A Cubic Vertex-Kernel for Trivially Perfect Editing
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On the Super Domination Number of Graphs
On the super domination number of graphs Douglas J. Klein1, Juan A. Rodr´ıguez-Vel´azquez1,2, Eunjeong Yi1 1Texas A&M University at Galveston Foundational Sciences, Galveston, TX 77553, United States 2Universitat Rovira i Virgili, Departament d’Enginyeria Inform`atica i Matem`atiques Av. Pa¨ısos Catalans 26, 43007 Tarragona, Spain Email addresses: [email protected], [email protected],[email protected] April 24, 2018 Abstract The open neighbourhood of a vertex v of a graph G is the set N(v) consisting of all vertices adjacent to v in G. For D ⊆ V (G), we define D = V (G) \ D. A set D ⊆ V (G) is called a super dominating set of G if for every vertex u ∈ D, there exists v ∈ D such that N(v) ∩ D = {u}. The super domination number of G is the minimum cardinality among all super dominating sets in G. In this article, we obtain closed formulas and tight bounds for the super domination number of G in terms of several invariants of G. Furthermore, the particular cases of corona product graphs and Cartesian product graphs are considered. Keywords: Super domination number; Domination number; Cartesian product; Corona product. AMS Subject Classification numbers: 05C69; 05C70 ; 05C76 1 Introduction arXiv:1705.00928v2 [math.CO] 23 Apr 2018 The open neighbourhood of a vertex v of a graph G is the set N(v) consisting of all vertices adjacent to v in G. For D ⊆ V (G), we define D = V (G) \ D. A set D ⊆ V (G) is dominating in G if every vertex in D has at least one neighbour in D, i.e., N(u) ∩ D =6 ∅ for every u ∈ D. -
Merging Peg Solitaire in Graphs
Marquette University e-Publications@Marquette Mathematics, Statistics and Computer Science Mathematics, Statistics and Computer Science, Faculty Research and Publications Department of (-2019) 7-17-2017 Merging Peg Solitaire in Graphs John Engbers Marquette University, [email protected] Ryan Weber Marquette University Follow this and additional works at: https://epublications.marquette.edu/mscs_fac Part of the Computer Sciences Commons, Mathematics Commons, and the Statistics and Probability Commons Recommended Citation Engbers, John and Weber, Ryan, "Merging Peg Solitaire in Graphs" (2017). Mathematics, Statistics and Computer Science Faculty Research and Publications. 629. https://epublications.marquette.edu/mscs_fac/629 INVOLVE 11:1 (2018) :-msp dx.doi.org/10.2140/involve.2018.11.53 Merging peg solitaire on graphs John Engbers and Ryan Weber (Communicated by Anant Godbole) Peg solitaire has recently been generalized to graphs. Here, pegs start on all but one of the vertices in a graph. A move takes pegs on adjacent vertices x and y, with y also adjacent to a hole on vertex z, and jumps the peg on x over the peg on y to z, removing the peg on y. The goal of the game is to reduce the number of pegs to one. We introduce the game merging peg solitaire on graphs, where a move takes pegs on vertices x and z (with a hole on y) and merges them to a single peg on y. When can a confguration on a graph, consisting of pegs on all vertices but one, be reduced to a confguration with only a single peg? We give results for a number of graph classes, including stars, paths, cycles, complete bipartite graphs, and some caterpillars. -
Decomposition of Wheel Graphs Into Stars, Cycles and Paths
Malaya Journal of Matematik, Vol. 9, No. 1, 456-460, 2021 https://doi.org/10.26637/MJM0901/0076 Decomposition of wheel graphs into stars, cycles and paths M. Subbulakshmi1 and I. Valliammal2* Abstract Let G = (V;E) be a finite graph with n vertices. The Wheel graph Wn is a graph with vertex set fv0;v1;v2;:::;vng and edge-set consisting of all edges of the form vivi+1 and v0vi where 1 ≤ i ≤ n, the subscripts being reduced modulo n. Wheel graph of (n + 1) vertices denoted by Wn. Decomposition of Wheel graph denoted by D(Wn). A star with 3 edges is called a claw S3. In this paper, we show that any Wheel graph can be decomposed into following ways. 8 (n − 2d)S ; d = 1;2;3;::: if n ≡ 0 (mod 6) > 3 > >[(n − 2d) − 1]S3 and P3; d = 1;2;3::: if n ≡ 1 (mod 6) > <[(n − 2d) − 1]S3 and P2; d = 1;2;3;::: if n ≡ 2 (mod 6) D(Wn) = . (n − 2d)S and C ; d = 1;2;3;::: if n ≡ 3 (mod 6) > 3 3 > >(n − 2d)S3 and P3; d = 1;2;3::: if n ≡ 4 (mod 6) > :(n − 2d)S3 and P2; d = 1;2;3;::: if n ≡ 5 (mod 6) Keywords Wheel Graph, Decomposition, claw. AMS Subject Classification 05C70. 1Department of Mathematics, G.V.N. College, Kovilpatti, Thoothukudi-628502, Tamil Nadu, India. 2Department of Mathematics, Manonmaniam Sundaranar University, Tirunelveli-627012, Tamil Nadu, India. *Corresponding author: [email protected]; [email protected] Article History: Received 01 November 2020; Accepted 30 January 2021 c 2021 MJM. -
Arxiv:2106.16130V1 [Math.CO] 30 Jun 2021 in the Special Case of Cyclohedra, and by Cardinal, Langerman and P´Erez-Lantero [5] in the Special Case of Tree Associahedra
LAGOS 2021 Bounds on the Diameter of Graph Associahedra Jean Cardinal1;4 Universit´elibre de Bruxelles (ULB) Lionel Pournin2;4 Mario Valencia-Pabon3;4 LIPN, Universit´eSorbonne Paris Nord Abstract Graph associahedra are generalized permutohedra arising as special cases of nestohedra and hypergraphic polytopes. The graph associahedron of a graph G encodes the combinatorics of search trees on G, defined recursively by a root r together with search trees on each of the connected components of G − r. In particular, the skeleton of the graph associahedron is the rotation graph of those search trees. We investigate the diameter of graph associahedra as a function of some graph parameters. It is known that the diameter of the associahedra of paths of length n, the classical associahedra, is 2n − 6 for a large enough n. We give a tight bound of Θ(m) on the diameter of trivially perfect graph associahedra on m edges. We consider the maximum diameter of associahedra of graphs on n vertices and of given tree-depth, treewidth, or pathwidth, and give lower and upper bounds as a function of these parameters. Finally, we prove that the maximum diameter of associahedra of graphs of pathwidth two is Θ(n log n). Keywords: generalized permutohedra, graph associahedra, tree-depth, treewidth, pathwidth 1 Introduction The vertices and edges of a polyhedron form a graph whose diameter (often referred to as the diameter of the polyhedron for short) is related to a number of computational problems. For instance, the question of how large the diameter of a polyhedron arises naturally from the study of linear programming and the simplex algorithm (see, for instance [27] and references therein). -
Coalition Graphs of Paths, Cycles, and Trees
Discussiones Mathematicae Graph Theory xx (xxxx) 1–16 https://doi.org/10.7151/dmgt.2416 COALITION GRAPHS OF PATHS, CYCLES, AND TREES Teresa W. Haynes Department of Mathematics and Statistics East Tennessee State University Johnson City, TN 37604 e-mail: [email protected] Jason T. Hedetniemi Department of Mathematics Wilkes Honors College Florida Atlantic University Jupiter, FL 33458 e-mail: [email protected] Stephen T. Hedetniemi School of Computing Clemson University Clemson, SC 29634 e-mail: [email protected] Alice A. McRae and Raghuveer Mohan Computer Science Department Appalachian State University Boone, NC 28608 e-mail: [email protected] [email protected] Abstract A coalition in a graph G =(V,E) consists of two disjoint sets of vertices V1 and V2, neither of which is a dominating set of G but whose union V1 ∪V2 is a dominating set of G. A coalition partition in a graph G of order n = |V | 2 Haynes, Hedetniemi, Hedetniemi, McRae and Mohan is a vertex partition π = {V1,V2,...,Vk} of V such that every set Vi either is a dominating set consisting of a single vertex of degree n − 1, or is not a dominating set but forms a coalition with another set Vj which is not a dominating set. Associated with every coalition partition π of a graph G is a graph called the coalition graph of G with respect to π, denoted CG(G, π), the vertices of which correspond one-to-one with the sets V1,V2,...,Vk of π and two vertices are adjacent in CG(G, π) if and only if their corresponding sets in π form a coalition. -
Interval Completion with Few Edges∗
Interval Completion with Few Edges∗ Pinar Heggernes Christophe Paul Department of Informatics CNRS - LIRMM, and University of Bergen School of Computer Science Norway McGill Univ. Canada [email protected] [email protected] Jan Arne Telle Yngve Villanger Department of Informatics Department of Informatics University of Bergen University of Bergen Norway Norway [email protected] [email protected] ABSTRACT Keywords We present an algorithm with runtime O(k2kn3m) for the Interval graphs, physical mapping, profile minimization, following NP-complete problem [8, problem GT35]: Given edge completion, FPT algorithm, branching an arbitrary graph G on n vertices and m edges, can we obtain an interval graph by adding at most k new edges to G? This resolves the long-standing open question [17, 6, 24, 1. INTRODUCTION AND MOTIVATION 13], first posed by Kaplan, Shamir and Tarjan, of whether Interval graphs are the intersection graphs of intervals of this problem could be solved in time f(k) nO(1). The prob- the real line and have a wide range of applications [12]. lem has applications in Physical Mapping· of DNA [11] and Connected with interval graphs is the following problem: in Profile Minimization for Sparse Matrix Computations [9, Given an arbitrary graph G, what is the minimum number 25]. For the first application, our results show tractability of edges that must be added to G in order to obtain an in- for the case of a small number k of false negative errors, and terval graph? This problem is NP-hard [18, 8] and it arises for the second, a small number k of zero elements in the in both Physical Mapping of DNA and Sparse Matrix Com- envelope. -
A Class of Hypergraphs That Generalizes Chordal Graphs
MATH. SCAND. 106 (2010), 50–66 A CLASS OF HYPERGRAPHS THAT GENERALIZES CHORDAL GRAPHS ERIC EMTANDER Abstract In this paper we introduce a class of hypergraphs that we call chordal. We also extend the definition of triangulated hypergraphs, given by H. T. Hà and A. Van Tuyl, so that a triangulated hypergraph, according to our definition, is a natural generalization of a chordal (rigid circuit) graph. R. Fröberg has showed that the chordal graphs corresponds to graph algebras, R/I(G), with linear resolu- tions. We extend Fröberg’s method and show that the hypergraph algebras of generalized chordal hypergraphs, a class of hypergraphs that includes the chordal hypergraphs, have linear resolutions. The definitions we give, yield a natural higher dimensional version of the well known flag property of simplicial complexes. We obtain what we call d-flag complexes. 1. Introduction and preliminaries Let X be a finite set and E ={E1,...,Es } a finite collection of non empty subsets of X . The pair H = (X, E ) is called a hypergraph. The elements of X and E , respectively, are called the vertices and the edges, respectively, of the hypergraph. If we want to specify what hypergraph we consider, we may write X (H ) and E (H ) for the vertices and edges respectively. A hypergraph is called simple if: (1) |Ei |≥2 for all i = 1,...,s and (2) Ej ⊆ Ei only if i = j. If the cardinality of X is n we often just use the set [n] ={1, 2,...,n} instead of X . Let H be a hypergraph. A subhypergraph K of H is a hypergraph such that X (K ) ⊆ X (H ), and E (K ) ⊆ E (H ).IfY ⊆ X , the induced hypergraph on Y, HY , is the subhypergraph with X (HY ) = Y and with E (HY ) consisting of the edges of H that lie entirely in Y. -
Vertex Deletion Problems on Chordal Graphs∗†
Vertex Deletion Problems on Chordal Graphs∗† Yixin Cao1, Yuping Ke2, Yota Otachi3, and Jie You4 1 Department of Computing, Hong Kong Polytechnic University, Hong Kong, China [email protected] 2 Department of Computing, Hong Kong Polytechnic University, Hong Kong, China [email protected] 3 Faculty of Advanced Science and Technology, Kumamoto University, Kumamoto, Japan [email protected] 4 School of Information Science and Engineering, Central South University and Department of Computing, Hong Kong Polytechnic University, Hong Kong, China [email protected] Abstract Containing many classic optimization problems, the family of vertex deletion problems has an important position in algorithm and complexity study. The celebrated result of Lewis and Yan- nakakis gives a complete dichotomy of their complexity. It however has nothing to say about the case when the input graph is also special. This paper initiates a systematic study of vertex deletion problems from one subclass of chordal graphs to another. We give polynomial-time algorithms or proofs of NP-completeness for most of the problems. In particular, we show that the vertex deletion problem from chordal graphs to interval graphs is NP-complete. 1998 ACM Subject Classification F.2.2 Analysis of Algorithms and Problem Complexity, G.2.2 Graph Theory Keywords and phrases vertex deletion problem, maximum subgraph, chordal graph, (unit) in- terval graph, split graph, hereditary property, NP-complete, polynomial-time algorithm Digital Object Identifier 10.4230/LIPIcs.FSTTCS.2017.22 1 Introduction Generally speaking, a vertex deletion problem asks to transform an input graph to a graph in a certain class by deleting a minimum number of vertices. -
A Subexponential Parameterized Algorithm for Proper Interval Completion
A subexponential parameterized algorithm for Proper Interval Completion Ivan Bliznets1 Fedor V. Fomin2 Marcin Pilipczuk2 Micha l Pilipczuk2 1St. Petersburg Academic University of the Russian Academy of Sciences, Russia 2Department of Informatics, University of Bergen, Norway ESA'14, Wroc law, September 9th, 2014 Bliznets, Fomin, Pilipczuk×2 SubExp for PIC 1/17 Proper interval graphs: graphs admitting an intersection model of intervals on a line s.t. no interval contains any other interval. Unit interval graphs: graphs admitting an intersection model of unit intervals on a line. PIG = UIG. (Proper) interval graphs Interval graphs: graphs admitting an intersection model of intervals on a line. Bliznets, Fomin, Pilipczuk×2 SubExp for PIC 2/17 Unit interval graphs: graphs admitting an intersection model of unit intervals on a line. PIG = UIG. (Proper) interval graphs Interval graphs: graphs admitting an intersection model of intervals on a line. Proper interval graphs: graphs admitting an intersection model of intervals on a line s.t. no interval contains any other interval. Bliznets, Fomin, Pilipczuk×2 SubExp for PIC 2/17 PIG = UIG. (Proper) interval graphs Interval graphs: graphs admitting an intersection model of intervals on a line. Proper interval graphs: graphs admitting an intersection model of intervals on a line s.t. no interval contains any other interval. Unit interval graphs: graphs admitting an intersection model of unit intervals on a line. Bliznets, Fomin, Pilipczuk×2 SubExp for PIC 2/17 (Proper) interval graphs Interval graphs: graphs admitting an intersection model of intervals on a line. Proper interval graphs: graphs admitting an intersection model of intervals on a line s.t. -
The Hadwiger Number, Chordal Graphs and Ab-Perfection Arxiv
The Hadwiger number, chordal graphs and ab-perfection∗ Christian Rubio-Montiel [email protected] Instituto de Matem´aticas, Universidad Nacional Aut´onomade M´exico, 04510, Mexico City, Mexico Department of Algebra, Comenius University, 84248, Bratislava, Slovakia October 2, 2018 Abstract A graph is chordal if every induced cycle has three vertices. The Hadwiger number is the order of the largest complete minor of a graph. We characterize the chordal graphs in terms of the Hadwiger number and we also characterize the families of graphs such that for each induced subgraph H, (1) the Hadwiger number of H is equal to the maximum clique order of H, (2) the Hadwiger number of H is equal to the achromatic number of H, (3) the b-chromatic number is equal to the pseudoachromatic number, (4) the pseudo-b-chromatic number is equal to the pseudoachromatic number, (5) the arXiv:1701.08417v1 [math.CO] 29 Jan 2017 Hadwiger number of H is equal to the Grundy number of H, and (6) the b-chromatic number is equal to the pseudo-Grundy number. Keywords: Complete colorings, perfect graphs, forbidden graphs characterization. 2010 Mathematics Subject Classification: 05C17; 05C15; 05C83. ∗Research partially supported by CONACyT-Mexico, Grants 178395, 166306; PAPIIT-Mexico, Grant IN104915; a Postdoctoral fellowship of CONACyT-Mexico; and the National scholarship programme of the Slovak republic. 1 1 Introduction Let G be a finite graph. A k-coloring of G is a surjective function & that assigns a number from the set [k] := 1; : : : ; k to each vertex of G.A k-coloring & of G is called proper if any two adjacent verticesf haveg different colors, and & is called complete if for each pair of different colors i; j [k] there exists an edge xy E(G) such that x &−1(i) and y &−1(j). -
Ssp Structure of Some Graph Classes
International Journal of Pure and Applied Mathematics Volume 101 No. 6 2015, 939-948 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: A http://www.ijpam.eu P ijpam.eu SSP STRUCTURE OF SOME GRAPH CLASSES R. Mary Jeya Jothi1, A. Amutha2 1,2Department of Mathematics Sathyabama University Chennai, 119, INDIA Abstract: A Graph G is Super Strongly Perfect if every induced sub graph H of G possesses a minimal dominating set that meets all maximal cliques of H. Strongly perfect, complete bipartite graph, etc., are some of the most important classes of super strongly perfect graphs. Here, we analyse the other classes of super strongly perfect graphs like trivially perfect graphs and very strongly perfect graphs. We investigate the structure of super strongly perfect graph in friendship graphs. Also, we discuss the maximal cliques, colourability and dominating sets in friendship graphs. AMS Subject Classification: 05C75 Key Words: super strongly perfect graph, trivially perfect graph, very strongly perfect graph and friendship graph 1. Introduction Super strongly perfect graph is defined by B.D. Acharya and its characterization has been given as an open problem in 2006 [5]. Many analysation on super strongly perfect graph have been done by us in our previous research work, (i.e.,) we have investigated the classes of super strongly perfect graphs like strongly c 2015 Academic Publications, Ltd. Received: March 12, 2015 url: www.acadpubl.eu 940 R.M.J. Jothi, A. Amutha perfect, complete bipartite graph, etc., [3, 4]. In this paper we have discussed some other classes of super strongly perfect graphs like trivially perfect graph, very strongly perfect graph and friendship graph. -
On Dasgupta's Hierarchical Clustering Objective and Its Relation to Other
On Dasgupta's hierarchical clustering objective and its relation to other graph parameters Svein Høgemo1, Benjamin Bergougnoux1, Ulrik Brandes3, Christophe Paul2, and Jan Arne Telle1 1 Department of Informatics, University of Bergen, Norway 2 LIRMM, CNRS, Univ Montpellier, France 3 Social Networks Lab, ETH Z¨urich, Switzerland Abstract. The minimum height of vertex and edge partition trees are well-studied graph parameters known as, for instance, vertex and edge ranking number. While they are NP-hard to determine in general, linear- time algorithms exist for trees. Motivated by a correspondence with Das- gupta's objective for hierarchical clustering we consider the total rather than maximum depth of vertices as an alternative objective for mini- mization. For vertex partition trees this leads to a new parameter with a natural interpretation as a measure of robustness against vertex removal. As tools for the study of this family of parameters we show that they have similar recursive expressions and prove a binary tree rotation lemma. The new parameter is related to trivially perfect graph completion and there- fore intractable like the other three are known to be. We give polynomial- time algorithms for both total-depth variants on caterpillars and on trees with a bounded number of leaf neighbors. For general trees, we obtain a 2-approximation algorithm. 1 Introduction Clustering is a central problem in data mining and statistics. Although many objective functions have been proposed for (flat) partitions into clusters, hier- archical clustering has long been considered from the perspective of iterated merge (in agglomerative clustering) or split (in divisive clustering) operations.