14,385 research outputs found

    Permutation Inequalities for Walks in Graphs

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    Using spectral graph theory, we show how to obtain inequalities for the number of walks in graphs from nonnegative polynomials and present a new family of such inequalities

    Self-avoiding walks and connective constants

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    The connective constant μ(G)\mu(G) of a quasi-transitive graph GG is the asymptotic growth rate of the number of self-avoiding walks (SAWs) on GG from a given starting vertex. We survey several aspects of the relationship between the connective constant and the underlying graph GG. ∙\bullet We present upper and lower bounds for μ\mu in terms of the vertex-degree and girth of a transitive graph. ∙\bullet We discuss the question of whether μ≥ϕ\mu\ge\phi for transitive cubic graphs (where ϕ\phi denotes the golden mean), and we introduce the Fisher transformation for SAWs (that is, the replacement of vertices by triangles). ∙\bullet We present strict inequalities for the connective constants μ(G)\mu(G) of transitive graphs GG, as GG varies. ∙\bullet As a consequence of the last, the connective constant of a Cayley graph of a finitely generated group decreases strictly when a new relator is added, and increases strictly when a non-trivial group element is declared to be a further generator. ∙\bullet We describe so-called graph height functions within an account of "bridges" for quasi-transitive graphs, and indicate that the bridge constant equals the connective constant when the graph has a unimodular graph height function. ∙\bullet A partial answer is given to the question of the locality of connective constants, based around the existence of unimodular graph height functions. ∙\bullet Examples are presented of Cayley graphs of finitely presented groups that possess graph height functions (that are, in addition, harmonic and unimodular), and that do not. ∙\bullet The review closes with a brief account of the "speed" of SAW.Comment: Accepted version. arXiv admin note: substantial text overlap with arXiv:1304.721

    Random matrices, non-backtracking walks, and orthogonal polynomials

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    Several well-known results from the random matrix theory, such as Wigner's law and the Marchenko--Pastur law, can be interpreted (and proved) in terms of non-backtracking walks on a certain graph. Orthogonal polynomials with respect to the limiting spectral measure play a role in this approach.Comment: (more) minor change

    Walks and the spectral radius of graphs

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    We give upper and lower bounds on the spectral radius of a graph in terms of the number of walks. We generalize a number of known results.Comment: Corrections were made in Theorems 5 and 11 (the new numbers are different), following a remark of professor Yaoping Ho
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