4,738 research outputs found

    Creation and Growth of Components in a Random Hypergraph Process

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    Denote by an \ell-component a connected bb-uniform hypergraph with kk edges and k(b1)k(b-1) - \ell vertices. We prove that the expected number of creations of \ell-component during a random hypergraph process tends to 1 as \ell and bb tend to \infty with the total number of vertices nn such that =o(nb3)\ell = o(\sqrt[3]{\frac{n}{b}}). Under the same conditions, we also show that the expected number of vertices that ever belong to an \ell-component is approximately 121/3(b1)1/31/3n2/312^{1/3} (b-1)^{1/3} \ell^{1/3} n^{2/3}. As an immediate consequence, it follows that with high probability the largest \ell-component during the process is of size O((b1)1/31/3n2/3)O((b-1)^{1/3} \ell^{1/3} n^{2/3}). Our results give insight about the size of giant components inside the phase transition of random hypergraphs.Comment: R\'{e}sum\'{e} \'{e}tend

    Fully Analyzing an Algebraic Polya Urn Model

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    This paper introduces and analyzes a particular class of Polya urns: balls are of two colors, can only be added (the urns are said to be additive) and at every step the same constant number of balls is added, thus only the color compositions varies (the urns are said to be balanced). These properties make this class of urns ideally suited for analysis from an "analytic combinatorics" point-of-view, following in the footsteps of Flajolet-Dumas-Puyhaubert, 2006. Through an algebraic generating function to which we apply a multiple coalescing saddle-point method, we are able to give precise asymptotic results for the probability distribution of the composition of the urn, as well as local limit law and large deviation bounds.Comment: LATIN 2012, Arequipa : Peru (2012

    Upper tails for counting objects in randomly induced subhypergraphs and rooted random graphs

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    General upper tail estimates are given for counting edges in a random induced subhypergraph of a fixed hypergraph H, with an easy proof by estimating the moments. As an application we consider the numbers of arithmetic progressions and Schur triples in random subsets of integers. In the second part of the paper we return to the subgraph counts in random graphs and provide upper tail estimates in the rooted case.Comment: 15 page

    Detecting degree symmetries in networks

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    The surrounding of a vertex in a network can be more or less symmetric. We derive measures of a specific kind of symmetry of a vertex which we call degree symmetry -- the property that many paths going out from a vertex have overlapping degree sequences. These measures are evaluated on artificial and real networks. Specifically we consider vertices in the human metabolic network. We also measure the average degree-symmetry coefficient for different classes of real-world network. We find that most studied examples are weakly positively degree-symmetric. The exceptions are an airport network (having a negative degree-symmetry coefficient) and one-mode projections of social affiliation networks that are rather strongly degree-symmetric

    Seeded Graph Matching via Large Neighborhood Statistics

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    We study a well known noisy model of the graph isomorphism problem. In this model, the goal is to perfectly recover the vertex correspondence between two edge-correlated Erd\H{o}s-R\'{e}nyi random graphs, with an initial seed set of correctly matched vertex pairs revealed as side information. For seeded problems, our result provides a significant improvement over previously known results. We show that it is possible to achieve the information-theoretic limit of graph sparsity in time polynomial in the number of vertices nn. Moreover, we show the number of seeds needed for exact recovery in polynomial-time can be as low as n3ϵn^{3\epsilon} in the sparse graph regime (with the average degree smaller than nϵn^{\epsilon}) and Ω(logn)\Omega(\log n) in the dense graph regime. Our results also shed light on the unseeded problem. In particular, we give sub-exponential time algorithms for sparse models and an nO(logn)n^{O(\log n)} algorithm for dense models for some parameters, including some that are not covered by recent results of Barak et al

    Network reachability of real-world contact sequences

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    We use real-world contact sequences, time-ordered lists of contacts from one person to another, to study how fast information or disease can spread across network of contacts. Specifically we measure the reachability time -- the average shortest time for a series of contacts to spread information between a reachable pair of vertices (a pair where a chain of contacts exists leading from one person to the other) -- and the reachability ratio -- the fraction of reachable vertex pairs. These measures are studied using conditional uniform graph tests. We conclude, among other things, that the network reachability depends much on a core where the path lengths are short and communication frequent, that clustering of the contacts of an edge in time tend to decrease the reachability, and that the order of the contacts really do make sense for dynamical spreading processes.Comment: (v2: fig. 1 fixed

    Monotone graph limits and quasimonotone graphs

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    The recent theory of graph limits gives a powerful framework for understanding the properties of suitable (convergent) sequences (Gn)(G_n) of graphs in terms of a limiting object which may be represented by a symmetric function WW on [0,1][0,1], i.e., a kernel or graphon. In this context it is natural to wish to relate specific properties of the sequence to specific properties of the kernel. Here we show that the kernel is monotone (i.e., increasing in both variables) if and only if the sequence satisfies a `quasi-monotonicity' property defined by a certain functional tending to zero. As a tool we prove an inequality relating the cut and L1L^1 norms of kernels of the form W1W2W_1-W_2 with W1W_1 and W2W_2 monotone that may be of interest in its own right; no such inequality holds for general kernels.Comment: 38 page

    Probabilistic Analysis of Optimization Problems on Generalized Random Shortest Path Metrics

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    Simple heuristics often show a remarkable performance in practice for optimization problems. Worst-case analysis often falls short of explaining this performance. Because of this, "beyond worst-case analysis" of algorithms has recently gained a lot of attention, including probabilistic analysis of algorithms. The instances of many optimization problems are essentially a discrete metric space. Probabilistic analysis for such metric optimization problems has nevertheless mostly been conducted on instances drawn from Euclidean space, which provides a structure that is usually heavily exploited in the analysis. However, most instances from practice are not Euclidean. Little work has been done on metric instances drawn from other, more realistic, distributions. Some initial results have been obtained by Bringmann et al. (Algorithmica, 2013), who have used random shortest path metrics on complete graphs to analyze heuristics. The goal of this paper is to generalize these findings to non-complete graphs, especially Erd\H{o}s-R\'enyi random graphs. A random shortest path metric is constructed by drawing independent random edge weights for each edge in the graph and setting the distance between every pair of vertices to the length of a shortest path between them with respect to the drawn weights. For such instances, we prove that the greedy heuristic for the minimum distance maximum matching problem, the nearest neighbor and insertion heuristics for the traveling salesman problem, and a trivial heuristic for the kk-median problem all achieve a constant expected approximation ratio. Additionally, we show a polynomial upper bound for the expected number of iterations of the 2-opt heuristic for the traveling salesman problem.Comment: An extended abstract appeared in the proceedings of WALCOM 201

    An Interesting Class of Operators with unusual Schatten-von Neumann behavior

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    We consider the class of integral operators Q_\f on L2(R+)L^2(\R_+) of the form (Q_\f f)(x)=\int_0^\be\f (\max\{x,y\})f(y)dy. We discuss necessary and sufficient conditions on ϕ\phi to insure that QϕQ_{\phi} is bounded, compact, or in the Schatten-von Neumann class \bS_p, 1<p<1<p<\infty. We also give necessary and sufficient conditions for QϕQ_{\phi} to be a finite rank operator. However, there is a kind of cut-off at p=1p=1, and for membership in \bS_{p}, 0<p10<p\leq1, the situation is more complicated. Although we give various necessary conditions and sufficient conditions relating to Q_{\phi}\in\bS_{p} in that range, we do not have necessary and sufficient conditions. In the most important case p=1p=1, we have a necessary condition and a sufficient condition, using L1L^1 and L2L^2 modulus of continuity, respectively, with a rather small gap in between. A second cut-off occurs at p=1/2p=1/2: if \f is sufficiently smooth and decays reasonably fast, then \qf belongs to the weak Schatten-von Neumann class \wS{1/2}, but never to \bS_{1/2} unless \f=0. We also obtain results for related families of operators acting on L2(R)L^2(\R) and 2(Z)\ell^2(\Z). We further study operations acting on bounded linear operators on L2(R+)L^{2}(\R^{+}) related to the class of operators Q_\f. In particular we study Schur multipliers given by functions of the form ϕ(max{x,y})\phi(\max\{x,y\}) and we study properties of the averaging projection (Hilbert-Schmidt projection) onto the operators of the form Q_\f.Comment: 87 page
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