Unlabelling Signed Graph Colorings and Acyclic Orientations
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I?'!'-Comparability Graphs
Discrete Mathematics 74 (1989) 173-200 173 North-Holland I?‘!‘-COMPARABILITYGRAPHS C.T. HOANG Department of Computer Science, Rutgers University, New Brunswick, NJ 08903, U.S.A. and B.A. REED Discrete Mathematics Group, Bell Communications Research, Morristown, NJ 07950, U.S.A. In 1981, Chv&tal defined the class of perfectly orderable graphs. This class of perfect graphs contains the comparability graphs. In this paper, we introduce a new class of perfectly orderable graphs, the &comparability graphs. This class generalizes comparability graphs in a natural way. We also prove a decomposition theorem which leads to a structural characteriza- tion of &comparability graphs. Using this characterization, we develop a polynomial-time recognition algorithm and polynomial-time algorithms for the clique and colouring problems for &comparability graphs. 1. Introduction A natural way to color the vertices of a graph is to put them in some order v*cv~<” l < v, and then assign colors in the following manner: (1) Consider the vertxes sequentially (in the sequence given by the order) (2) Assign to each Vi the smallest color (positive integer) not used on any neighbor vi of Vi with j c i. We shall call this the greedy coloring algorithm. An order < of a graph G is perfect if for each subgraph H of G, the greedy algorithm applied to H, gives an optimal coloring of H. An obstruction in a ordered graph (G, <) is a set of four vertices {a, b, c, d} with edges ab, bc, cd (and no other edge) and a c b, d CC. Clearly, if < is a perfect order on G, then (G, C) contains no obstruction (because the chromatic number of an obstruction is twu, but the greedy coloring algorithm uses three colors). -
Graph Orientations and Linear Extensions
GRAPH ORIENTATIONS AND LINEAR EXTENSIONS. BENJAMIN IRIARTE Abstract. Given an underlying undirected simple graph, we consider the set of all acyclic orientations of its edges. Each of these orientations induces a par- tial order on the vertices of our graph and, therefore, we can count the number of linear extensions of these posets. We want to know which choice of orien- tation maximizes the number of linear extensions of the corresponding poset, and this problem will be solved essentially for comparability graphs and odd cycles, presenting several proofs. The corresponding enumeration problem for arbitrary simple graphs will be studied, including the case of random graphs; this will culminate in 1) new bounds for the volume of the stable polytope and 2) strong concentration results for our main statistic and for the graph entropy, which hold true a:s: for random graphs. We will then argue that our problem springs up naturally in the theory of graphical arrangements and graphical zonotopes. 1. Introduction. Linear extensions of partially ordered sets have been the object of much attention and their uses and applications remain increasing. Their number is a fundamental statistic of posets, and they relate to ever-recurring problems in computer science due to their role in sorting problems. Still, many fundamental questions about linear extensions are unsolved, including the well-known 1=3-2=3 Conjecture. Efficiently enumerating linear extensions of certain posets is difficult, and the general problem has been found to be ]P-complete in Brightwell and Winkler (1991). Directed acyclic graphs, and similarly, acyclic orientations of simple undirected graphs, are closely related to posets, and their problem-modeling values in several disciplines, including the biological sciences, needs no introduction. -
Arxiv:2003.05578V2 [Math.CO] 5 Apr 2021 Iegah a Efudi 7
SIGNED ANALOGUE OF LINE GRAPHS AND THEIR SMALLEST EIGENVALUES ALEXANDER L. GAVRILYUK, AKIHIRO MUNEMASA, YOSHIO SANO, AND TETSUJI TANIGUCHI Abstract. In this paper, we show that every connected signed graph with smallest eigenvalue strictly greater than 2 and large enough minimum degree is switching equivalent to− a complete graph. This is a signed analogue of a theorem of Hoffman. The proof is based on what we call Hoffman’s limit theorem which we formulate for Hermitian matrices, and also the extension of the concept of Hoffman graph and line graph for the setting of signed graphs. 1. Introduction Let G be a simple graph with the vertices-versus-edges incidence (0, 1)-matrix N. It is well known that the line graph L(G) of G, whose vertices are the edges of G with two edges being adjacent whenever they are incident, has adjacency matrix A(L(G)) = N ⊤N 2I , − |E(G)| and hence its smallest eigenvalue λmin is at least 2. Although this property is not exclusive, a theorem of Cameron, Goethals,− Shult, and Seidel [4], which is one of the most beautiful results in algebraic graph theory, classifies connected graphs having λmin 2. Namely, such a graph L on at least 37 vertices must be a generalized≥ − line graph in the arXiv:2003.05578v2 [math.CO] 5 Apr 2021 sense that its adjacency matrix satisfies A(L)= N ⊤N 2I, − for some (0, 1)-matrix N. (A combinatorial definition of generalized line graphs can± be found in [7].) The proof relies on the classification of root systems in Euclidean space [4]. -
Dessin De Triangulations: Algorithmes, Combinatoire, Et Analyse
Dessin de triangulations: algorithmes, combinatoire, et analyse Eric´ Fusy Projet ALGO, INRIA Rocquencourt et LIX, Ecole´ Polytechnique – p.1/53 Motivations Display of large structures on a planar surface – p.2/53 Planar maps • A planar map is obtained by embedding a planar graph in the plane without edge crossings. • A planar map is defined up to continuous deformation Planar map The same planar map Quadrangulation Triangulation – p.3/53 Planar maps • Planar maps are combinatorial objects • They can be encoded without dealing with coordinates 2 1 Planar map Choice of labels 6 7 4 3 5 Encoding: to each vertex is associated the (cyclic) list of its neighbours in clockwise order 1: (2, 4) 2: (1, 7, 6) 3: (4, 6, 5) 4: (1, 3) 5: (3, 7) 6: (3, 2, 7) 7: (2, 5, 6) – p.4/53 Combinatorics of maps Triangulations Quadrangulations Tetravalent 3 spanning trees 2 spanning trees eulerian orientation = 2(4n−3)! = 2(3n−3)! = 2·3n(2n)! |Tn| n!(3n−2)! |Qn| n!(2n−2)! |En| n!(n+2)! ⇒ Tutte, Schaeffer, Schnyder, De Fraysseix et al... – p.5/53 A particular family of triangulations • We consider triangulations of the 4-gon (the outer face is a quadrangle) • Each 3-cycle delimits a face (irreducibility) Forbidden Irreducible – p.6/53 Transversal structures We define a transversal structure using local conditions Inner edges are colored blue or red and oriented: Inner vertex ⇒ Border vertices ⇒ Example: ⇒ – p.7/53 Link with bipolar orientations bipolar orientation = acyclic orientation with a unique minimum and a unique maximum The blue (resp. -
Common-Edge Signed Graph of a Signed Graph
J. Indones. Math. Soc. Vol. 16, No. 2 (2010), pp. 105–113. COMMON-EDGE SIGNED GRAPH OF A SIGNED GRAPH P. Siva Kota Reddy1, E. Sampathkumar2 and M. S. Subramanya3 1Department of Mathematics, Acharya Institute of Technology, Soldevanahalli, Bangalore 560 090, India, [email protected] 2Department of Studies in Mathematics, University of Mysore, Manasagangotri, Mysore 570 006, India, [email protected] 3Department of Studies in Mathematics, University of Mysore, Manasagangotri, Mysore 570 006, India, subramanya ms@rediffmail.com Abstract. A Smarandachely k-signed graph (Smarandachely k-marked graph) is an ordered pair S = (G, σ)(S = (G, µ)) where G = (V, E) is a graph called underlying graph of S and σ : E → (e1, e2, ..., ek)(µ : V → (e1, e2, ..., ek)) is a function, where each ei ∈ {+, −}. Particularly, a Smarandachely 2-signed graph or Smarandachely 2-marked graph is abbreviated a signed graph or a marked graph. The common- edge graph of a graph G = (V, E) is a graph CE (G) = (VE ,EE ), where VE = {A ⊆ V ; |A| = 3, and A is a connected set} and two vertices in VE are adjacent if they have an edge of G in common. Analogously, one can define the common-edge ′ signed graph of a signed graph S = (G, σ) as a signed graph CE (S) = (CE (G), σ ), where CE (G) is the underlying graph of CE (S), where for any edge (e1e2, e2e3) ′ in CE (S), σ (e1e2, e2e3) = σ(e1e2)σ(e2e3). It is shown that for any signed graph S, its common-edge signed graph CE (S) is balanced. -
Acyclic Orientations of Graphsଁ Richard P
Discrete Mathematics 306 (2006) 905–909 www.elsevier.com/locate/disc Acyclic orientations of graphsଁ Richard P. Stanley Department of Mathematics, University of California, Berkeley, Calif. 94720, USA Abstract Let G be a finite graph with p vertices and its chromatic polynomial. A combinatorial interpretation is given to the positive p p integer (−1) (−), where is a positive integer, in terms of acyclic orientations of G. In particular, (−1) (−1) is the number of acyclic orientations of G. An application is given to the enumeration of labeled acyclic digraphs. An algebra of full binomial type, in the sense of Doubilet–Rota–Stanley, is constructed which yields the generating functions which occur in the above context. © 1973 Published by Elsevier B.V. 1. The chromatic polynomial with negative arguments Let G be a finite graph, which we assume to be without loops or multiple edges. Let V = V (G) denote the set of vertices of G and X = X(G) the set of edges. An edge e ∈ X is thought of as an unordered pair {u, v} of two distinct vertices. The integers p and q denote the cardinalities of V and X, respectively. An orientation of G is an assignment of a direction to each edge {u, v}, denoted by u → v or v → u, as the case may be. An orientation of G is said to be acyclic if it has no directed cycles. Let () = (G, ) denote the chromatic polynomial of G evaluated at ∈ C.If is a non-negative integer, then () has the following rather unorthodox interpretation. Proposition 1.1. -
Parameterized Mixed Graph Coloring
Parameterized mixed graph coloring Downloaded from: https://research.chalmers.se, 2021-09-26 10:22 UTC Citation for the original published paper (version of record): Damaschke, P. (2019) Parameterized mixed graph coloring Journal of Combinatorial Optimization, 38(2): 362-374 http://dx.doi.org/10.1007/s10878-019-00388-z N.B. When citing this work, cite the original published paper. research.chalmers.se offers the possibility of retrieving research publications produced at Chalmers University of Technology. It covers all kind of research output: articles, dissertations, conference papers, reports etc. since 2004. research.chalmers.se is administrated and maintained by Chalmers Library (article starts on next page) Journal of Combinatorial Optimization (2019) 38:362–374 https://doi.org/10.1007/s10878-019-00388-z Parameterized Mixed Graph Coloring Peter Damaschke1 Published online: 7 February 2019 © The Author(s) 2019 Abstract Coloring of mixed graphs that contain both directed arcs and undirected edges is relevant for scheduling of unit-length jobs with precedence constraints and conflicts. The classic GHRV theorem (attributed to Gallai, Hasse, Roy, and Vitaver) relates graph coloring to longest paths. It can be extended to mixed graphs. In the present paper we further extend the GHRV theorem to weighted mixed graphs. As a byproduct this yields a kernel and a parameterized algorithm (with the number of undirected edges as parameter) that is slightly faster than the brute-force algorithm. The parameter is natural since the directed version is polynomial whereas the undirected version is NP- complete. Furthermore we point out a new polynomial case where the edges form a clique. -
The Number of Orientations Having No Fixed Tournament
The number of orientations having no fixed tournament Noga Alon ∗ Raphael Yuster y Abstract Let T be a fixed tournament on k vertices. Let D(n; T ) denote the maximum number of tk 1(n) orientations of an n-vertex graph that have no copy of T . We prove that D(n; T ) = 2 − for all sufficiently (very) large n, where tk 1(n) is the maximum possible number of edges of a − graph on n vertices with no Kk, (determined by Tur´an'sTheorem). The proof is based on a directed version of Szemer´edi'sregularity lemma together with some additional ideas and tools from Extremal Graph Theory, and provides an example of a precise result proved by applying this lemma. For the two possible tournaments with three vertices we obtain separate proofs that n2=4 avoid the use of the regularity lemma and therefore show that in these cases D(n; T ) = 2b c already holds for (relatively) small values of n. 1 Introduction All graphs considered here are finite and simple. For standard terminology on undirected and directed graphs the reader is referred to [4]. Let T be some fixed tournament. An orientation of an undirected graph G = (V; E) is called T -free if it does not contain T as a subgraph. Let D(G; T ) denote the number of orientations of G that are T -free. Let D(n; T ) denote the maximum possible value of D(G; T ) where G is an n-vertex graph. In this paper we determine D(n; T ) precisely for every fixed tournament T and all sufficiently large n. -
Voter Model on Signed Social Networks
Voter Model on Signed Social Networks Yanhua Li†∗, Wei Chen§, Yajun Wang§ and Zhi-Li Zhang† †Dept. of Computer Science & Engineering, Univ. of Minnesota, Twin Cities § Microsoft Research {yanhua,zhzhang}@cs.umn.edu,{weic,yajunw}@microsoft.com Abstract Online social networks (OSNs) are becoming increasingly popular in recent years, which have generated great interest in studying the influence diffusion and influence maximization with applications to online viral mar- keting. Existing studies focus on social networks with only friendship re- lations, whereas the foe or enemy relations that commonly exist in many OSNs, e.g., Epinions and Slashdot, are completely ignored. In this paper, we make the first attempt to investigate the influence diffusion and influence maximization in OSNs with both friend and foe relations, which are mod- eled using positive and negative edges on signed networks. In particular, we extend the classic voter model to signed networks and analyze the dynamics of influence diffusion of two opposite opinions. We first provide systemat- ic characterization of both short-term and long-term dynamics of influence diffusion in this model, and illustrate that the steady state behaviors of the dynamics depend on three types of graph structures, which we refer to as balanced graphs, anti-balanced graphs, and strictly unbalanced graphs. We then apply our results to solve the influence maximization problem and de- velop efficient algorithms to select initial seeds of one opinion that maximize either its short-term influence coverage or long-term steady state influence coverage. Extensive simulation results on both synthetic and real-world net- works, such as Epinions and Slashdot, confirm our theoretical analysis on influence diffusion dynamics, and demonstrate the efficacy of our influence maximization algorithm over other heuristic algorithms. -
List Homomorphism Problems for Signed Graphs
List homomorphism problems for signed graphs Jan Bok Computer Science Institute, Faculty of Mathematics and Physics, Charles University, Czech Republic [email protected]ff.cuni.cz Richard Brewster Department of Mathematics and Statistics, Thompson Rivers University, Canada [email protected] Tomás Feder 268 Waverley St., Palo Alto, USA [email protected] Pavol Hell School of Computing Science, Simon Fraser University, Canada [email protected] Nikola Jedličková Department of Applied Mathematics, Faculty of Mathematics and Physics, Charles University, Czech Republic [email protected]ff.cuni.cz Abstract We consider homomorphisms of signed graphs from a computational perspective. In particular, we study the list homomorphism problem seeking a homomorphism of an input signed graph (G, σ), equipped with lists L(v) ⊆ V (H), v ∈ V (G), of allowed images, to a fixed target signed graph (H, π). The complexity of the similar homomorphism problem without lists (corresponding to all lists being L(v) = V (H)) has been previously classified by Brewster and Siggers, but the list version remains open and appears difficult. We illustrate this difficulty by classifying the complexity of the problem when H is a tree (with possible loops). The tools we develop will be useful for classifications of other classes of signed graphs, and we illustrate this by classifying the complexity of irreflexive signed graphs in which the unicoloured edges form some simple structures, namely paths or cycles. The structure of the signed graphs in the polynomial cases is interesting, suggesting they may constitute a nice class of signed graphs analogous to the so-called bi-arc graphs (which characterized the polynomial cases of list homomorphisms to unsigned graphs). -
The Connectivity of Acyclic Orientation Graphs Carla D
Discrete Mathematics 184 (1998) 281{287 Note The connectivity of acyclic orientation graphs Carla D. Savagea;∗;1, Cun-Quan Zhangb;2 a Department of Computer Science, North Carolina State University, Raleigh, NC 27695-8206, USA b Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310, USA Received 27 July 1995; received in revised form 5 May 1997; accepted 19 May 1997 Abstract The acyclic orientation graph, AO(G), of an undirected graph, G, is the graph whose vertices are the acyclic orientations of G and whose edges are the pairs of orientations di ering only by the reversal of one edge. Edelman (1984) has observed that it follows from results on polytopes that when G is simple, the connectivity of AO(G) is at least n − c, where n is the number of vertices and c is the number of components of G. In this paper we give a simple graph-theoretic proof of this fact. Our proof uses a result of independent interest. We establish that if H is a triangle-free graph with minimum degree at least k, and the graph obtained by contracting the edges of a matching in H is k-connected, then H is k-connected. The connectivity bound on AO(G) is tight for various graphs including Kn, Kp; q, and trees. Applications and extensions are discussed, as well as the connection with polytopes. c 1998 Elsevier Science B.V. All rights reserved 1. Introduction For an undirected graph G and an acyclic orientation D of G, an edge e of D is called dependent if reversing the direction of e creates a directed cycle in D; otherwise, e is independent [18]. -
Arxiv:1911.01113V1 [Math.CO] 4 Nov 2019 Whenever 00MSC: 2000 Complement
On eigenvalue multiplicity in signed graphs Farzaneh Ramezani Department of Mathematics, K.N. Toosi University of Technology P.O. Box 16315-1618, Teheran, Iran. Peter Rowlinson Mathematics and Statistics Group, Division of Computing Science and Mathematics, University of Stirling Scotland FK9 4LA, United Kingdom. Zoran Stani´c Faculty of Mathematics, University of Belgrade Studentski trg 16, 11 000 Belgrade, Serbia. Abstract Given a signed graph Σ with n vertices, let µ be an eigenvalue of Σ, and let t be the codimension of the corresponding eigenspace. We prove that t + 2 n ≤ 3 whenever µ / 0, 1, 1 . We show that this bound is sharp by providing ∈ { − } examples of signed graphs in which it is attained. We also discuss particular cases in which the bound can be decreased. Keywords: Signed graph, Eigenvalue multiplicity, Net-regular signed graph, Star complement. arXiv:1911.01113v1 [math.CO] 4 Nov 2019 2000 MSC: 05C22, 05C50 1. Introduction A signed graph Σ is a pair (G, σ), where G = (V, E) is an (unsigned) graph, called the underlying graph, and σ : E 1, 1 is the sign function −→ { − } Email addresses: [email protected] (Farzaneh Ramezani), [email protected] (Peter Rowlinson), [email protected] (Zoran Stani´c) Preprint submitted to DM. November 5, 2019 or the signature. The edge set E consists of positive and negative edges. Throughout the paper we interpret a graph as a signed graph in which all edges are positive. The degree di of a vertex i coincides with its degree in the underlying ± graph. Its net-degree di is the difference between the numbers of positive and negative edges incident with it.