ABC of Graph Theory
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Minimum Cycle Bases and Their Applications
Minimum Cycle Bases and Their Applications Franziska Berger1, Peter Gritzmann2, and Sven de Vries3 1 Department of Mathematics, Polytechnic Institute of NYU, Six MetroTech Center, Brooklyn NY 11201, USA [email protected] 2 Zentrum Mathematik, Technische Universit¨at M¨unchen, 80290 M¨unchen, Germany [email protected] 3 FB IV, Mathematik, Universit¨at Trier, 54286 Trier, Germany [email protected] Abstract. Minimum cycle bases of weighted undirected and directed graphs are bases of the cycle space of the (di)graphs with minimum weight. We survey the known polynomial-time algorithms for their con- struction, explain some of their properties and describe a few important applications. 1 Introduction Minimum cycle bases of undirected or directed multigraphs are bases of the cycle space of the graphs or digraphs with minimum length or weight. Their intrigu- ing combinatorial properties and their construction have interested researchers for several decades. Since minimum cycle bases have diverse applications (e.g., electric networks, theoretical chemistry and biology, as well as periodic event scheduling), they are also important for practitioners. After introducing the necessary notation and concepts in Subsections 1.1 and 1.2 and reviewing some fundamental properties of minimum cycle bases in Subsection 1.3, we explain the known algorithms for computing minimum cycle bases in Section 2. Finally, Section 3 is devoted to applications. 1.1 Definitions and Notation Let G =(V,E) be a directed multigraph with m edges and n vertices. Let + E = {e1,...,em},andletw : E → R be a positive weight function on E.A cycle C in G is a subgraph (actually ignoring orientation) of G in which every vertex has even degree (= in-degree + out-degree). -
Planar Hypohamiltonian Graphs on 40 Vertices
Planar Hypohamiltonian Graphs on 40 Vertices Mohammadreza Jooyandeh, Brendan D. McKay Research School of Computer Science, Australian National University, ACT 2601, Australia Patric R. J. Osterg˚ard,¨ Ville H. Pettersson Department of Communications and Networking, Aalto University School of Electrical Engineering, P.O. Box 13000, 00076 Aalto, Finland Carol T. Zamfirescu Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Krijgslaan 281 - S9, 9000 Ghent, Belgium Abstract A graph is hypohamiltonian if it is not Hamiltonian, but the deletion of any single vertex gives a Hamiltonian graph. Until now, the smallest known planar hypohamiltonian graph had 42 vertices, a result due to Araya and Wiener. That result is here improved upon by 25 planar hypohamiltonian graphs of order 40, which are found through computer-aided generation of certain families of planar graphs with girth 4 and a fixed number of 4-faces. It is further shown that planar hypohamiltonian graphs exist for all orders greater than or equal to 42. If Hamiltonian cycles are replaced by Hamilto- nian paths throughout the definition of hypohamiltonian graphs, we get the definition of hypotraceable graphs. It is shown that there is a planar hypo- traceable graph of order 154 and of all orders greater than or equal to 156. We also show that the smallest planar hypohamiltonian graph of girth 5 has 45 vertices. Email addresses: [email protected] (Mohammadreza Jooyandeh), [email protected] (Brendan D. McKay), [email protected] (Patric R. J. Osterg˚ard),¨ [email protected] (Ville H. Pettersson), [email protected] (Carol T. Zamfirescu) URL: http://www.jooyandeh.com (Mohammadreza Jooyandeh), http://cs.anu.edu.au/~bdm (Brendan D. -
Towards Maximum Independent Sets on Massive Graphs
Towards Maximum Independent Sets on Massive Graphs Yu Liuy Jiaheng Lu x Hua Yangy Xiaokui Xiaoz Zhewei Weiy yDEKE, MOE and School of Information, Renmin University of China x Department of Computer Science, University of Helsinki, Finland zSchool of Computer Engineering, Nanyang Technological University, Singapore ABSTRACT Maximum independent set (MIS) is a fundamental problem in graph theory and it has important applications in many areas such as so- cial network analysis, graphical information systems and coding theory. The problem is NP-hard, and there has been numerous s- tudies on its approximate solutions. While successful to a certain degree, the existing methods require memory space at least linear in the size of the input graph. This has become a serious concern in !"#$!%&'!(#&)*+,+)*+)-#.+- /"#$!%&'0'#&)*+,+)*+)-#.+- view of the massive volume of today’s fast-growing graphs. Figure 1: An example to illustrate that fv , v g is a maximal inde- In this paper, we study the MIS problem under the semi-external 1 2 pendent set, but fv , v , v , v g is a maximum independent set. setting, which assumes that the main memory can accommodate 2 3 4 5 all vertices of the graph but not all edges. We present a greedy algorithm and a general vertex-swap framework, which swaps ver- duced subgraphs, minimum vertex covers, graph coloring, and tices to incrementally increase the size of independent sets. Our maximum common edge subgraphs, etc. Its significance is not solutions require only few sequential scans of graphs on the disk just limited to graph theory but also in numerous real-world ap- file, thus enabling in-memory computation without costly random plications, such as indexing techniques for shortest path and dis- disk accesses. -
1 Vertex Connectivity 2 Edge Connectivity 3 Biconnectivity
1 Vertex Connectivity So far we've talked about connectivity for undirected graphs and weak and strong connec- tivity for directed graphs. For undirected graphs, we're going to now somewhat generalize the concept of connectedness in terms of network robustness. Essentially, given a graph, we may want to answer the question of how many vertices or edges must be removed in order to disconnect the graph; i.e., break it up into multiple components. Formally, for a connected graph G, a set of vertices S ⊆ V (G) is a separating set if subgraph G − S has more than one component or is only a single vertex. The set S is also called a vertex separator or a vertex cut. The connectivity of G, κ(G), is the minimum size of any S ⊆ V (G) such that G − S is disconnected or has a single vertex; such an S would be called a minimum separator. We say that G is k-connected if κ(G) ≥ k. 2 Edge Connectivity We have similar concepts for edges. For a connected graph G, a set of edges F ⊆ E(G) is a disconnecting set if G − F has more than one component. If G − F has two components, F is also called an edge cut. The edge-connectivity if G, κ0(G), is the minimum size of any F ⊆ E(G) such that G − F is disconnected; such an F would be called a minimum cut.A bond is a minimal non-empty edge cut; note that a bond is not necessarily a minimum cut. -
Simpler Sequential and Parallel Biconnectivity Augmentation
Simpler Sequential and Parallel Biconnectivity Augmentation Surabhi Jain and N.Sadagopan Department of Computer Science and Engineering, Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram, Chennai, India. fsurabhijain,[email protected] Abstract. For a connected graph, a vertex separator is a set of vertices whose removal creates at least two components and a minimum vertex separator is a vertex separator of least cardinality. The vertex connectivity refers to the size of a minimum vertex separator. For a connected graph G with vertex connectivity k (k ≥ 1), the connectivity augmentation refers to a set S of edges whose augmentation to G increases its vertex connectivity by one. A minimum connectivity augmentation of G is the one in which S is minimum. In this paper, we focus our attention on connectivity augmentation of trees. Towards this end, we present a new sequential algorithm for biconnectivity augmentation in trees by simplifying the algorithm reported in [7]. The simplicity is achieved with the help of edge contraction tool. This tool helps us in getting a recursive subproblem preserving all connectivity information. Subsequently, we present a parallel algorithm to obtain a minimum connectivity augmentation set in trees. Our parallel algorithm essentially follows the overall structure of sequential algorithm. Our implementation is based on CREW PRAM model with O(∆) processors, where ∆ refers to the maximum degree of a tree. We also show that our parallel algorithm is optimal whose processor-time product is O(n) where n is the number of vertices of a tree, which is an improvement over the parallel algorithm reported in [3]. -
Q(A) - Balance Super Edge Magic Graphs Results
International Journal of Pure and Applied Mathematical Sciences. ISSN 0972-9828 Volume 10, Number 2 (2017), pp. 157-170 © Research India Publications http://www.ripublication.com Q(A) - Balance Super Edge Magic Graphs Results M. Rameshpandi and S. Vimala 1Assistant Professor, Department of Mathematics, Pasumpon Muthuramalinga Thevar College, Usilampatti, Madurai. 2Assistant Professor, Department of Mathematics, Mother Teresa Women’s University, Kodaikanal. Abstract Let G be (p,q)-graph in which the edges are labeled 1,2,3,4,…q so that the vertex sums are constant, mod p, then G is called an edge magic graph. Magic labeling on Q(a) balance super edge–magic graphs introduced [5]. In this paper extend my discussion of Q(a)- balance super edge magic labeling(BSEM) to few types of special graphs. AMS 2010: 05C Keywords: edge magic graph, super edge magic graph, Q(a) balance edge- magic graph. 1.INTRODUCTION Magic graphs are related to the well-known magic squares, but are not quite as famous. Magic squares are an arrangement of numbers in a square in such a way that the sum of the rows, columns and diagonals is always the same. All graphs in this paper are connected, (multi-)graphs without loop. The graph G has vertex – set V(G) and edge – set E(G). A labeling (or valuation) of a graph is a map that carries graph elements to numbers(usually to the positive or non- negative integers). Edge magic graph introduced by Sin Min Lee, Eric Seah and S.K Tan in 1992. Various author discussed in edge magic graphs like Edge magic(p,3p-1)- graphs, Zykov sums of graphs, cubic multigraphs, Edge-magicness of the composition of a cycle with a null graph. -
Every Graph Occurs As an Induced Subgraph of Some Hypohamiltonian Graph
View metadata, citation and similar papers at core.ac.uk brought to you by CORE Received: 27 October 2016 Revised: 31 October 2017 Accepted: 20 November 2017 provided by Ghent University Academic Bibliography DOI: 10.1002/jgt.22228 ARTICLE Every graph occurs as an induced subgraph of some hypohamiltonian graph Carol T. Zamfirescu1 Tudor I. Zamfirescu2,3,4 1 Department of Applied Mathematics, Com- Abstract puter Science and Statistics, Ghent University, Krijgslaan 281 - S9, 9000 Ghent, Belgium We prove the titular statement. This settles a problem 2Fachbereich Mathematik, Universität of Chvátal from 1973 and encompasses earlier results Dortmund, 44221 Dortmund, Germany of Thomassen, who showed it for 3, and Collier and 3 “Simion Stoilow” Institute of Mathematics, Schmeichel, who proved it for bipartite graphs. We also Roumanian Academy, Bucharest, Roumania show that for every outerplanar graph there exists a pla- 4College of Mathematics and Information Science, Hebei Normal University, 050024 nar hypohamiltonian graph containing it as an induced Shijiazhuang, P.R. China subgraph. Correspondence Carol T. Zamfirescu, Department of KEYWORDS Applied Mathematics, Computer Sci- hypohamiltonian, induced subgraph ence and Statistics, Ghent University, Krijgslaan 281 - S9, 9000 Ghent, Belgium. MSC 2010. Email: czamfi[email protected] 05C10, 05C45, 05C60 Funding information Fonds Wetenschappelijk Onderzoek 1 INTRODUCTION Consider a non-hamiltonian graph . We call hypohamiltonian if for every vertex in , the graph − is hamiltonian. In similar spirit, is said to be almost hypohamiltonian if there exists a vertex in , which we will call exceptional, such that − is non-hamiltonian, and for any vertex ≠ in , the graph − is hamiltonian. For an overview of results on hypohamiltonicity till 1993, see the survey by Holton and Sheehan [7]. -
On Computing Longest Paths in Small Graph Classes
On Computing Longest Paths in Small Graph Classes Ryuhei Uehara∗ Yushi Uno† July 28, 2005 Abstract The longest path problem is to find a longest path in a given graph. While the graph classes in which the Hamiltonian path problem can be solved efficiently are widely investigated, few graph classes are known to be solved efficiently for the longest path problem. For a tree, a simple linear time algorithm for the longest path problem is known. We first generalize the algorithm, and show that the longest path problem can be solved efficiently for weighted trees, block graphs, and cacti. We next show that the longest path problem can be solved efficiently on some graph classes that have natural interval representations. Keywords: efficient algorithms, graph classes, longest path problem. 1 Introduction The Hamiltonian path problem is one of the most well known NP-hard problem, and there are numerous applications of the problems [17]. For such an intractable problem, there are two major approaches; approximation algorithms [20, 2, 35] and algorithms with parameterized complexity analyses [15]. In both approaches, we have to change the decision problem to the optimization problem. Therefore the longest path problem is one of the basic problems from the viewpoint of combinatorial optimization. From the practical point of view, it is also very natural approach to try to find a longest path in a given graph, even if it does not have a Hamiltonian path. However, finding a longest path seems to be more difficult than determining whether the given graph has a Hamiltonian path or not. -
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. -
On Stable Cycles and Cycle Double Covers of Graphs with Large Circumference
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Discrete Mathematics 312 (2012) 2540–2544 Contents lists available at SciVerse ScienceDirect Discrete Mathematics journal homepage: www.elsevier.com/locate/disc On stable cycles and cycle double covers of graphs with large circumference Jonas Hägglund ∗, Klas Markström Department of Mathematics and Mathematical Statistics, Umeå University, SE-901 87 Umeå, Sweden article info a b s t r a c t Article history: A cycle C in a graph is called stable if there exists no other cycle D in the same graph such Received 11 October 2010 that V .C/ ⊆ V .D/. In this paper, we study stable cycles in snarks and we show that if a Accepted 16 August 2011 cubic graph G has a cycle of length at least jV .G/j − 9 then it has a cycle double cover. We Available online 23 September 2011 also give a construction for an infinite snark family with stable cycles of constant length and answer a question by Kochol by giving examples of cyclically 5-edge connected snarks Keywords: with stable cycles. Stable cycle ' 2011 Elsevier B.V. All rights reserved. Snark Cycle double cover Semiextension 1. Introduction In this paper, a cycle is a connected 2-regular subgraph. A cycle double cover (usually abbreviated CDC) is a multiset of cycles covering the edges of a graph such that each edge lies in exactly two cycles. The following is a famous open conjecture in graph theory. Conjecture 1.1 (CDCC). -
Lab05 - Matroid Exercises for Algorithms by Xiaofeng Gao, 2016 Spring Semester
Lab05 - Matroid Exercises for Algorithms by Xiaofeng Gao, 2016 Spring Semester Name: Student ID: Email: 1. Provide an example of (S; C) which is an independent system but not a matroid. Give an instance of S such that v(S) 6= u(S) (should be different from the example posted in class). 2. Matching matroid MC : Let G = (V; E) be an arbitrary undirected graph. C is the collection of all vertices set which can be covered by a matching in G. (a) Prove that MC = (V; C) is a matroid. (b) Given a graph G = (V; E) where each vertex vi has a weight w(vi), please give an algorithm to find the matching where the weight of all covered vertices is maximum. Prove the correctness and analyze the time complexity of your algorithm. Note: Given a graph G = (V; E), a matching M in G is a set of pairwise non-adjacent edges; that is, no two edges share a common vertex. A vertex is covered (or matched) if it is an endpoint of one of the edges in the matching. Otherwise the vertex is uncovered. 3. A Dyck path of length 2n is a path in the plane from (0; 0) to (2n; 0), with steps U = (1; 1) and D = (1; −1), that never passes below the x-axis. For example, P = UUDUDUUDDD is a Dyck path of length 10. Each Dyck path defines an up-step set: the subset of [2n] consisting of the integers i such that the i-th step of the path is U. -
BIOINFORMATICS Doi:10.1093/Bioinformatics/Btt213
Vol. 29 ISMB/ECCB 2013, pages i352–i360 BIOINFORMATICS doi:10.1093/bioinformatics/btt213 Haplotype assembly in polyploid genomes and identical by descent shared tracts Derek Aguiar and Sorin Istrail* Department of Computer Science and Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA ABSTRACT Standard genome sequencing workflows produce contiguous Motivation: Genome-wide haplotype reconstruction from sequence DNA segments of an unknown chromosomal origin. De novo data, or haplotype assembly, is at the center of major challenges in assemblies for genomes with two sets of chromosomes (diploid) molecular biology and life sciences. For complex eukaryotic organ- or more (polyploid) produce consensus sequences in which the isms like humans, the genome is vast and the population samples are relative haplotype phase between variants is undetermined. The growing so rapidly that algorithms processing high-throughput set of sequencing reads can be mapped to the phase-ambiguous sequencing data must scale favorably in terms of both accuracy and reference genome and the diploid chromosome origin can be computational efficiency. Furthermore, current models and methodol- determined but, without knowledge of the haplotype sequences, ogies for haplotype assembly (i) do not consider individuals sharing reads cannot be mapped to the particular haploid chromosome haplotypes jointly, which reduces the size and accuracy of assembled sequence. As a result, reference-based genome assembly algo- haplotypes, and (ii) are unable to model genomes having more than rithms also produce unphased assemblies. However, sequence two sets of homologous chromosomes (polyploidy). Polyploid organ- reads are derived from a single haploid fragment and thus pro- isms are increasingly becoming the target of many research groups vide valuable phase information when they contain two or more variants.