Characterisations and Examples of Graph Classes with Bounded Expansion
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Arxiv:1908.08938V1 [Cs.DS] 23 Aug 2019 U ≺ W ≺ X ≺ V (Under the Same Assumptions As Above)
Mixed Linear Layouts: Complexity, Heuristics, and Experiments Philipp de Col, Fabian Klute, and Martin N¨ollenburg Algorithms and Complexity Group, TU Wien, Vienna, Austria [email protected],ffklute,[email protected] Abstract. A k-page linear graph layout of a graph G = (V; E) draws all vertices along a line ` and each edge in one of k disjoint halfplanes called pages, which are bounded by `. We consider two types of pages. In a stack page no two edges should cross and in a queue page no edge should be nested by another edge. A crossing (nesting) in a stack (queue) page is called a conflict. The algorithmic problem is twofold and requires to compute (i) a vertex ordering and (ii) a page assignment of the edges such that the resulting layout is either conflict-free or conflict-minimal. While linear layouts with only stack or only queue pages are well-studied, mixed s-stack q-queue layouts for s; q ≥ 1 have received less attention. We show NP-completeness results on the recognition problem of certain mixed linear layouts and present a new heuristic for minimizing conflicts. In a computational experiment for the case s; q = 1 we show that the new heuristic is an improvement over previous heuristics for linear layouts. 1 Introduction Linear graph layouts, in particular book embeddings [1,11] (also known as stack layouts) and queue layouts [8,9], form a classic research topic in graph drawing with many applications beyond graph visualization as surveyed by Dujmovi´cand Wood [5]. A k-page linear layout Γ = (≺; P) of a graph G = (V; E) consists of an order ≺ on the vertex set V and a partition of E into k subsets P = fP1;:::;Pkg called pages. -
Planar Graphs Have Bounded Queue-Number
2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS) Planar Graphs have Bounded Queue-Number Vida Dujmovic´∗, Gwenaël Joret†, Piotr Micek‡, Pat Morin§, Torsten Ueckerdt¶, David R. Wood ∗ School of Computer Science and Electrical Eng., University of Ottawa, Canada ([email protected]) † Département d’Informatique, Université Libre de Bruxelles, Brussels, Belgium ([email protected]) ‡ Faculty of Mathematics and Computer Science, Jagiellonian University, Poland ([email protected]) § School of Computer Science, Carleton University, Ottawa, Canada ([email protected]) ¶ Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany ([email protected]) School of Mathematics, Monash University, Melbourne, Australia ([email protected]) Abstract—We show that planar graphs have bounded queue- open whether every graph has stack-number bounded by a number, thus proving a conjecture of Heath, Leighton and function of its queue-number, or whether every graph has Rosenberg from 1992. The key to the proof is a new structural queue-number bounded by a function of its stack-number tool called layered partitions, and the result that every planar graph has a vertex-partition and a layering, such that each [1,2]. part has a bounded number of vertices in each layer, and the Planar graphs are the simplest class of graphs where it is quotient graph has bounded treewidth. This result generalises unknown whether both stack and queue-number are bounded. for graphs of bounded Euler genus. Moreover, we prove that In particular, Buss and Shor [3] first proved that planar every graph in a minor-closed class has such a layered partition graphs have bounded stack-number; the best known upper if and only if the class excludes some apex graph. -
Homomorphisms of 3-Chromatic Graphs
Discrete Mathematics 54 (1985) 127-132 127 North-Holland HOMOMORPHISMS OF 3-CHROMATIC GRAPHS Michael O. ALBERTSON Department of Mathematics, Smith College, Northampton, MA 01063, U.S.A. Karen L. COLLINS Department of Mathematics, M.L T., Cambridge, MA 02139, U.S.A. Received 29 March 1984 Revised 17 August 1984 This paper examines the effect of a graph homomorphism upon the chromatic difference sequence of a graph. Our principal result (Theorem 2) provides necessary conditions for the existence of a homomorphism onto a prescribed target. As a consequence we note that iterated cartesian products of the Petersen graph form an infinite family of vertex transitive graphs no one of which is the homomorphic image of any other. We also prove that there is a unique minimal element in the homomorphism order of 3-chromatic graphs with non-monotonic chromatic difference sequences (Theorem 1). We include a brief guide to some recent papers on graph homomorphisms. A homomorphism f from a graph G to a graph H is a mapping from the vertex set of G (denoted by V(G)) to the vertex set of H which preserves edges, i.e., if (u, v) is an edge in G, then (f(u), f(v)) is an edge in H. If in addition f is onto V(H) and each edge in H is the image of some edge in G, then f is said to be onto and H is called a homomorphic image of G. We define the homomorphism order ~> on the set of finite connected graphs as G ~>H if there exists a homomorphism which maps G onto H. -
Packing and Covering Dense Graphs
Packing and Covering Dense Graphs Noga Alon ∗ Yair Caro y Raphael Yuster z Abstract Let d be a positive integer. A graph G is called d-divisible if d divides the degree of each vertex of G. G is called nowhere d-divisible if no degree of a vertex of G is divisible by d. For a graph H, gcd(H) denotes the greatest common divisor of the degrees of the vertices of H. The H-packing number of G is the maximum number of pairwise edge disjoint copies of H in G. The H-covering number of G is the minimum number of copies of H in G whose union covers all edges of G. Our main result is the following: For every fixed graph H with gcd(H) = d, there exist positive constants (H) and N(H) such that if G is a graph with at least N(H) vertices and has minimum degree at least (1 − (H)) G , then the H-packing number of G and the H-covering number of G can be computed j j in polynomial time. Furthermore, if G is either d-divisible or nowhere d-divisible, then there is a closed formula for the H-packing number of G, and the H-covering number of G. Further extensions and solutions to related problems are also given. 1 Introduction All graphs considered here are finite, undirected and simple, unless otherwise noted. For the standard graph-theoretic terminology the reader is referred to [1]. Let H be a graph without isolated vertices. An H-covering of a graph G is a set L = G1;:::;Gs of subgraphs of G, where f g each subgraph is isomorphic to H, and every edge of G appears in at least one member of L. -
Graph Operations and Upper Bounds on Graph Homomorphism Counts
Graph Operations and Upper Bounds on Graph Homomorphism Counts Luke Sernau March 9, 2017 Abstract We construct a family of countexamples to a conjecture of Galvin [5], which stated that for any n-vertex, d-regular graph G and any graph H (possibly with loops), n n d d hom(G, H) ≤ max hom(Kd,d,H) 2 , hom(Kd+1,H) +1 , n o where hom(G, H) is the number of homomorphisms from G to H. By exploiting properties of the graph tensor product and graph exponentiation, we also find new infinite families of H for which the bound stated above on hom(G, H) holds for all n-vertex, d-regular G. In particular we show that if HWR is the complete looped path on three vertices, also known as the Widom-Rowlinson graph, then n d hom(G, HWR) ≤ hom(Kd+1,HWR) +1 for all n-vertex, d-regular G. This verifies a conjecture of Galvin. arXiv:1510.01833v3 [math.CO] 8 Mar 2017 1 Introduction Graph homomorphisms are an important concept in many areas of graph theory. A graph homomorphism is simply an adjacency-preserving map be- tween a graph G and a graph H. That is, for given graphs G and H, a function φ : V (G) → V (H) is said to be a homomorphism from G to H if for every edge uv ∈ E(G), we have φ(u)φ(v) ∈ E(H) (Here, as throughout, all graphs are simple, meaning without multi-edges, but they are permitted 1 to have loops). -
Embedding Trees in Dense Graphs
Embedding trees in dense graphs Václav Rozhoň February 14, 2019 joint work with T. Klimo¹ová and D. Piguet Václav Rozhoň Embedding trees in dense graphs February 14, 2019 1 / 11 Alternative definition: substructures in graphs Extremal graph theory Definition (Extremal graph theory, Bollobás 1976) Extremal graph theory, in its strictest sense, is a branch of graph theory developed and loved by Hungarians. Václav Rozhoň Embedding trees in dense graphs February 14, 2019 2 / 11 Extremal graph theory Definition (Extremal graph theory, Bollobás 1976) Extremal graph theory, in its strictest sense, is a branch of graph theory developed and loved by Hungarians. Alternative definition: substructures in graphs Václav Rozhoň Embedding trees in dense graphs February 14, 2019 2 / 11 Density of edges vs. density of triangles (Razborov 2008) (image from the book of Lovász) Extremal graph theory Theorem (Mantel 1907) Graph G has n vertices. If G has more than n2=4 edges then it contains a triangle. Generalisations? Václav Rozhoň Embedding trees in dense graphs February 14, 2019 3 / 11 Extremal graph theory Theorem (Mantel 1907) Graph G has n vertices. If G has more than n2=4 edges then it contains a triangle. Generalisations? Density of edges vs. density of triangles (Razborov 2008) (image from the book of Lovász) Václav Rozhoň Embedding trees in dense graphs February 14, 2019 3 / 11 3=2 The answer for C4 is of order n , lower bound via finite projective planes. What is the answer for trees? Extremal graph theory Theorem (Mantel 1907) Graph G has n vertices. If G has more than n2=4 edges then it contains a triangle. -
Fractional Arboricity, Strength, and Principal Partitions in Graphs and Matroids
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Discrete Applied Mathematics 40 (1992) 285-302 285 North-Holland Fractional arboricity, strength, and principal partitions in graphs and matroids Paul A. Catlin Wayne State University, Detroit, MI 48202. USA Jerrold W. Grossman Oakland University, Rochester, MI 48309, USA Arthur M. Hobbs* Texas A & M University, College Station, TX 77843, USA Hong-Jian Lai** West Virginia University, Morgantown, WV 26506, USA Received 15 February 1989 Revised 15 November 1989 Abstract Catlin, P.A., J.W. Grossman, A.M. Hobbs and H.-J. Lai, Fractional arboricity, strength, and principal partitions in graphs and matroids, Discrete Applied Mathematics 40 (1992) 285-302. In a 1983 paper, D. Gusfield introduced a function which is called (following W.H. Cunningham, 1985) the strength of a graph or matroid. In terms of a graph G with edge set E(G) and at least one link, this is the function v(G) = mmFr9c) IFl/(w(G F) - w(G)), where the minimum is taken over all subsets F of E(G) such that w(G F), the number of components of G - F, is at least w(G) + 1. In a 1986 paper, C. Payan introduced thefractional arboricity of a graph or matroid. In terms of a graph G with edge set E(G) and at least one link this function is y(G) = maxHrC lE(H)I/(l V(H)1 -w(H)), where H runs over Correspondence to: Professor A.M. Hobbs, Department of Mathematics, Texas A & M University, College Station, TX 77843, USA. -
Chromatic Number of the Product of Graphs, Graph Homomorphisms, Antichains and Cofinal Subsets of Posets Without AC
CHROMATIC NUMBER OF THE PRODUCT OF GRAPHS, GRAPH HOMOMORPHISMS, ANTICHAINS AND COFINAL SUBSETS OF POSETS WITHOUT AC AMITAYU BANERJEE AND ZALAN´ GYENIS Abstract. In set theory without the Axiom of Choice (AC), we observe new relations of the following statements with weak choice principles. • If in a partially ordered set, all chains are finite and all antichains are countable, then the set is countable. • If in a partially ordered set, all chains are finite and all antichains have size ℵα, then the set has size ℵα for any regular ℵα. • CS (Every partially ordered set without a maximal element has two disjoint cofinal subsets). • CWF (Every partially ordered set has a cofinal well-founded subset). • DT (Dilworth’s decomposition theorem for infinite p.o.sets of finite width). We also study a graph homomorphism problem and a problem due to Andr´as Hajnal without AC. Further, we study a few statements restricted to linearly-ordered structures without AC. 1. Introduction Firstly, the first author observes the following in ZFA (Zermelo-Fraenkel set theory with atoms). (1) In Problem 15, Chapter 11 of [KT06], applying Zorn’s lemma, Komj´ath and Totik proved the statement “Every partially ordered set without a maximal element has two disjoint cofinal subsets” (CS). In Theorem 3.26 of [THS16], Tachtsis, Howard and Saveliev proved that CS does not imply ‘there are no amorphous sets’ in ZFA. We observe ω that CS 6→ ACfin (the axiom of choice for countably infinite familes of non-empty finite − sets), CS 6→ ACn (‘Every infinite family of n-element sets has a partial choice function’) 1 − for every 2 ≤ n<ω and CS 6→ LOKW4 (Every infinite linearly orderable family A of 4-element sets has a partial Kinna–Wegner selection function)2 in ZFA. -
No Finite-Infinite Antichain Duality in the Homomorphism Poset D of Directed Graphs
NO FINITE-INFINITE ANTICHAIN DUALITY IN THE HOMOMORPHISM POSET D OF DIRECTED GRAPHS PETER¶ L. ERDOS} AND LAJOS SOUKUP Abstract. D denotes the homomorphism poset of ¯nite directed graphs. An antichain duality is a pair hF; Di of antichains of D such that (F!) [ (!D) = D is a partition. A generalized duality pair in D is an antichain duality hF; Di with ¯nite F and D: We give a simpli¯ed proof of the Foniok - Ne·set·ril- Tardif theorem for the special case D, which gave full description of the generalized duality pairs in D. Although there are many antichain dualities hF; Di with in¯nite D and F, we can show that there is no antichain duality hF; Di with ¯nite F and in¯nite D. 1. Introduction If G and H are ¯nite directed graphs, write G · H or G ! H i® there is a homomorphism from G to H, that is, a map f : V (G) ! V (H) such that hf(x); f(y)i is a directed edge 2 E(H) whenever hx; yi 2 E(G). The relation · is a quasi-order and so it induces an equivalence relation: G and H are homomorphism-equivalent if and only if G · H and H · G. The homomorphism poset D is the partially ordered set of all equivalence classes of ¯nite directed graphs, ordered by ·. In this paper we continue the study of antichain dualities in D (what was started, in this form, in [2]). An antichain duality is a pair hF; Di of disjoint antichains of D such that D = (F!) [ (!D) is a partition of D, where the set F! := fG : F · G for some F 2 Fg, and !D := fG : G · D for some D 2 Dg. -
Limits of Graph Sequences
Snapshots of modern mathematics № 10/2019 from Oberwolfach Limits of graph sequences Tereza Klimošová Graphs are simple mathematical structures used to model a wide variety of real-life objects. With the rise of computers, the size of the graphs used for these models has grown enormously. The need to ef- ficiently represent and study properties of extremely large graphs led to the development of the theory of graph limits. 1 Graphs A graph is one of the simplest mathematical structures. It consists of a set of vertices (which we depict as points) and edges between the pairs of vertices (depicted as line segments); several examples are shown in Figure 1. Many real-life settings can be modeled using graphs: for example, social and computer networks, road and other transport network maps, and the structure of molecules (see Figure 2a and 2b). These models are widely used in computer science, for instance for route planning algorithms or by Google’s PageRank algorithm, which generates search results. What these models all have in common is the representation of a set of several objects (the vertices) and relations or connections between pairs of those objects (the edges). In recent years, with the increasing use of computers in all areas of life, it has become necessary to handle large volumes of data. To represent such data (for example, connections between internet servers) in turn requires graphs with very many vertices and an even larger number of edges. In such situations, traditional algorithms for processing graphs are often impractical, or even impossible, because the computations take too much time and/or computational 1 Figure 1: Examples of graphs. -
Arxiv:2107.04993V1 [Cs.DS] 11 Jul 2021
The Mixed Page Number of Graphs Jawaherul Md. Alam1 , Michael A. Bekos2 , Martin Gronemann3 , Michael Kaufmann2 , and Sergey Pupyrev4 1 Amazon Inc., Tempe, AZ, USA [email protected] 2 Institut f¨urInformatik, Universit¨atT¨ubingen,T¨ubingen,Germany fbekos,[email protected] 3 Theoretical Computer Science, Osnabr¨uck University, Osnabr¨uck, Germany [email protected] 4 Facebook, Inc., Menlo Park, CA, USA [email protected] Abstract. A linear layout of a graph typically consists of a total vertex order, and a partition of the edges into sets of either non-crossing edges, called stacks, or non-nested edges, called queues. The stack (queue) number of a graph is the minimum number of required stacks (queues) in a linear layout. Mixed linear layouts combine these layouts by allowing each set of edges to form either a stack or a queue. In this work we initiate the study of the mixed page number of a graph which corresponds to the minimum number of such sets. First, we study the edge density of graphs with bounded mixed page number. Then, we focus on complete and complete bipartite graphs, for which we derive lower and upper bounds on their mixed page number. Our findings indicate that combining stacks and queues is more powerful in various ways compared to the two traditional layouts. Keywords: Linear layouts · Mixed page number · Stacks and queues 1 Introduction Linear layouts of graphs form an important research topic, which has been studied in different areas and under different perspectives. As a matter of fact, several combinatorial optimization problems are defined by means of a measure over a linear layout of a graph (including the well- known cutwidth [1], bandwidth [9] and pathwidth [23]). -
Layouts of Graph Subdivisions
Layouts of Graph Subdivisions Vida Dujmovi´c1,2 and David R. Wood2,3 1 School of Computer Science, McGill University, Montr´eal, Canada [email protected] 2 School of Computer Science, Carleton University, Ottawa, Canada [email protected] 3 Department of Applied Mathematics, Charles University, Prague, Czech Republic Abstract. A k-stack layout (respectively, k-queue layout) of a graph consists of a total order of the vertices, and a partition of the edges into k sets of non-crossing (non-nested) edges with respect to the vertex or- dering. A k-track layout of a graph consists of a vertex k-colouring, and a total order of each vertex colour class, such that between each pair of colour classes no two edges cross. The stack-number (respectively, queue-number, track-number) of a graph G, denoted by sn(G)(qn(G), tn(G)), is the minimum k such that G has a k-stack (k-queue, k-track) layout. This paper studies stack, queue, and track layouts of graph sub- divisions. It is known that every graph has a 3-stack subdivision. The best known upper bound on the number of division vertices per edge in a 3-stack subdivision of an n-vertex graph G is improved from O(log n)to O(log min{sn(G), qn(G)}). This result reduces the question of whether queue-number is bounded by stack-number to whether 3-stack graphs have bounded queue number. It is proved that every graph has a 2- queue subdivision, a 4-track subdivision, and a mixed 1-stack 1-queue subdivision.