Treewidth of Chordal Bipartite Graphs
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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. -
Counting Independent Sets in Graphs with Bounded Bipartite Pathwidth∗
Counting independent sets in graphs with bounded bipartite pathwidth∗ Martin Dyery Catherine Greenhillz School of Computing School of Mathematics and Statistics University of Leeds UNSW Sydney, NSW 2052 Leeds LS2 9JT, UK Australia [email protected] [email protected] Haiko M¨uller∗ School of Computing University of Leeds Leeds LS2 9JT, UK [email protected] 7 August 2019 Abstract We show that a simple Markov chain, the Glauber dynamics, can efficiently sample independent sets almost uniformly at random in polynomial time for graphs in a certain class. The class is determined by boundedness of a new graph parameter called bipartite pathwidth. This result, which we prove for the more general hardcore distribution with fugacity λ, can be viewed as a strong generalisation of Jerrum and Sinclair's work on approximately counting matchings, that is, independent sets in line graphs. The class of graphs with bounded bipartite pathwidth includes claw-free graphs, which generalise line graphs. We consider two further generalisations of claw-free graphs and prove that these classes have bounded bipartite pathwidth. We also show how to extend all our results to polynomially-bounded vertex weights. 1 Introduction There is a well-known bijection between matchings of a graph G and independent sets in the line graph of G. We will show that we can approximate the number of independent sets ∗A preliminary version of this paper appeared as [19]. yResearch supported by EPSRC grant EP/S016562/1 \Sampling in hereditary classes". zResearch supported by Australian Research Council grant DP190100977. 1 in graphs for which all bipartite induced subgraphs are well structured, in a sense that we will define precisely. -
Forbidding Subgraphs
Graph Theory and Additive Combinatorics Lecturer: Prof. Yufei Zhao 2 Forbidding subgraphs 2.1 Mantel’s theorem: forbidding a triangle We begin our discussion of extremal graph theory with the following basic question. Question 2.1. What is the maximum number of edges in an n-vertex graph that does not contain a triangle? Bipartite graphs are always triangle-free. A complete bipartite graph, where the vertex set is split equally into two parts (or differing by one vertex, in case n is odd), has n2/4 edges. Mantel’s theorem states that we cannot obtain a better bound: Theorem 2.2 (Mantel). Every triangle-free graph on n vertices has at W. Mantel, "Problem 28 (Solution by H. most bn2/4c edges. Gouwentak, W. Mantel, J. Teixeira de Mattes, F. Schuh and W. A. Wythoff). Wiskundige Opgaven 10, 60 —61, 1907. We will give two proofs of Theorem 2.2. Proof 1. G = (V E) n m Let , a triangle-free graph with vertices and x edges. Observe that for distinct x, y 2 V such that xy 2 E, x and y N(x) must not share neighbors by triangle-freeness. Therefore, d(x) + d(y) ≤ n, which implies that d(x)2 = (d(x) + d(y)) ≤ mn. ∑ ∑ N(y) x2V xy2E y On the other hand, by the handshake lemma, ∑x2V d(x) = 2m. Now by the Cauchy–Schwarz inequality and the equation above, Adjacent vertices have disjoint neigh- borhoods in a triangle-free graph. !2 ! 4m2 = ∑ d(x) ≤ n ∑ d(x)2 ≤ mn2; x2V x2V hence m ≤ n2/4. -
Estimating All Pairs Shortest Paths in Restricted Graph Families: a Unified Approach
Estimating All Pairs Shortest Paths in Restricted Graph Families: A Unified Approach (Extended Abstract) Feodor F. Dragan Dept. of Computer Science, Kent State University, Kent, Ohio 44242, USA [email protected] Abstract. In this paper we show that a very simple and efficient ap- proach can be used to solve the all pairs almost shortest path problem on the class of weakly chordal graphs and its different subclasses. Moreover, this approach works well also on graphs with small size of largest induced cycle and gives a unified way to solve the all pairs almost shortest path and all pairs shortest path problems on different graph classes includ- ing chordal, strongly chordal, chordal bipartite, and distance-hereditary graphs. 1 Introduction Let G =(V,E) be a finite, unweighted, undirected, connected and simple (i.e., without loops and multiple edges) graph. Let also |V | = n and |E| = m. The distance d(v, u) between vertices v and u is the smallest number of edges in a path connecting v and u. The all pairs shortest path problem is to compute d(v, u) for all pairs of vertices v and u in G. The all pairs shortest path (APSP) problem is one of the most fundamental graph problems. There has been a renewed interest in it recently (see [1,2,4,6,12], [15,29] for general (unweighted, undirected) graphs, and [3,5,7,10,11,14,20,21,24], [28,32,33] for special graph classes). For general graphs, the best result known is by Seidel [29], who showed that the APSP problem can be solved in O(M(n) log n) time where M(n) denotes the time complexity for matrix multiplication involving small integers only. -
The Labeled Perfect Matching in Bipartite Graphs Jérôme Monnot
The Labeled perfect matching in bipartite graphs Jérôme Monnot To cite this version: Jérôme Monnot. The Labeled perfect matching in bipartite graphs. Information Processing Letters, Elsevier, 2005, to appear, pp.1-9. hal-00007798 HAL Id: hal-00007798 https://hal.archives-ouvertes.fr/hal-00007798 Submitted on 5 Aug 2005 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. The Labeled perfect matching in bipartite graphs J´erˆome Monnot∗ July 4, 2005 Abstract In this paper, we deal with both the complexity and the approximability of the labeled perfect matching problem in bipartite graphs. Given a simple graph G = (V, E) with |V | = 2n vertices such that E contains a perfect matching (of size n), together with a color (or label) function L : E → {c1, . , cq}, the labeled perfect matching problem consists in finding a perfect matching on G that uses a minimum or a maximum number of colors. Keywords: labeled matching; bipartite graphs; NP-complete; approximate algorithms. 1 Introduction Let Π be a NPO problem accepting simple graphs G = (V,E) as instances, edge-subsets E′ ⊆ E verifying a given polynomial-time decidable property Pred as solutions, and the solutions cardinality as objective function; the labeled problem associated to Π, denoted by Labeled Π, seeks, given an instance I = (G, L) where G = (V,E) is a simple graph ′ and L is a mapping from E to {c1,...,cq}, in finding a subset E verifying Pred that optimizes the size of the set L(E′)= {L(e): e ∈ E′}. -
Density Theorems for Bipartite Graphs and Related Ramsey-Type Results
Density theorems for bipartite graphs and related Ramsey-type results Jacob Fox Benny Sudakov Princeton UCLA and IAS Ramsey’s theorem Definition: r(G) is the minimum N such that every 2-edge-coloring of the complete graph KN contains a monochromatic copy of graph G. Theorem: (Ramsey-Erdos-Szekeres,˝ Erdos)˝ t/2 2t 2 ≤ r(Kt ) ≤ 2 . Question: (Burr-Erd˝os1975) How large is r(G) for a sparse graph G on n vertices? Ramsey numbers for sparse graphs Conjecture: (Burr-Erd˝os1975) For every d there exists a constant cd such that if a graph G has n vertices and maximum degree d, then r(G) ≤ cd n. Theorem: 1 (Chv´atal-R¨odl-Szemer´edi-Trotter 1983) cd exists. 2αd 2 (Eaton 1998) cd ≤ 2 . βd αd log2 d 3 (Graham-R¨odl-Ruci´nski2000) 2 ≤ cd ≤ 2 . Moreover, if G is bipartite, r(G) ≤ 2αd log d n. Density theorem for bipartite graphs Theorem: (F.-Sudakov) Let G be a bipartite graph with n vertices and maximum degree d 2 and let H be a bipartite graph with parts |V1| = |V2| = N and εN edges. If N ≥ 8dε−d n, then H contains G. Corollary: For every bipartite graph G with n vertices and maximum degree d, r(G) ≤ d2d+4n. (D. Conlon independently proved that r(G) ≤ 2(2+o(1))d n.) Proof: Take ε = 1/2 and H to be the graph of the majority color. Ramsey numbers for cubes Definition: d The binary cube Qd has vertex set {0, 1} and x, y are adjacent if x and y differ in exactly one coordinate. -
Constrained Representations of Map Graphs and Half-Squares
Constrained Representations of Map Graphs and Half-Squares Hoang-Oanh Le Berlin, Germany [email protected] Van Bang Le Universität Rostock, Institut für Informatik, Rostock, Germany [email protected] Abstract The square of a graph H, denoted H2, is obtained from H by adding new edges between two distinct vertices whenever their distance in H is two. The half-squares of a bipartite graph B = (X, Y, EB ) are the subgraphs of B2 induced by the color classes X and Y , B2[X] and B2[Y ]. For a given graph 2 G = (V, EG), if G = B [V ] for some bipartite graph B = (V, W, EB ), then B is a representation of G and W is the set of points in B. If in addition B is planar, then G is also called a map graph and B is a witness of G [Chen, Grigni, Papadimitriou. Map graphs. J. ACM, 49 (2) (2002) 127-138]. While Chen, Grigni, Papadimitriou proved that any map graph G = (V, EG) has a witness with at most 3|V | − 6 points, we show that, given a map graph G and an integer k, deciding if G admits a witness with at most k points is NP-complete. As a by-product, we obtain NP-completeness of edge clique partition on planar graphs; until this present paper, the complexity status of edge clique partition for planar graphs was previously unknown. We also consider half-squares of tree-convex bipartite graphs and prove the following complexity 2 dichotomy: Given a graph G = (V, EG) and an integer k, deciding if G = B [V ] for some tree-convex bipartite graph B = (V, W, EB ) with |W | ≤ k points is NP-complete if G is non-chordal dually chordal and solvable in linear time otherwise. -
Graph Theory
1 Graph Theory “Begin at the beginning,” the King said, gravely, “and go on till you come to the end; then stop.” — Lewis Carroll, Alice in Wonderland The Pregolya River passes through a city once known as K¨onigsberg. In the 1700s seven bridges were situated across this river in a manner similar to what you see in Figure 1.1. The city’s residents enjoyed strolling on these bridges, but, as hard as they tried, no residentof the city was ever able to walk a route that crossed each of these bridges exactly once. The Swiss mathematician Leonhard Euler learned of this frustrating phenomenon, and in 1736 he wrote an article [98] about it. His work on the “K¨onigsberg Bridge Problem” is considered by many to be the beginning of the field of graph theory. FIGURE 1.1. The bridges in K¨onigsberg. J.M. Harris et al., Combinatorics and Graph Theory , DOI: 10.1007/978-0-387-79711-3 1, °c Springer Science+Business Media, LLC 2008 2 1. Graph Theory At first, the usefulness of Euler’s ideas and of “graph theory” itself was found only in solving puzzles and in analyzing games and other recreations. In the mid 1800s, however, people began to realize that graphs could be used to model many things that were of interest in society. For instance, the “Four Color Map Conjec- ture,” introduced by DeMorgan in 1852, was a famous problem that was seem- ingly unrelated to graph theory. The conjecture stated that four is the maximum number of colors required to color any map where bordering regions are colored differently. -
Lecture 12 — October 10, 2017 1 Overview 2 Matchings in Bipartite Graphs
CS 388R: Randomized Algorithms Fall 2017 Lecture 12 | October 10, 2017 Prof. Eric Price Scribe: Shuangquan Feng, Xinrui Hua 1 Overview In this lecture, we will explore 1. Problem of finding matchings in bipartite graphs. 2. Hall's Theorem: sufficient and necessary condition for the existence of perfect matchings in bipartite graphs. 3. An algorithm for finding perfect matching in d-regular bipartite graphs when d = 2k which is based on the idea of Euler tour and has a time complexity of O(nd). 4. A randomized algorithm for finding perfect matchings in all d regular bipartite graphs which has an expected time complexity of O(n log n). 5. Problem of online bipartite matching. 2 Matchings in Bipartite Graphs Definition 1 (Bipartite Graph). A graph G = (V; E) is said to be bipartite if the vertex set V can be partitioned into 2 disjoint sets L and R so that any edge has one vertex in L and the other in R. Definition 2 (Matching). Given an undirected graph G = (V; E), a matching is a subset of edges M ⊆ E that have no endpoints in common. Definition 3 (Maximum Matching). Given an undirected graph G = (V; E), a maximum matching M is a matching of maximum size. Thus for any other matching M 0, we have that jMj ≥ jM 0j. Definition 4 (Perfect Matching). Given an bipartite graph G = (V; E), with the bipartition V = L [ R where jLj = jRj = n, a perfect matching is a maximum matching of size n. There are several well known algorithms for the problem of finding maximum matchings in bipartite graphs. -
Lecture 9-10: Extremal Combinatorics 1 Bipartite Forbidden Subgraphs 2 Graphs Without Any 4-Cycle
MAT 307: Combinatorics Lecture 9-10: Extremal combinatorics Instructor: Jacob Fox 1 Bipartite forbidden subgraphs We have seen the Erd}os-Stonetheorem which says that given a forbidden subgraph H, the extremal 1 2 number of edges is ex(n; H) = 2 (1¡1=(Â(H)¡1)+o(1))n . Here, o(1) means a term tending to zero as n ! 1. This basically resolves the question for forbidden subgraphs H of chromatic number at least 3, since then the answer is roughly cn2 for some constant c > 0. However, for bipartite forbidden subgraphs, Â(H) = 2, this answer is not satisfactory, because we get ex(n; H) = o(n2), which does not determine the order of ex(n; H). Hence, bipartite graphs form the most interesting class of forbidden subgraphs. 2 Graphs without any 4-cycle Let us start with the ¯rst non-trivial case where H is bipartite, H = C4. I.e., the question is how many edges G can have before a 4-cycle appears. The answer is roughly n3=2. Theorem 1. For any graph G on n vertices, not containing a 4-cycle, 1 p E(G) · (1 + 4n ¡ 3)n: 4 Proof. Let dv denote the degree of v 2 V . Let F denote the set of \labeled forks": F = f(u; v; w):(u; v) 2 E; (u; w) 2 E; v 6= wg: Note that we do not care whether (v; w) is an edge or not. We count the size of F in two possible ways: First, each vertex u contributes du(du ¡ 1) forks, since this is the number of choices for v and w among the neighbors of u. -
Minimum Fill-In for Chordal Bipartite Graphs
Minimum fill-in for chordal bipartite graphs Citation for published version (APA): Kloks, A. J. J. (1993). Minimum fill-in for chordal bipartite graphs. (Universiteit Utrecht. UU-CS, Department of Computer Science; Vol. 9311). Utrecht University. Document status and date: Published: 01/01/1993 Document Version: Publisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers) Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. -
Hypergraph Packing and Sparse Bipartite Ramsey Numbers
Hypergraph packing and sparse bipartite Ramsey numbers David Conlon ∗ Abstract We prove that there exists a constant c such that, for any integer ∆, the Ramsey number of a bipartite graph on n vertices with maximum degree ∆ is less than 2c∆n. A probabilistic argument due to Graham, R¨odland Ruci´nskiimplies that this result is essentially sharp, up to the constant c in the exponent. Our proof hinges upon a quantitative form of a hypergraph packing result of R¨odl,Ruci´nskiand Taraz. 1 Introduction For a graph G, the Ramsey number r(G) is defined to be the smallest natural number n such that, in any two-colouring of the edges of Kn, there exists a monochromatic copy of G. That these numbers exist was proven by Ramsey [19] and rediscovered independently by Erd}osand Szekeres [10]. Whereas the original focus was on finding the Ramsey numbers of complete graphs, in which case it is known that t t p2 r(Kt) 4 ; ≤ ≤ the field has broadened considerably over the years. One of the most famous results in the area to date is the theorem, due to Chvat´al,R¨odl,Szemer´ediand Trotter [7], that if a graph G, on n vertices, has maximum degree ∆, then r(G) c(∆)n; ≤ where c(∆) is just some appropriate constant depending only on ∆. Their proof makes use of the regularity lemma and because of this the bound it gives on the constant c(∆) is (and is necessarily [11]) very bad. The situation was improved somewhat by Eaton [8], who proved, by using a variant of the regularity lemma, that the function c(∆) may be taken to be of the form 22c∆ .