Bounded Cliquewidth Are Polynomially Χ-Bounded
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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. -
Domination in Circle Graphs
Circles graphs Dominating set Some positive results Open Problems Domination in circle graphs Nicolas Bousquet Daniel Gon¸calves George B. Mertzios Christophe Paul Ignasi Sau St´ephanThomass´e WG 2012 Domination in circle graphs Circles graphs Dominating set Some positive results Open Problems 1 Circles graphs 2 Dominating set 3 Some positive results 4 Open Problems Domination in circle graphs W [1]-hardness Under some algorithmic hypothesis, the W [1]-hard problems do not admit FPT algorithms. Circles graphs Dominating set Some positive results Open Problems Parameterized complexity FPT A problem parameterized by k is FPT (Fixed Parameter Tractable) iff it admits an algorithm which runs in time Poly(n) · f (k) for any instances of size n and of parameter k. Domination in circle graphs Circles graphs Dominating set Some positive results Open Problems Parameterized complexity FPT A problem parameterized by k is FPT (Fixed Parameter Tractable) iff it admits an algorithm which runs in time Poly(n) · f (k) for any instances of size n and of parameter k. W [1]-hardness Under some algorithmic hypothesis, the W [1]-hard problems do not admit FPT algorithms. Domination in circle graphs Circles graphs Dominating set Some positive results Open Problems Circle graphs Circle graph A circle graph is a graph which can be represented as an intersection graph of chords in a circle. 3 3 4 2 5 4 2 6 1 1 5 7 7 6 Domination in circle graphs Independent dominating sets. Connected dominating sets. Total dominating sets. All these problems are NP-complete. Circles graphs Dominating set Some positive results Open Problems Dominating set 3 4 5 2 6 1 7 Dominating set Set of chords which intersects all the chords of the graph. -
Clay Mathematics Institute 2005 James A
Contents Clay Mathematics Institute 2005 James A. Carlson Letter from the President 2 The Prize Problems The Millennium Prize Problems 3 Recognizing Achievement 2005 Clay Research Awards 4 CMI Researchers Summary of 2005 6 Workshops & Conferences CMI Programs & Research Activities Student Programs Collected Works James Arthur Archive 9 Raoul Bott Library CMI Profile Interview with Research Fellow 10 Maria Chudnovsky Feature Article Can Biology Lead to New Theorems? 13 by Bernd Sturmfels CMI Summer Schools Summary 14 Ricci Flow, 3–Manifolds, and Geometry 15 at MSRI Program Overview CMI Senior Scholars Program 17 Institute News Euclid and His Heritage Meeting 18 Appointments & Honors 20 CMI Publications Selected Articles by Research Fellows 27 Books & Videos 28 About CMI Profile of Bow Street Staff 30 CMI Activities 2006 Institute Calendar 32 2005 Euclid: www.claymath.org/euclid James Arthur Collected Works: www.claymath.org/cw/arthur Hanoi Institute of Mathematics: www.math.ac.vn Ramanujan Society: www.ramanujanmathsociety.org $.* $MBZ.BUIFNBUJDT*OTUJUVUF ".4 "NFSJDBO.BUIFNBUJDBM4PDJFUZ In addition to major,0O"VHVTU BUUIFTFDPOE*OUFSOBUJPOBM$POHSFTTPG.BUIFNBUJDJBOT ongoing activities such as JO1BSJT %BWJE)JMCFSUEFMJWFSFEIJTGBNPVTMFDUVSFJOXIJDIIFEFTDSJCFE the summer schools,UXFOUZUISFFQSPCMFNTUIBUXFSFUPQMBZBOJOnVFOUJBMSPMFJONBUIFNBUJDBM the Institute undertakes a 5IF.JMMFOOJVN1SJ[F1SPCMFNT SFTFBSDI"DFOUVSZMBUFS PO.BZ BUBNFFUJOHBUUIF$PMMÒHFEF number of smaller'SBODF UIF$MBZ.BUIFNBUJDT*OTUJUVUF $.* BOOPVODFEUIFDSFBUJPOPGB special projects -
Coloring Clean and K4-Free Circle Graphs 401
Coloring Clean and K4-FreeCircleGraphs Alexandr V. Kostochka and Kevin G. Milans Abstract A circle graph is the intersection graph of chords drawn in a circle. The best-known general upper bound on the chromatic number of circle graphs with clique number k is 50 · 2k. We prove a stronger bound of 2k − 1 for graphs in a simpler subclass of circle graphs, called clean graphs. Based on this result, we prove that the chromatic number of every circle graph with clique number at most 3 is at most 38. 1 Introduction Recall that the chromatic number of a graph G, denoted χ(G), is the minimum size of a partition of V(G) into independent sets. A clique is a set of pairwise adjacent vertices, and the clique number of G, denoted ω(G), is the maximum size of a clique in G. Vertices in a clique must receive distinct colors, so χ(G) ≥ ω(G) for every graph G. In general, χ(G) cannot be bounded above by any function of ω(G). Indeed, there are triangle-free graphs with arbitrarily large chromatic number [4, 18]. When graphs have additional structure, it may be possible to bound the chromatic number in terms of the clique number. A family of graphs G is χ-bounded if there is a function f such that χ(G) ≤ f (ω(G)) for each G ∈G. Some families of intersection graphs of geometric objects have been shown to be χ-bounded (see e.g. [8,11,12]). Recall that the intersection graph of a family of sets has a vertex A.V. -
Some Remarks on Even-Hole-Free Graphs
Some remarks on even-hole-free graphs Zi-Xia Song∗ Department of Mathematics, University of Central Florida, Orlando, FL 32816, USA Abstract A vertex of a graph is bisimplicial if the set of its neighbors is the union of two cliques; a graph is quasi-line if every vertex is bisimplicial. A recent result of Chudnovsky and Seymour asserts that every non-empty even-hole-free graph has a bisimplicial vertex. Both Hadwiger’s conjecture and the Erd˝os-Lov´asz Tihany conjecture have been shown to be true for quasi-line graphs, but are open for even-hole-free graphs. In this note, we prove that for all k ≥ 7, every even-hole-free graph with no Kk minor is (2k − 5)-colorable; every even-hole-free graph G with ω(G) < χ(G) = s + t − 1 satisfies the Erd˝os-Lov´asz Tihany conjecture provided that t ≥ s>χ(G)/3. Furthermore, we prove that every 9-chromatic graph G with ω(G) ≤ 8 has a K4 ∪ K6 minor. Our proofs rely heavily on the structural result of Chudnovsky and Seymour on even-hole-free graphs. 1 Introduction All graphs in this paper are finite and simple. For a graph G, we use V (G) to denote the vertex set, E(G) the edge set, |G| the number of vertices, e(G) the number of edges, δ(G) the minimum degree, ∆(G) the maximum degree, α(G) the independence number, ω(G) the clique number and χ(G) the chromatic number. A graph H is a minor of a graph G if H can be obtained from a subgraph of G by contracting edges. -
Open Problems on Graph Drawing
Open problems on Graph Drawing Alexandros Angelopoulos Corelab E.C.E - N.T.U.A. February 17, 2014 Outline Introduction - Motivation - Discussion Variants of thicknesses Thickness Geometric thickness Book thickness Bounds Complexity Related problems & future work 2/ Motivation: Air Traffic Management Separation -VerticalVertical - Lateral - Longitudinal 3/ Motivation: Air Traffic Management : Maximization of \free flight” airspace c d c d X f f i1 i4 i0 i2 i3 i5 e e Y a b a b 8 Direct-to flight (as a choice among \free flight") increases the complexity of air traffic patterns Actually... 4 Direct-to flight increases the complexity of air traffic patterns and we have something to study... 4/ Motivation: Air Traffic Management 5/ How to model? { Graph drawing & thicknesses Geometric thickness (θ¯) Book thickness (bt) Dillencourt et al. (2000) Bernhart and Kainen (1979) : only straight lines : convex positioning of nodes v4 v5 v1 v2 θ(G) ≤ θ¯(G) ≤ bt(G) v5 v3 v0 v4 4 v1 Applications in VLSI & graph visualizationv3 Thickness (θ) v0 8 θ, θ¯, bt characterize the graph (minimizations over all allowedv2 drawings) Tutte (1963), \classical" planar decomposition 6/ Geometric graphs and graph drawings Definition 1.1 (Geometric graph, Bose et al. (2006), many Erd¨ospapers). A geometric graph G is a pair (V (G);E(G)) where V (G) is a set of points in the plane in general position and E(G) is set of closed segments with endpoints in V (G). Elements of V (G) are vertices and elements of E(G) are edges, so we can associate this straight-line drawing with the underlying abstract graph G(V; E). -
The Structure of Claw-Free Graphs
The structure of claw-free graphs Maria Chudnovsky and Paul Seymour Abstract A graph is claw-free if no vertex has three pairwise nonadjacent neighbours. At first sight, there seem to be a great variety of types of claw-free graphs. For instance, there are line graphs, the graph of the icosahedron, complements of triangle-free graphs, and the Schl¨afli graph (an amazingly highly-symmetric graph with 27 vertices), and more; for instance, if we arrange vertices in a circle, choose some intervals from the circle, and make the vertices in each interval adjacent to each other, the graph we produce is claw-free. There are several other such examples, which we regard as \basic" claw-free graphs. Nevertheless, it is possible to prove a complete structure theorem for claw- free graphs. We have shown that every connected claw-free graph can be ob- tained from one of the basic claw-free graphs by simple expansion operations. In this paper we explain the precise statement of the theorem, sketch the proof, and give a few applications. 1 Introduction A graph is claw-free if no vertex has three pairwise nonadjacent neighbours. (Graphs in this paper are finite and simple.) Line graphs are claw-free, and it has long been recognized that claw-free graphs are an interesting generalization of line graphs, sharing some of the same properties. For instance, Minty [16] showed in 1980 that there is a polynomial-time algorithm to find a stable set of maximum weight in a claw-free graph, generalizing the algorithm of Edmonds [9, 10] to find a maximum weight matching in a graph. -
Local Page Numbers
Local Page Numbers Bachelor Thesis of Laura Merker At the Department of Informatics Institute of Theoretical Informatics Reviewers: Prof. Dr. Dorothea Wagner Prof. Dr. Peter Sanders Advisor: Dr. Torsten Ueckerdt Time Period: May 22, 2018 – September 21, 2018 KIT – University of the State of Baden-Wuerttemberg and National Laboratory of the Helmholtz Association www.kit.edu Statement of Authorship I hereby declare that this document has been composed by myself and describes my own work, unless otherwise acknowledged in the text. I declare that I have observed the Satzung des KIT zur Sicherung guter wissenschaftlicher Praxis, as amended. Ich versichere wahrheitsgemäß, die Arbeit selbstständig verfasst, alle benutzten Hilfsmittel vollständig und genau angegeben und alles kenntlich gemacht zu haben, was aus Arbeiten anderer unverändert oder mit Abänderungen entnommen wurde, sowie die Satzung des KIT zur Sicherung guter wissenschaftlicher Praxis in der jeweils gültigen Fassung beachtet zu haben. Karlsruhe, September 21, 2018 iii Abstract A k-local book embedding consists of a linear ordering of the vertices of a graph and a partition of its edges into sets of edges, called pages, such that any two edges on the same page do not cross and every vertex has incident edges on at most k pages. Here, two edges cross if their endpoints alternate in the linear ordering. The local page number pl(G) of a graph G is the minimum k such that there exists a k-local book embedding for G. Given a graph G and a vertex ordering, we prove that it is NP-complete to decide whether there exists a k-local book embedding for G with respect to the given vertex ordering for any fixed k ≥ 3. -
A Fast Heuristic Algorithm Based on Verification and Elimination Methods for Maximum Clique Problem
A Fast Heuristic Algorithm Based on Verification and Elimination Methods for Maximum Clique Problem Sabu .M Thampi * Murali Krishna P L.B.S College of Engineering, LBS College of Engineering Kasaragod, Kerala-671542, India Kasaragod, Kerala-671542, India [email protected] [email protected] Abstract protein sequences. A major application of the maximum clique problem occurs in the area of coding A clique in an undirected graph G= (V, E) is a theory [1]. The goal here is to find the largest binary ' code, consisting of binary words, which can correct a subset V ⊆ V of vertices, each pair of which is connected by an edge in E. The clique problem is an certain number of errors. A maximal clique is a clique that is not a proper set optimization problem of finding a clique of maximum of any other clique. A maximum clique is a maximal size in graph . The clique problem is NP-Complete. We have succeeded in developing a fast algorithm for clique that has the maximum cardinality. In many maximum clique problem by employing the method of applications, the underlying problem can be formulated verification and elimination. For a graph of size N as a maximum clique problem while in others a N subproblem of the solution procedure consists of there are 2 sub graphs, which may be cliques and finding a maximum clique. This necessitates the hence verifying all of them, will take a long time. Idea is to eliminate a major number of sub graphs, which development of fast and approximate algorithms for cannot be cliques and verifying only the remaining sub the problem. -
Strong Perfect Graph Theorem a Graph G Is Perfect If and Only If Neither G Nor Its Complement G¯ Contains an Induced Odd Circuit of Length ≥ 5
THEOREM OF THE DAY The Strong Perfect Graph Theorem A graph G is perfect if and only if neither G nor its complement G¯ contains an induced odd circuit of length ≥ 5. An induced odd circuit is an odd-length, circular sequence of edges having no ‘short-circuit’ edges across it, while G¯ is the graph obtained by replacing edges in G by non-edges and vice-versa. A perfect graph G is one in which, for every induced subgraph H, the size of a largest clique (that is, maximal complete subgraph) is equal to the chromatic number of H (the least number of vertex colours guaranteeing no identically coloured adjacent vertices). This deep and subtle property is confirmed by today’s theorem to have a surprisingly simple characterisation, whereby the railway above is clearly perfect. The railway scenario illustrates just one way in which perfect graphs are important. We wish to dispatch goods every day from depots v1, v2,..., choosing the best-stocked depots but subject to the constraint that we nominate at most one depot per network clique, so as to avoid head-on collisions. The depot-clique incidence relationship is modelled as a 0-1 matrix and we attempt to replicate our constraint numerically from this as a set of inequalities (far right, bottom). Now we may optimise dispatch as a standard linear programming problem unless... the optimum allocates a fractional amount to each depot, failing to respect the one-depot-per-clique constraint. A 1975 theorem of V. Chv´atal asserts: if a clique incidence matrix is the constraint matrix for a linear programme then an integer optimal solution is guaranteed if and only if the underlying network is a perfect graph. -
Mathematics People
Mathematics People information, sometimes even one incorrect bit can de- Chudnovsky and Spielman stroy the integrity of the data stream; adding verification Selected as MacArthur Fellows ‘codes’ to the data helps to test its accuracy. Spielman and collaborators developed several families of codes Maria Chudnovsky of Columbia University and Dan- that optimize speed and reliability, some approaching the iel Spielman of Yale University have been named Mac- theoretical limit of performance. One, an enhanced version Arthur Fellows for 2012. Each Fellow receives a grant of of low-density parity checking, is now used to broadcast US$500,000 in support, with no strings attached, over the and decode high-definition television transmissions. In a next five years. separate line of research, Spielman resolved an enduring Chudnovsky was honored for her work on the classifica- mystery of computer science: why a venerable algorithm tions and properties of graphs. The prize citation reads, for optimization (e.g., to compute the fastest route to the “Maria Chudnovsky is a mathematician who investigates airport, picking up three friends along the way) usually the fundamental principles of graph theory. In mathemat- works better in practice than theory would predict. He and ics, a graph is an abstraction that represents a set of similar a collaborator proved that small amounts of randomness things and the connections between them—e.g., cities and convert worst-case conditions into problems that can be the roads connecting them, networks of friendship among solved much faster. This finding holds enormous practi- people, websites and their links to other sites. When used cal implications for a myriad of calculations in science, to solve real-world problems, like efficient scheduling for engineering, social science, business, and statistics that an airline or package delivery service, graphs are usually depend on the simplex algorithm or its derivatives. -
Arxiv:1908.08911V1 [Cs.DS] 23 Aug 2019
Parameterized Algorithms for Book Embedding Problems? Sujoy Bhore1, Robert Ganian1, Fabrizio Montecchiani2, and Martin N¨ollenburg1 1 Algorithms and Complexity Group, TU Wien, Vienna, Austria fsujoy,rganian,[email protected] 2 Engineering Department, University of Perugia, Perugia, Italy [email protected] Abstract. A k-page book embedding of a graph G draws the vertices of G on a line and the edges on k half-planes (called pages) bounded by this line, such that no two edges on the same page cross. We study the problem of determining whether G admits a k-page book embedding both when the linear order of the vertices is fixed, called Fixed-Order Book Thickness, or not fixed, called Book Thickness. Both problems are known to be NP-complete in general. We show that Fixed-Order Book Thickness and Book Thickness are fixed-parameter tractable parameterized by the vertex cover number of the graph and that Fixed- Order Book Thickness is fixed-parameter tractable parameterized by the pathwidth of the vertex order. 1 Introduction A k-page book embedding of a graph G is a drawing that maps the vertices of G to distinct points on a line, called spine, and each edge to a simple curve drawn inside one of k half-planes bounded by the spine, called pages, such that no two edges on the same page cross [20,25]; see Fig.1 for an illustration. This kind of layout can be alternatively defined in combinatorial terms as follows. A k-page book embedding of G is a linear order ≺ of its vertices and a coloring of its edges which guarantee that no two edges uv, wx of the same color have their vertices ordered as u ≺ w ≺ v ≺ x.