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By
Paul Erdős, Mathematical Institute of the Hungarian Academy of Sciences, Budapest,
A. Hajnal, Mathematical Institute of the Hungarian Academy of Sciences, Budapest,
M. Simonovits, Mathematical Institute of the Hungarian Academy of Sciences, Budapest,
V.T. Sós, Mathematical Institute of the Hungarian Academy of Sciences, Budapest,
E. Szemerédi, Mathematical Institute of the Hungarian Academy of Sciences, Budapest
By
J.K. Dugdale, Department of Mathematics, West Virginia University, PO Box 6310, Morgantown WV 26506-6310, U.S.A.,
A.J.W. Hilton, Department of Mathematics, University of Reading, Whiteknights, PO Box 220, Reading RG6 2AX. U.K.
By
J. Nešetřil, Department of Applied Mathematics, Charles University, Malostranské nám. 25, 118 00 Praha 1, Czech Republic,
P. Valtr, Department of Applied Mathematics, Charles University, Malostranské nám. 25, 118 00 Praha 1, Czech Republic; Graduiertenkolleg ‘Algorithmische Diskrete Mathematik’, Fachbereich Mathematik, Freie Universität Berlin, Takustrasse 9, 14194 Berlin, Germany
By
Z. Füredi, Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139,
M.X. Goemans, Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139,
D.J. Kleitman, Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139
Gallai raised the question of determining t(n), the maximum number of triangles in graphs of n vertices with acyclic neighborhoods. Here we disprove his conjecture (t(n) ∼ n2/8) by exhibiting graphs having n2/7.5 triangles. We improve the upper bound of (n2 − n)/6 to t(n) ≤ n2/7.02 + O(n). For regular graphs, we further decrease this bound to n2/7.75 + O(n).
Introduction
Let WFGn be the class of graphs on n vertices with the property that the neighborhood of any vertex is acyclic. A graph G is given by its vertex set V(G) and edge set E(G). The subgraph induced by X ⊂ V(G) is denoted by G[X]. The neighborhood N(v) of vertex v is the set of vertices adjacent to v. Note that v ∉ N(v). The degree of v ∈ V(G), denoted by dv or dv(G), is the size of the neighborhood: dv = |N(v)|. The maximum (minimum) degree is denoted by Δ (δ), or Δ(G) (δ(G), respectively) to avoid misunderstandings. A matching M ⊂ E(G) is a set of pairwise disjoint edges. A wheel Wi is obtained from a cycle Ci by adding a new vertex and edges joining it to all the vertices of the cycle; the new edges are called the spokes of the wheel (i ≥ 3, W3 = K4). Therefore, WFGn consists of all graphs on n vertices containing no wheel.
By
R. Häggkvist, Department of Mathematics, University of Umeá, S-901 87 Umeá, Sweden,
A. Johansson, Department of Mathematics, University of Umeá, S-901 87 Umeá, Sweden
Every general graph with degrees 2k and 2k − 2,k ≥ 3, with zero or at least two vertices of degree 2k − 2 in each component, has a k-edge-colouring such that each monochromatic subgraph has degree 1 or 2 at every vertex.
In particular, if T is a triangle in a 6-regular general graph, there exists a 2-factorization of G such that each factor uses an edge in T if and only if T is non-separating.
Introduction
In this paper we will characterize those general graphs with degrees 2k − 2 and 2k that can be decomposed into spanning subgraphs with degrees 1 and 2 everywhere. Before we state the result, it is perhaps of some interest to review some related problems and their history.
Background
One of the starting points of graph theory is a classic investigation by the Danish mathematician Julius Petersen who in 1891 published a paper: ‘Die Theorie der regulären graphs’, which contains a wealth of material on the problem of factorizing regular graphs into graphs of uniform degree k. An excellent source of information concerning Julius Petersen and problems spawned by his 1891 paper is the conference volume.
The motivation for Petersen's work, as given in the first few lines of his article, came from Hilbert's proof of the finiteness of the system of invariants associated with a binary form.
By
M. Aigner, II. Mathematisches Institut, Freie Universität Berlin, Arnimallee 3, D-14195 Berlin,
R. Klimmek, II. Mathematisches Institut, Freie Universität Berlin, Arnimallee 3, D-14195 Berlin
By
N. Hindman, Department of Mathematics, Howard University, Washington, D.C. 20059, U.S.A,
I. Leader, Department of Pure Mathematics and Mathematical Statistics, Cambridge University, England
By
N. Alon, Department of Mathematics, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel,
R. Yuster, Department of Mathematics, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel
By
Paul Erdős, Mathematical Institute, Hungarian Academy of Sciences,
E.T. Ordman, Memphis State University, Memphis, TN 38152 U.S.A,
Y. Zalcstein, Division of Computer and Computation Research, National Science Foundation, Washington, D. C. 20550, U. S. A
To partition the edges of a chordal graph on n vertices into cliques may require as many as n2/6 cliques; there is an example requiring this many, which is also a threshold graph and a split graph. It is unknown whether this many cliques will always suffice. We are able to show that (1 − c)n2/4 cliques will suffice for some c > 0.
Introduction
We consider undirected graphs without loops or multiple edges. The graph Kn on n vertices for which every pair of distinct vertices induces an edge is called a complete graph or a clique on n vertices. If G is any graph, we call any complete subgraph of G a clique of G (we do not require that it be a maximal complete subgraph). A clique covering of G is a set of cliques of G that together contain each edge of G at least once; if each edge is covered exactly once we call it a clique partition. The clique covering number cc(G) and clique partition number cp(G) are the smallest cardinalities of, respectively, a clique covering and a clique partition of G.
The question of calculating these numbers was raised by Orlin in 1977. DeBruijn and Erdős had already proved, in 1948, that partitioning Kn into smaller cliques required at least n cliques. Some more recent studies motivating the current paper include.
We consider a simple randomised algorithm that seeks a weak 2-colouring of a hypergraph H; that is, it tries to 2-colour the points of H so that no edge is monochromatic. If H has a particular well-behaved form of such a colouring, then the method is successful within expected number of iterations O(n3) when H has n points. In particular, when applied to a graph G with n nodes and chromatic number 3, the method yields a 2-colouring of the vertices such that no triangle is monochromatic in expected time O(n4).
A hypergraph H on a set of points V is simply a collection of subsets E of V, the edges of H. A d-graph is a hypergraph in which each edge has size d. A weak 2-colouring of a hypergraph is a partition of the points into two ‘colour’ sets A and B such that each edge E meets both A and B. Deciding if a 3-graph has a weak 2-colouring is NP-complete.
The following simple randomised recolouring method attempts to find a weak 2-colouring of a hypergraph H. It is assumed that we have a subroutine SEEK, which on input of a 2-colouring of the points outputs a monochromatic edge if there is one, and otherwise reports that there are none.
Let S be a closed surface with boundary ∂S and let G be a graph. Let K ⊆ G be a subgraph embedded in S such that ∂S ⊆ K. An embedding extension of K to G is an embedding of G in S that coincides on K with the given embedding of K. Minimal obstructions for the existence of embedding extensions are classified in cases when S is the disk or the cylinder. Linear time algorithms are presented that either find an embedding extension, or return an obstruction to the existence of extensions. These results are to be used as the corner stones in the design of linear time algorithms for the embeddability of graphs in an arbitrary surface and for solving more general embedding extension problems.
Introduction
Let K be a subgraph of G. A K-component or a K-bridge in G is a subgraph of G that is either an edge e ∈ E(G)\E(K) (together with its endpoints) that has both endpoints in K, or it is a connected component of G − V(K) together with all edges (and their endpoints) between this component and K. Each edge of a K-component R having an endpoint in K is a foot of R. The vertices of R ∩ K are the vertices of attachment of R. A vertex of K of degree in K different from 2 is a main vertex of K.