44 research outputs found

    Edge-disjoint Hamilton cycles in graphs

    Get PDF
    In this paper we give an approximate answer to a question of Nash-Williams from 1970: we show that for every \alpha > 0, every sufficiently large graph on n vertices with minimum degree at least (1/2 + \alpha)n contains at least n/8 edge-disjoint Hamilton cycles. More generally, we give an asymptotically best possible answer for the number of edge-disjoint Hamilton cycles that a graph G with minimum degree \delta must have. We also prove an approximate version of another long-standing conjecture of Nash-Williams: we show that for every \alpha > 0, every (almost) regular and sufficiently large graph on n vertices with minimum degree at least (1/2+α)n(1/2 + \alpha)n can be almost decomposed into edge-disjoint Hamilton cycles.Comment: Minor Revisio

    Random graphs with bounded maximum degree: asymptotic structure and a logical limit law

    Full text link
    For any fixed integer R2R \geq 2 we characterise the typical structure of undirected graphs with vertices 1,...,n1, ..., n and maximum degree RR, as nn tends to infinity. The information is used to prove that such graphs satisfy a labelled limit law for first-order logic. If R5R \geq 5 then also an unlabelled limit law holds

    Decomposing tournaments into paths

    Get PDF
    We consider a generalisation of Kelly's conjecture which is due to Alspach, Mason, and Pullman from 1976. Kelly's conjecture states that every regular tournament has an edge decomposition into Hamilton cycles, and this was proved by Kühn and Osthus for large tournaments. The conjecture of Alspach, Mason, and Pullman asks for the minimum number of paths needed in a path decomposition of a general tournament T . There is a natural lower bound for this number in terms of the degree sequence of T and it is conjectured that this bound is correct for tournaments of even order. Almost all cases of the conjecture are open and we prove many of them

    On disjoint matchings in cubic graphs

    Get PDF
    For i=2,3i=2,3 and a cubic graph GG let νi(G)\nu_{i}(G) denote the maximum number of edges that can be covered by ii matchings. We show that ν2(G)4/5V(G)\nu_{2}(G)\geq {4/5}| V(G)| and ν3(G)7/6V(G)\nu_{3}(G)\geq {7/6}| V(G)| . Moreover, it turns out that ν2(G)V(G)+2ν3(G)4\nu_{2}(G)\leq \frac{|V(G)|+2\nu_{3}(G)}{4}.Comment: 41 pages, 8 figures, minor chage

    Combinatorics

    Get PDF
    Combinatorics is a fundamental mathematical discipline that focuses on the study of discrete objects and their properties. The present workshop featured research in such diverse areas as Extremal, Probabilistic and Algebraic Combinatorics, Graph Theory, Discrete Geometry, Combinatorial Optimization, Theory of Computation and Statistical Mechanics. It provided current accounts of exciting developments and challenges in these fields and a stimulating venue for a variety of fruitful interactions. This is a report on the meeting, containing extended abstracts of the presentations and a summary of the problem session

    Cycle factors and renewal theory

    Full text link
    For which values of kk does a uniformly chosen 33-regular graph GG on nn vertices typically contain n/k n/k vertex-disjoint kk-cycles (a kk-cycle factor)? To date, this has been answered for k=nk=n and for klognk \ll \log n; the former, the Hamiltonicity problem, was finally answered in the affirmative by Robinson and Wormald in 1992, while the answer in the latter case is negative since with high probability most vertices do not lie on kk-cycles. Here we settle the problem completely: the threshold for a kk-cycle factor in GG as above is κ0log2n\kappa_0 \log_2 n with κ0=[112log23]14.82\kappa_0=[1-\frac12\log_2 3]^{-1}\approx 4.82. Precisely, we prove a 2-point concentration result: if kκ0log2(2n/e)k \geq \kappa_0 \log_2(2n/e) divides nn then GG contains a kk-cycle factor w.h.p., whereas if k<κ0log2(2n/e)log2nnk<\kappa_0\log_2(2n/e)-\frac{\log^2 n}n then w.h.p. it does not. As a byproduct, we confirm the "Comb Conjecture," an old problem concerning the embedding of certain spanning trees in the random graph G(n,p)G(n,p). The proof follows the small subgraph conditioning framework, but the associated second moment analysis here is far more delicate than in any earlier use of this method and involves several novel features, among them a sharp estimate for tail probabilities in renewal processes without replacement which may be of independent interest.Comment: 45 page
    corecore