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Forbidden Subgraph Characterization of Quasi-Line Graphs Medha Dhurandhar [email protected]
Forbidden Subgraph Characterization of Quasi-line Graphs Medha Dhurandhar [email protected] Abstract: Here in particular, we give a characterization of Quasi-line Graphs in terms of forbidden induced subgraphs. In general, we prove a necessary and sufficient condition for a graph to be a union of two cliques. 1. Introduction: A graph is a quasi-line graph if for every vertex v, the set of neighbours of v is expressible as the union of two cliques. Such graphs are more general than line graphs, but less general than claw-free graphs. In [2] Chudnovsky and Seymour gave a constructive characterization of quasi-line graphs. An alternative characterization of quasi-line graphs is given in [3] stating that a graph has a fuzzy reconstruction iff it is a quasi-line graph and also in [4] using the concept of sums of Hoffman graphs. Here we characterize quasi-line graphs in terms of the forbidden induced subgraphs like line graphs. We consider in this paper only finite, simple, connected, undirected graphs. The vertex set of G is denoted by V(G), the edge set by E(G), the maximum degree of vertices in G by Δ(G), the maximum clique size by (G) and the chromatic number by G). N(u) denotes the neighbourhood of u and N(u) = N(u) + u. For further notation please refer to Harary [3]. 2. Main Result: Before proving the main result we prove some lemmas, which will be used later. Lemma 1: If G is {3K1, C5}-free, then either 1) G ~ K|V(G)| or 2) If v, w V(G) are s.t. -
On Treewidth and Graph Minors
On Treewidth and Graph Minors Daniel John Harvey Submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy February 2014 Department of Mathematics and Statistics The University of Melbourne Produced on archival quality paper ii Abstract Both treewidth and the Hadwiger number are key graph parameters in structural and al- gorithmic graph theory, especially in the theory of graph minors. For example, treewidth demarcates the two major cases of the Robertson and Seymour proof of Wagner's Con- jecture. Also, the Hadwiger number is the key measure of the structural complexity of a graph. In this thesis, we shall investigate these parameters on some interesting classes of graphs. The treewidth of a graph defines, in some sense, how \tree-like" the graph is. Treewidth is a key parameter in the algorithmic field of fixed-parameter tractability. In particular, on classes of bounded treewidth, certain NP-Hard problems can be solved in polynomial time. In structural graph theory, treewidth is of key interest due to its part in the stronger form of Robertson and Seymour's Graph Minor Structure Theorem. A key fact is that the treewidth of a graph is tied to the size of its largest grid minor. In fact, treewidth is tied to a large number of other graph structural parameters, which this thesis thoroughly investigates. In doing so, some of the tying functions between these results are improved. This thesis also determines exactly the treewidth of the line graph of a complete graph. This is a critical example in a recent paper of Marx, and improves on a recent result by Grohe and Marx. -
Infinitely Many Minimal Classes of Graphs of Unbounded Clique-Width∗
Infinitely many minimal classes of graphs of unbounded clique-width∗ A. Collins, J. Foniok†, N. Korpelainen, V. Lozin, V. Zamaraev Abstract The celebrated theorem of Robertson and Seymour states that in the family of minor-closed graph classes, there is a unique minimal class of graphs of unbounded tree-width, namely, the class of planar graphs. In the case of tree-width, the restriction to minor-closed classes is justified by the fact that the tree-width of a graph is never smaller than the tree-width of any of its minors. This, however, is not the case with respect to clique-width, as the clique-width of a graph can be (much) smaller than the clique-width of its minor. On the other hand, the clique-width of a graph is never smaller than the clique-width of any of its induced subgraphs, which allows us to be restricted to hereditary classes (that is, classes closed under taking induced subgraphs), when we study clique-width. Up to date, only finitely many minimal hereditary classes of graphs of unbounded clique-width have been discovered in the literature. In the present paper, we prove that the family of such classes is infinite. Moreover, we show that the same is true with respect to linear clique-width. Keywords: clique-width, linear clique-width, hereditary class 1 Introduction Clique-width is a graph parameter which is important in theoretical computer science, because many algorithmic problems that are generally NP-hard become polynomial-time solvable when restricted to graphs of bounded clique-width [4]. -
Counting Independent Sets in Graphs with Bounded Bipartite Pathwidth∗
Counting independent sets in graphs with bounded bipartite pathwidth∗ Martin Dyery Catherine Greenhillz School of Computing School of Mathematics and Statistics University of Leeds UNSW Sydney, NSW 2052 Leeds LS2 9JT, UK Australia [email protected] [email protected] Haiko M¨uller∗ School of Computing University of Leeds Leeds LS2 9JT, UK [email protected] 7 August 2019 Abstract We show that a simple Markov chain, the Glauber dynamics, can efficiently sample independent sets almost uniformly at random in polynomial time for graphs in a certain class. The class is determined by boundedness of a new graph parameter called bipartite pathwidth. This result, which we prove for the more general hardcore distribution with fugacity λ, can be viewed as a strong generalisation of Jerrum and Sinclair's work on approximately counting matchings, that is, independent sets in line graphs. The class of graphs with bounded bipartite pathwidth includes claw-free graphs, which generalise line graphs. We consider two further generalisations of claw-free graphs and prove that these classes have bounded bipartite pathwidth. We also show how to extend all our results to polynomially-bounded vertex weights. 1 Introduction There is a well-known bijection between matchings of a graph G and independent sets in the line graph of G. We will show that we can approximate the number of independent sets ∗A preliminary version of this paper appeared as [19]. yResearch supported by EPSRC grant EP/S016562/1 \Sampling in hereditary classes". zResearch supported by Australian Research Council grant DP190100977. 1 in graphs for which all bipartite induced subgraphs are well structured, in a sense that we will define precisely. -
General Approach to Line Graphs of Graphs 1
DEMONSTRATIO MATHEMATICA Vol. XVII! No 2 1985 Antoni Marczyk, Zdzislaw Skupien GENERAL APPROACH TO LINE GRAPHS OF GRAPHS 1. Introduction A unified approach to the notion of a line graph of general graphs is adopted and proofs of theorems announced in [6] are presented. Those theorems characterize five different types of line graphs. Both Krausz-type and forbidden induced sub- graph characterizations are provided. So far other authors introduced and dealt with single spe- cial notions of a line graph of graphs possibly belonging to a special subclass of graphs. In particular, the notion of a simple line graph of a simple graph is implied by a paper of Whitney (1932). Since then it has been repeatedly introduc- ed, rediscovered and generalized by many authors, among them are Krausz (1943), Izbicki (1960$ a special line graph of a general graph), Sabidussi (1961) a simple line graph of a loop-free graph), Menon (1967} adjoint graph of a general graph) and Schwartz (1969; interchange graph which coincides with our line graph defined below). In this paper we follow another way, originated in our previous work [6]. Namely, we distinguish special subclasses of general graphs and consider five different types of line graphs each of which is defined in a natural way. Note that a similar approach to the notion of a line graph of hypergraphs can be adopted. We consider here the following line graphsi line graphs, loop-free line graphs, simple line graphs, as well as augmented line graphs and augmented loop-free line graphs. - 447 - 2 A. Marczyk, Z. -
Empirical Comparison of Greedy Strategies for Learning Markov Networks of Treewidth K
Empirical Comparison of Greedy Strategies for Learning Markov Networks of Treewidth k K. Nunez, J. Chen and P. Chen G. Ding and R. F. Lax B. Marx Dept. of Computer Science Dept. of Mathematics Dept. of Experimental Statistics LSU LSU LSU Baton Rouge, LA 70803 Baton Rouge, LA 70803 Baton Rouge, LA 70803 Abstract—We recently proposed the Edgewise Greedy Algo- simply one less than the maximum of the orders of the rithm (EGA) for learning a decomposable Markov network of maximal cliques [5], a treewidth k DMN approximation to treewidth k approximating a given joint probability distribution a joint probability distribution of n random variables offers of n discrete random variables. The main ingredient of our algorithm is the stepwise forward selection algorithm (FSA) due computational benefits as the approximation uses products of to Deshpande, Garofalakis, and Jordan. EGA is an efficient alter- marginal distributions each involving at most k + 1 of the native to the algorithm (HGA) by Malvestuto, which constructs random variables. a model of treewidth k by selecting hyperedges of order k +1. In The treewidth k DNM learning problem deals with a given this paper, we present results of empirical studies that compare empirical distribution P ∗ (which could be given in the form HGA, EGA and FSA-K which is a straightforward application of FSA, in terms of approximation accuracy (measured by of a distribution table or in the form of a set of training data), KL-divergence) and computational time. Our experiments show and the objective is to find a DNM (i.e., a chordal graph) that (1) on the average, all three algorithms produce similar G of treewidth k which defines a probability distribution Pµ approximation accuracy; (2) EGA produces comparable or better that ”best” approximates P ∗ according to some criterion. -
The Strong Perfect Graph Theorem
Annals of Mathematics, 164 (2006), 51–229 The strong perfect graph theorem ∗ ∗ By Maria Chudnovsky, Neil Robertson, Paul Seymour, * ∗∗∗ and Robin Thomas Abstract A graph G is perfect if for every induced subgraph H, the chromatic number of H equals the size of the largest complete subgraph of H, and G is Berge if no induced subgraph of G is an odd cycle of length at least five or the complement of one. The “strong perfect graph conjecture” (Berge, 1961) asserts that a graph is perfect if and only if it is Berge. A stronger conjecture was made recently by Conforti, Cornu´ejols and Vuˇskovi´c — that every Berge graph either falls into one of a few basic classes, or admits one of a few kinds of separation (designed so that a minimum counterexample to Berge’s conjecture cannot have either of these properties). In this paper we prove both of these conjectures. 1. Introduction We begin with definitions of some of our terms which may be nonstandard. All graphs in this paper are finite and simple. The complement G of a graph G has the same vertex set as G, and distinct vertices u, v are adjacent in G just when they are not adjacent in G.Ahole of G is an induced subgraph of G which is a cycle of length at least 4. An antihole of G is an induced subgraph of G whose complement is a hole in G. A graph G is Berge if every hole and antihole of G has even length. A clique in G is a subset X of V (G) such that every two members of X are adjacent. -
Hamiltonian Cycles in Generalized Petersen Graphs Let N and K Be
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector JOURNAL OF COMBINATORIAL THEORY, Series B 24, 181-188 (1978) Hamiltonian Cycles in Generalized Petersen Graphs Kozo BANNAI Information Processing Research Center, Central Research Institute of Electric Power Industry, 1-6-I Ohternachi, Chiyoda-ku, Tokyo, Japan Communicated by the Managing Edirors Received March 5, 1974 Watkins (J. Combinatorial Theory 6 (1969), 152-164) introduced the concept of generalized Petersen graphs and conjectured that all but the original Petersen graph have a Tait coloring. Castagna and Prins (Pacific J. Math. 40 (1972), 53-58) showed that the conjecture was true and conjectured that generalized Petersen graphs G(n, k) are Hamiltonian unless isomorphic to G(n, 2) where n E S(mod 6). The purpose of this paper is to prove the conjecture of Castagna and Prins in the case of coprime numbers n and k. 1. INTRODUCTION Let n and k be coprime positive integers with k < n, i.e., (n, k) = 1. The generalized Petersengraph G(n, k) consistsof 2n vertices (0, 1, 2,..., n - 1; O’, l’,..., n - I’} and 3n edgesof the form (i, i + l), (i’, i + l’), (i, ik’) for 0 < i < n - 1, where all numbers are read modulo n. The set of edges ((i, i + 1)) and the set of edges((i’, i f l’)} are called the outer rim and the inner rim, respectively, and edges{(i, ik’)) are called spokes. Note that the above definition of generalized Petersen graphs differs from that of Watkins /4] and Castagna and Prins [2] in the numbering of the vertices. -
Cut and Pendant Vertices and the Number of Connected Induced Subgraphs of a Graph
CUT AND PENDANT VERTICES AND THE NUMBER OF CONNECTED INDUCED SUBGRAPHS OF A GRAPH AUDACE A. V. DOSSOU-OLORY Abstract. A vertex whose removal in a graph G increases the number of components of G is called a cut vertex. For all n; c, we determine the maximum number of connected induced subgraphs in a connected graph with order n and c cut vertices, and also charac- terise those graphs attaining the bound. Moreover, we show that the cycle has the smallest number of connected induced subgraphs among all cut vertex-free connected graphs. The general case c > 0 remains an open task. We also characterise the extremal graph struc- tures given both order and number of pendant vertices, and establish the corresponding formulas for the number of connected induced subgraphs. The `minimal' graph in this case is a tree, thus coincides with the structure that was given by Li and Wang [Further analysis on the total number of subtrees of trees. Electron. J. Comb. 19(4), #P48, 2012]. 1. Introduction and Preliminaries Let G be a simple graph with vertex set V (G) and edge set E(G). The graph G is said to be connected if for all u; v 2 V (G), there is a u − v path in G. An induced subgraph H of G is a graph such that ;= 6 V (H) ⊆ V (G) and E(H) consists of all those edges of G whose endvertices both belong to V (H). The order of G is the cardinality jV (G)j, i.e. the number of vertices of G; the girth of G is the smallest order of a cycle (if any) in G; a pendant vertex (or leaf) of G is a vertex of degree 1 in G. -
Induced Cycles in Graphs
Induced Cycles in Graphs 1Michael A. Henning, 2Felix Joos, 2Christian L¨owenstein, and 2Thomas Sasse 1Department of Mathematics University of Johannesburg Auckland Park, 2006 South Africa E-mail: [email protected] 2Institute of Optimization and Operations Research, Ulm University, Ulm 89081, Germany, E-mail: [email protected], E-mail: [email protected], E-mail: [email protected] Abstract The maximum cardinality of an induced 2-regular subgraph of a graph G is denoted by cind(G). We prove that if G is an r-regular graph of order n, then cind(G) ≥ n 1 2(r−1) + (r−1)(r−2) and we prove that if G is a cubic claw-free graph on order n, then cind(G) > 13n/20 and this bound is asymptotically best possible. Keywords: Induced regular subgraph; induced cycle; claw-free; matching; 1-extendability AMS subject classification: 05C38, 05C69 arXiv:1406.0606v1 [math.CO] 3 Jun 2014 1 Introduction The problem of finding a largest induced r-regular subgraph of a given graph for any value of r ≥ 0 has attracted much interest and dates back to Erd˝os, Fajtlowicz, and Staton [2]. Cardoso et al. [1] showed that it is NP-hard to find a maximum induced r-regular subgraph of a given graph. Lozin et al. [7] established efficient algorithms for special graph classes including 2P3-free graphs, while Moser and Thilikos [8] studied FPT-algorithms for finding regular induced subgraphs. The special case of finding a largest induced r-regular subgraph when r = 0 is the well- studied problem of finding a maximum independent set in a graph. -
Dominating Cliques in Graphs
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Discrete Mathematics 86 (1990) 101-116 101 North-Holland DOMINATING CLIQUES IN GRAPHS Margaret B. COZZENS Mathematics Department, Northeastern University, Boston, MA 02115, USA Laura L. KELLEHER Massachusetts Maritime Academy, USA Received 2 December 1988 A set of vertices is a dominating set in a graph if every vertex not in the dominating set is adjacent to one or more vertices in the dominating set. A dominating clique is a dominating set that induces a complete subgraph. Forbidden subgraph conditions sufficient to imply the existence of a dominating clique are given. For certain classes of graphs, a polynomial algorithm is given for finding a dominating clique. A forbidden subgraph characterization is given for a class of graphs that have a connected dominating set of size three. Introduction A set of vertices in a simple, undirected graph is a dominating set if every vertex in the graph which is not in the dominating set is adjacent to one or more vertices in the dominating set. The domination number of a graph G is the minimum number of vertices in a dominating set. Several types of dominating sets have been investigated, including independent dominating sets, total dominating sets, and connected dominating sets, each of which has a corresponding domination number. Dominating sets have applications in a variety of fields, including communication theory and political science. For more background on dominating sets see [3, 5, 151 and other articles in this issue. For arbitrary graphs, the problem of finding the size of a minimum dominating set in the graph is an NP-complete problem [9]. -
Graph in Data Structure with Example
Graph In Data Structure With Example Tremain remove punctually while Memphite Gerald valuate metabolically or soaks affrontingly. Grisliest Sasha usually reconverts some singlesticks or incage historiographically. If innocent or dignified Verge usually cleeking his pewit clipped skilfully or infests infra and exchangeably, how centum is Rad? What is integer at which means that was merely an organizational level overview of. Removes the specified node. Particularly find and examples. What facial data structure means. Graphs Murray State University. For example with edge going to structure of both have? Graphs in Data Structure Tutorial Ride. That instead of structure and with example as being compared. The traveling salesman problem near a folder example of using a tree algorithm to. When at the neighbors of efficient current node are considered, it marks the current node as visited and is removed from the unvisited list. You with example. There consider no isolated nodes in connected graph. The data structures in a stack of linked lists are featured in data in java some definitions that these files if a direction? We can be incident with example data structures! Vi and examples will only be it can be a structure in a source. What are examples can be identified by edges with. All data structures? A rescue Study a Graph Data Structure ijarcce. We can say that there are very much in its length of another and put a vertical. The edge uv, which functions that, we can be its direct support this essentially means. If they appear in data structures and solve other values for our official venues for others with them is another.