Subgraph Isomorphism in Graph Classes
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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. -
Graph Varieties Axiomatized by Semimedial, Medial, and Some Other Groupoid Identities
Discussiones Mathematicae General Algebra and Applications 40 (2020) 143–157 doi:10.7151/dmgaa.1344 GRAPH VARIETIES AXIOMATIZED BY SEMIMEDIAL, MEDIAL, AND SOME OTHER GROUPOID IDENTITIES Erkko Lehtonen Technische Universit¨at Dresden Institut f¨ur Algebra 01062 Dresden, Germany e-mail: [email protected] and Chaowat Manyuen Department of Mathematics, Faculty of Science Khon Kaen University Khon Kaen 40002, Thailand e-mail: [email protected] Abstract Directed graphs without multiple edges can be represented as algebras of type (2, 0), so-called graph algebras. A graph is said to satisfy an identity if the corresponding graph algebra does, and the set of all graphs satisfying a set of identities is called a graph variety. We describe the graph varieties axiomatized by certain groupoid identities (medial, semimedial, autodis- tributive, commutative, idempotent, unipotent, zeropotent, alternative). Keywords: graph algebra, groupoid, identities, semimediality, mediality. 2010 Mathematics Subject Classification: 05C25, 03C05. 1. Introduction Graph algebras were introduced by Shallon [10] in 1979 with the purpose of providing examples of nonfinitely based finite algebras. Let us briefly recall this concept. Given a directed graph G = (V, E) without multiple edges, the graph algebra associated with G is the algebra A(G) = (V ∪ {∞}, ◦, ∞) of type (2, 0), 144 E. Lehtonen and C. Manyuen where ∞ is an element not belonging to V and the binary operation ◦ is defined by the rule u, if (u, v) ∈ E, u ◦ v := (∞, otherwise, for all u, v ∈ V ∪ {∞}. We will denote the product u ◦ v simply by juxtaposition uv. Using this representation, we may view any algebraic property of a graph algebra as a property of the graph with which it is associated. -
A Logical Approach to Isomorphism Testing and Constraint Satisfaction
A logical approach to Isomorphism Testing and Constraint Satisfaction Oleg Verbitsky Humboldt University of Berlin, Germany ESSLLI 2016, 1519 August 1/21 Part 8: k with : FO# k ≥ 3 Applications to Isomorphism Testing 2/21 Outline 1 Warm-up 2 Weisfeiler-Leman algorithm 3 Bounds for particular classes of graphs 4 References 3/21 Outline 1 Warm-up 2 Weisfeiler-Leman algorithm 3 Bounds for particular classes of graphs 4 References 4/21 Closure properties of denable graphs Denition G denotes the complement graph of G: V (G) = V (G) and uv 2 E(G) () uv2 = E(G). Exercise Prove that, if is denable in k , then is also denable G FO# G in k . FO# 5/21 Closure properties of denable graphs Denition G1 + G2 denotes the vertex-disjoint union of graphs G1 and G2. Exercise Let k ≥ 3. Suppose that connected graphs G1;:::;Gm are denable in k . Prove that is also denable FO# G1 + G2 + ::: + Gm in k . FO# Hint As an example, let k = 3 and suppose that G = 5A + 4B and H = 4A + 5B for some connected A and B such that W#(A; B) ≤ 3. In the rst round, Spoiler makes a counting move in G by marking all vertices in all A-components. Duplicator is forced to mark at least one vertex v in a B-component of H. Spoiler pebbles v, and Duplicator can only pebble some vertex u in an A-component of G. From now on, Spoiler plays in the components that contain u and v using his winning strategy for the game on A and B. -
Monte-Carlo Algorithms in Graph Isomorphism Testing
Monte-Carlo algorithms in graph isomorphism testing L´aszl´oBabai∗ E¨otv¨osUniversity, Budapest, Hungary Universit´ede Montr´eal,Canada Abstract Abstract. We present an O(V 4 log V ) coin flipping algorithm to test vertex-colored graphs with bounded color multiplicities for color-preserving isomorphism. We are also able to generate uniformly distributed ran- dom automorphisms of such graphs. A more general result finds gener- ators for the intersection of cylindric subgroups of a direct product of groups in O(n7/2 log n) time, where n is the length of the input string. This result will be applied in another paper to find a polynomial time coin flipping algorithm to test isomorphism of graphs with bounded eigenvalue multiplicities. The most general result says that if AutX is accessible by a chain G0 ≥ · · · ≥ Gk = AutX of quickly recognizable groups such that the indices |Gi−1 : Gi| are small (but unknown), the order of |G0| is known and there is a fast way of generating uniformly distributed random members of G0 then a set of generators of AutX can be found by a fast algorithm. Applications of the main result im- prove the complexity of isomorphism testing for graphs with bounded valences to exp(n1/2+o(1)) and for distributive lattices to O(n6 log log n). ∗Apart from possible typos, this is a verbatim transcript of the author’s 1979 technical report, “Monte Carlo algorithms in graph isomorphism testing” (Universit´ede Montr´eal, D.M.S. No. 79-10), with two footnotes added to correct a typo and a glaring omission in the original. -
Arxiv:2006.06067V2 [Math.CO] 4 Jul 2021
Treewidth versus clique number. I. Graph classes with a forbidden structure∗† Cl´ement Dallard1 Martin Milaniˇc1 Kenny Storgelˇ 2 1 FAMNIT and IAM, University of Primorska, Koper, Slovenia 2 Faculty of Information Studies, Novo mesto, Slovenia [email protected] [email protected] [email protected] Treewidth is an important graph invariant, relevant for both structural and algo- rithmic reasons. A necessary condition for a graph class to have bounded treewidth is the absence of large cliques. We study graph classes closed under taking induced subgraphs in which this condition is also sufficient, which we call (tw,ω)-bounded. Such graph classes are known to have useful algorithmic applications related to variants of the clique and k-coloring problems. We consider six well-known graph containment relations: the minor, topological minor, subgraph, induced minor, in- duced topological minor, and induced subgraph relations. For each of them, we give a complete characterization of the graphs H for which the class of graphs excluding H is (tw,ω)-bounded. Our results yield an infinite family of χ-bounded induced-minor-closed graph classes and imply that the class of 1-perfectly orientable graphs is (tw,ω)-bounded, leading to linear-time algorithms for k-coloring 1-perfectly orientable graphs for every fixed k. This answers a question of Breˇsar, Hartinger, Kos, and Milaniˇc from 2018, and one of Beisegel, Chudnovsky, Gurvich, Milaniˇc, and Servatius from 2019, respectively. We also reveal some further algorithmic implications of (tw,ω)- boundedness related to list k-coloring and clique problems. In addition, we propose a question about the complexity of the Maximum Weight Independent Set prob- lem in (tw,ω)-bounded graph classes and prove that the problem is polynomial-time solvable in every class of graphs excluding a fixed star as an induced minor. -
Arxiv:1906.05510V2 [Math.AC]
BINOMIAL EDGE IDEALS OF COGRAPHS THOMAS KAHLE AND JONAS KRUSEMANN¨ Abstract. We determine the Castelnuovo–Mumford regularity of binomial edge ideals of complement reducible graphs (cographs). For cographs with n vertices the maximum regularity grows as 2n/3. We also bound the regularity by graph theoretic invariants and construct a family of counterexamples to a conjecture of Hibi and Matsuda. 1. Introduction Let G = ([n], E) be a simple undirected graph on the vertex set [n]= {1,...,n}. x1 ··· xn x1 ··· xn Let X = ( y1 ··· yn ) be a generic 2 × n matrix and S = k[ y1 ··· yn ] the polynomial ring whose indeterminates are the entries of X and with coefficients in a field k. The binomial edge ideal of G is JG = hxiyj −yixj : {i, j} ∈ Ei⊆ S, the ideal of 2×2 mi- nors indexed by the edges of the graph. Since their inception in [5, 15], connecting combinatorial properties of G with algebraic properties of JG or S/ JG has been a popular activity. Particular attention has been paid to the minimal free resolution of S/ JG as a standard N-graded S-module [3, 11]. The data of a minimal free res- olution is encoded in its graded Betti numbers βi,j (S/ JG) = dimk Tori(S/ JG, k)j . An interesting invariant is the highest degree appearing in the resolution, the Castelnuovo–Mumford regularity reg(S/ JG) = max{j − i : βij (S/ JG) 6= 0}. It is a complexity measure as low regularity implies favorable properties like vanish- ing of local cohomology. Binomial edge ideals have square-free initial ideals by arXiv:1906.05510v2 [math.AC] 10 Mar 2021 [5, Theorem 2.1] and, using [1], this implies that the extremal Betti numbers and regularity can also be derived from those initial ideals. -
Treewidth-Erickson.Pdf
Computational Topology (Jeff Erickson) Treewidth Or il y avait des graines terribles sur la planète du petit prince . c’étaient les graines de baobabs. Le sol de la planète en était infesté. Or un baobab, si l’on s’y prend trop tard, on ne peut jamais plus s’en débarrasser. Il encombre toute la planète. Il la perfore de ses racines. Et si la planète est trop petite, et si les baobabs sont trop nombreux, ils la font éclater. [Now there were some terrible seeds on the planet that was the home of the little prince; and these were the seeds of the baobab. The soil of that planet was infested with them. A baobab is something you will never, never be able to get rid of if you attend to it too late. It spreads over the entire planet. It bores clear through it with its roots. And if the planet is too small, and the baobabs are too many, they split it in pieces.] — Antoine de Saint-Exupéry (translated by Katherine Woods) Le Petit Prince [The Little Prince] (1943) 11 Treewidth In this lecture, I will introduce a graph parameter called treewidth, that generalizes the property of having small separators. Intuitively, a graph has small treewidth if it can be recursively decomposed into small subgraphs that have small overlap, or even more intuitively, if the graph resembles a ‘fat tree’. Many problems that are NP-hard for general graphs can be solved in polynomial time for graphs with small treewidth. Graphs embedded on surfaces of small genus do not necessarily have small treewidth, but they can be covered by a small number of subgraphs, each with small treewidth. -
Planar Graphs and Regular Polyhedra
Planar Graphs and Regular Polyhedra March 25, 2010 1 Planar Graphs ² A graph G is said to be embeddable in a plane, or planar, if it can be drawn in the plane in such a way that no two edges cross each other. Such a drawing is called a planar embedding of the graph. ² Let G be a planar graph and be embedded in a plane. The plane is divided by G into disjoint regions, also called faces of G. We denote by v(G), e(G), and f(G) the number of vertices, edges, and faces of G respectively. ² Strictly speaking, the number f(G) may depend on the ways of drawing G on the plane. Nevertheless, we shall see that f(G) is actually independent of the ways of drawing G on any plane. The relation between f(G) and the number of vertices and the number of edges of G are related by the well-known Euler Formula in the following theorem. ² The complete graph K4, the bipartite complete graph K2;n, and the cube graph Q3 are planar. They can be drawn on a plane without crossing edges; see Figure 5. However, by try-and-error, it seems that the complete graph K5 and the complete bipartite graph K3;3 are not planar. (a) Tetrahedron, K4 (b) K2;5 (c) Cube, Q3 Figure 1: Planar graphs (a) K5 (b) K3;3 Figure 2: Nonplanar graphs Theorem 1.1. (Euler Formula) Let G be a connected planar graph with v vertices, e edges, and f faces. Then v ¡ e + f = 2: (1) 1 (a) Octahedron (b) Dodecahedron (c) Icosahedron Figure 3: Regular polyhedra Proof. -
Group, Graphs, Algorithms: the Graph Isomorphism Problem
Proc. Int. Cong. of Math. – 2018 Rio de Janeiro, Vol. 3 (3303–3320) GROUP, GRAPHS, ALGORITHMS: THE GRAPH ISOMORPHISM PROBLEM László Babai Abstract Graph Isomorphism (GI) is one of a small number of natural algorithmic problems with unsettled complexity status in the P / NP theory: not expected to be NP-complete, yet not known to be solvable in polynomial time. Arguably, the GI problem boils down to filling the gap between symmetry and regularity, the former being defined in terms of automorphisms, the latter in terms of equations satisfied by numerical parameters. Recent progress on the complexity of GI relies on a combination of the asymptotic theory of permutation groups and asymptotic properties of highly regular combinato- rial structures called coherent configurations. Group theory provides the tools to infer either global symmetry or global irregularity from local information, eliminating the symmetry/regularity gap in the relevant scenario; the resulting global structure is the subject of combinatorial analysis. These structural studies are melded in a divide- and-conquer algorithmic framework pioneered in the GI context by Eugene M. Luks (1980). 1 Introduction We shall consider finite structures only; so the terms “graph” and “group” will refer to finite graphs and groups, respectively. 1.1 Graphs, isomorphism, NP-intermediate status. A graph is a set (the set of ver- tices) endowed with an irreflexive, symmetric binary relation called adjacency. Isomor- phisms are adjacency-preseving bijections between the sets of vertices. The Graph Iso- morphism (GI) problem asks to determine whether two given graphs are isomorphic. It is known that graphs are universal among explicit finite structures in the sense that the isomorphism problem for explicit structures can be reduced in polynomial time to GI (in the sense of Karp-reductions1) Hedrlı́n and Pultr [1966] and Miller [1979]. -
What Is a Polyhedron?
3. POLYHEDRA, GRAPHS AND SURFACES 3.1. From Polyhedra to Graphs What is a Polyhedron? Now that we’ve covered lots of geometry in two dimensions, let’s make things just a little more difficult. We’re going to consider geometric objects in three dimensions which can be made from two-dimensional pieces. For example, you can take six squares all the same size and glue them together to produce the shape which we call a cube. More generally, if you take a bunch of polygons and glue them together so that no side gets left unglued, then the resulting object is usually called a polyhedron.1 The corners of the polygons are called vertices, the sides of the polygons are called edges and the polygons themselves are called faces. So, for example, the cube has 8 vertices, 12 edges and 6 faces. Different people seem to define polyhedra in very slightly different ways. For our purposes, we will need to add one little extra condition — that the volume bound by a polyhedron “has no holes”. For example, consider the shape obtained by drilling a square hole straight through the centre of a cube. Even though the surface of such a shape can be constructed by gluing together polygons, we don’t consider this shape to be a polyhedron, because of the hole. We say that a polyhedron is convex if, for each plane which lies along a face, the polyhedron lies on one side of that plane. So, for example, the cube is a convex polyhedron while the more complicated spec- imen of a polyhedron pictured on the right is certainly not convex. -
5 Graph Theory
last edited March 21, 2016 5 Graph Theory Graph theory – the mathematical study of how collections of points can be con- nected – is used today to study problems in economics, physics, chemistry, soci- ology, linguistics, epidemiology, communication, and countless other fields. As complex networks play fundamental roles in financial markets, national security, the spread of disease, and other national and global issues, there is tremendous work being done in this very beautiful and evolving subject. The first several sections covered number systems, sets, cardinality, rational and irrational numbers, prime and composites, and several other topics. We also started to learn about the role that definitions play in mathematics, and we have begun to see how mathematicians prove statements called theorems – we’ve even proven some ourselves. At this point we turn our attention to a beautiful topic in modern mathematics called graph theory. Although this area was first introduced in the 18th century, it did not mature into a field of its own until the last fifty or sixty years. Over that time, it has blossomed into one of the most exciting, and practical, areas of mathematical research. Many readers will first associate the word ‘graph’ with the graph of a func- tion, such as that drawn in Figure 4. Although the word graph is commonly Figure 4: The graph of a function y = f(x). used in mathematics in this sense, it is also has a second, unrelated, meaning. Before providing a rigorous definition that we will use later, we begin with a very rough description and some examples. -
Crossing Number for Graphs with Bounded Pathwidth∗†
Crossing Number for Graphs with Bounded Pathwidth∗† Therese Biedl‡1, Markus Chimani§2, Martin Derka¶3, and Petra Mutzel‖4 1 Dept. of Computer Science, University of Waterloo, Canada [email protected] 2 Dept. of Computer Science, Universität Osnabrück, Germany [email protected] 3 Dept. of Computer Science, University of Waterloo, Canada [email protected] 4 Dept. of Computer Science, Technische Universität Dortmund, Germany [email protected] Abstract The crossing number is the smallest number of pairwise edge crossings when drawing a graph into the plane. There are only very few graph classes for which the exact crossing number is known or for which there at least exist constant approximation ratios. Furthermore, up to now, general crossing number computations have never been successfully tackled using bounded width of graph decompositions, like treewidth or pathwidth. In this paper, we for the first time show that crossing number is tractable (even in linear time) for maximal graphs of bounded pathwidth 3. The technique also shows that the crossing number and the rectilinear (a.k.a. straight-line) crossing number are identical for this graph class, and that we require only an O(n) × O(n)-grid to achieve such a drawing. Our techniques can further be extended to devise a 2-approximation for general graphs with pathwidth 3, and a 4w3-approximation for maximal graphs of pathwidth w. This is a constant approximation for bounded pathwidth graphs. 1998 ACM Subject Classification F.2.2 Nonnumerical Algorithms and Problems Keywords and phrases Crossing Number, Graphs with Bounded Pathwidth Digital Object Identifier 10.4230/LIPIcs.ISAAC.2017.13 1 Introduction The crossing number cr(G) is the smallest number of pairwise edge-crossings over all possible drawings of a graph G into the plane.