eSerna Iglesias Facultat de Matem`atiquesi Estad´ıstica Universitat Polit`ecnicade Catalunya 26th June 2017 ii Als meus pares; a la Maria pel seu suport durant el projecte; al meu poble, Men`arguens. iii iv Abstract The Minimum Linear Colouring Arrangement problem (MinLCA) is a variation from the Min- imum Linear Arrangement problem (MinLA) and the Colouring problem. The objective of the MinLA problem is finding the best way of labelling each vertex of a graph in such a manner that the sum of the induced distances between two adjacent vertices is the minimum. In our case, instead of labelling each vertex with a different integer, we group them with the condition that two adjacent vertices cannot be in the same group, or equivalently, by allowing the vertex labelling to be a proper colouring of the graph. In this project, we undertake the task of broadening the previous studies for the MinLCA problem. The main goal is developing some exact algorithms based on backtracking and some heuristic algorithms based on a maximal independent set approach and testing them with dif- ferent instances of graph families. As a secondary goal we are interested in providing theoretical results for particular graphs. The results will be made available in a simple, open-access bench- marking platform. -
The Snake-In-The-Box Problem: a Primer
THE SNAKE-IN-THE-BOX PROBLEM: A PRIMER by THOMAS E. DRAPELA (Under the Direction of Walter D. Potter) ABSTRACT This thesis is a primer designed to introduce novice and expert alike to the Snake-in-the- Box problem (SIB). Using plain language, and including explanations of prerequisite concepts necessary for understanding SIB throughout, it introduces the essential concepts of SIB, its origin, evolution, and continued relevance, as well as methods for representing, validating, and evaluating snake and coil solutions in SIB search. Finally, it is structured to serve as a convenient reference for those exploring SIB. INDEX WORDS: Snake-in-the-Box, Coil-in-the-Box, Hypercube, Snake, Coil, Graph Theory, Constraint Satisfaction, Canonical Ordering, Canonical Form, Equivalence Class, Disjunctive Normal Form, Conjunctive Normal Form, Heuristic Search, Fitness Function, Articulation Points THE SNAKE-IN-THE-BOX PROBLEM: A PRIMER by THOMAS E. DRAPELA B.A., George Mason University, 1991 A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE ATHENS, GEORGIA 2015 © 2015 Thomas E. Drapela All Rights Reserved THE SNAKE-IN-THE-BOX PROBLEM: A PRIMER by THOMAS E. DRAPELA Major Professor: Walter D. Potter Committee: Khaled Rasheed Pete Bettinger Electronic Version Approved: Julie Coffield Interim Dean of the Graduate School The University of Georgia May 2015 DEDICATION To my dearest Kristin: For loving me enough to give me a shove. iv ACKNOWLEDGEMENTS I wish to express my deepest gratitude to Dr. Potter for introducing me to the Snake-in-the-Box problem, for giving me the freedom to get lost in it, and finally, for helping me to find my way back. -
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 Archive of All Submitted Project Proposals
CS 598 JGE ] Fall 2017 One-Dimensional Computational Topology Project Proposals Theory 0 Bhuvan Venkatesh: embedding graphs into hypercubes ....................... 1 Brendan Wilson: anti-Borradaile-Klein? .................................. 4 Charles Shang: vertex-disjoint paths in planar graphs ......................... 6 Hsien-Chih Chang: bichromatic triangles in pseudoline arrangements ............. 9 Sameer Manchanda: one more shortest-path tree in planar graphs ............... 11 Implementation 13 Jing Huang: evaluation of image segmentation algorithms ..................... 13 Shailpik Roy: algorithm visualization .................................... 15 Qizin (Stark) Zhu: evaluation of r-division algorithms ........................ 17 Ziwei Ba: algorithm visualization ....................................... 20 Surveys 22 Haizi Yu: topological music analysis ..................................... 22 Kevin Hong: topological data analysis .................................... 24 Philip Shih: planarity testing algorithms .................................. 26 Ross Vasko: planar graph clustering ..................................... 28 Yasha Mostofi: image processing via maximum flow .......................... 31 CS 598JGE Project Proposal Name and Netid: Bhuvan Venkatesh: bvenkat2 Introduction Embedding arbitrary graphs into Hypercubes has been the study of research for many practical implementation purposes such as interprocess communication or resource. A hypercube graph is any graph that has a set of 2d vertexes and all the vertexes are -
Eindhoven University of Technology BACHELOR on the K-Independent
Eindhoven University of Technology BACHELOR On the k-Independent Set Problem Koerts, Hidde O. Award date: 2021 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain On the k-Independent Set Problem Hidde Koerts Supervised by Aida Abiad February 1, 2021 Hidde Koerts Supervised by Aida Abiad Abstract In this thesis, we study several open problems related to the k-independence num- ber, which is defined as the maximum size of a set of vertices at pairwise dis- tance greater than k (or alternatively, as the independence number of the k-th graph power). Firstly, we extend the definitions of vertex covers and cliques to allow for natural extensions of the equivalencies between independent sets, ver- tex covers, and cliques. -
Connectivity 1
Ma/CS 6b Class 5: Graph Connectivity By Adam Sheffer A Connectivity Problem Prove. The vertices of a connected graph 퐺 can always be ordered as 푣1, 푣2, … , 푣푛 such that for every 1 < 푖 ≤ 푛, if we remove 푣푖, 푣푖+1, … , 푣푛 and the edges adjacent to these vertices, 퐺 remains connected. 푣3 푣4 푣1 푣2 푣5 Proof Pick any vertex as 푣1. Pick a vertex that is connected to 푣1 in 퐺 and set it as 푣2. Pick a vertex that is connected either to 푣1 or to 푣2 in 퐺 and set it as 푣3. … Communications Network We are given a set of routers and wish to connect pairs of them to obtain a connected communications network. The network should be reliable – a few malfunctioning routers should not disable the entire network. ◦ What condition should we require from the network? ◦ That after removing any 푘 routers, the network remains connected. 푘-connected Graphs An graph 퐺 = (푉, 퐸) is said to be 푘- connected if 푉 > 푘 and we cannot obtain a non-connected graph by removing 푘 − 1 vertices from 푉. Is the graph in the figure ◦ 1-connected? Yes. ◦ 2-connected? Yes. ◦ 3-connected? No! Connectivity Which graphs are 1-connected? ◦ These are exactly the connected graphs. The connectivity of a graph 퐺 is the maximum integer 푘 such that 퐺 is 푘- connected. What is the connectivity of the complete graph 퐾푛? 푛 − 1. The graph in the figure has a connectivity of 2. Hypercube A hypercube is a generalization of the cube into any dimension. -
Layout Volumes of the Hypercube∗
Layout Volumes of the Hypercube¤ Lubomir Torok Institute of Mathematics and Computer Science Severna 5, 974 01 Banska Bystrica, Slovak Republic Imrich Vrt'o Department of Informatics Institute of Mathematics, Slovak Academy of Sciences Dubravska 9, 841 04 Bratislava, Slovak Republic Abstract We study 3-dimensional layouts of the hypercube in a 1-active layer and general model. The problem can be understood as a graph drawing problem in 3D space and was addressed at Graph Drawing 2003 [5]. For both models we prove general lower bounds which relate volumes of layouts to a graph parameter cutwidth. Then we propose tight bounds on volumes of layouts of N-vertex hypercubes. Especially, we 2 3 3 have VOL (Q ) = N 2 log N + O(N 2 ); for even log N and VOL(Q ) = p 1¡AL log N 3 log N 3 2 6 2 4=3 9 N + O(N log N); for log N divisible by 3. The 1-active layer layout can be easily extended to a 2-active layer (bottom and top) layout which improves a result from [5]. 1 Introduction The research on three-dimensional circuit layouts started in seminal works [15, 17] as a response to advances in VLSI technology. Their model of a 3-dimensional circuit was a natural generalization of the 2-dimensional model [18]. Several basic results have been proved since then which show that the 3-dimensional layout may essentially reduce ma- terial, measured as volume [6, 12]. The problem may be also understood as a special 3-dimensional orthogonal drawing of graphs, see e.g., [9].