46 research outputs found

    The Single Server Queue and the Storage Model: Large Deviations and Fixed Points

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    We consider the coupling of a single server queue and a storage model defined as a Queue/Store model in Draief et al. 2004. We establish that if the input variables, arrivals at the queue and store, satisfy large deviations principles and are linked through an {\em exponential tilting} then the output variables (departures from each system) satisfy large deviations principles with the same rate function. This generalizes to the context of large deviations the extension of Burke's Theorem derived in Draief et al. 2004.Comment: 20 page

    Viral processes by random walks on random regular graphs

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    We study the SIR epidemic model with infections carried by kk particles making independent random walks on a random regular graph. Here we assume knϵk\leq n^{\epsilon}, where nn is the number of vertices in the random graph, and ϵ\epsilon is some sufficiently small constant. We give an edge-weighted graph reduction of the dynamics of the process that allows us to apply standard results of Erd\H{o}s-R\'{e}nyi random graphs on the particle set. In particular, we show how the parameters of the model give two thresholds: In the subcritical regime, O(lnk)O(\ln k) particles are infected. In the supercritical regime, for a constant β(0,1)\beta\in(0,1) determined by the parameters of the model, βk\beta k get infected with probability β\beta, and O(lnk)O(\ln k) get infected with probability (1β)(1-\beta). Finally, there is a regime in which all kk particles are infected. Furthermore, the edge weights give information about when a particle becomes infected. We exploit this to give a completion time of the process for the SI case.Comment: Published in at http://dx.doi.org/10.1214/13-AAP1000 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Robust On-line Matrix Completion on Graphs

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    We study online robust matrix completion on graphs. At each iteration a vector with some entries missing is revealed and our goal is to reconstruct it by identifying the underlying low-dimensional subspace from which the vectors are drawn. We assume there is an underlying graph structure to the data, that is, the components of each vector correspond to nodes of a certain (known) graph, and their values are related accordingly. We give algorithms that exploit the graph to reconstruct the incomplete data, even in the presence of outlier noise. The theoretical properties of the algorithms are studied and numerical experiments using both synthetic and real world datasets verify the improved performance of the proposed technique compared to other state of the art algorithms

    The single server queue and the storage model: Large deviations and fixed points

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    We consider the coupling of a single server queue and a storage model defined as a queue/store model. We establish that if the input variables, arrivals at the queue and store, satisfy large deviations principles and are linked through an exponential tilting, then the output variables (departures from each system) satisfy large deviations principles with the same rate function.Peer Reviewe

    Opinion formation models on a gradient

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    Statistical physicists have become interested in models of collective social behavior such as opinion formation, where individuals change their inherently preferred opinion if their friends disagree. Real preferences often depend on regional cultural differences, which we model here as a spatial gradient gg in the initial opinion. The gradient does not only add reality to the model. It can also reveal that opinion clusters in two dimensions are typically in the standard (i.e.\ independent) percolation universality class, thus settling a recent controversy about a non-consensus model. However, using analytical and numerical tools, we also present a model where the width of the transition between opinions scales g1/4\propto g^{-1/4}, not g4/7\propto g^{-4/7} as in independent percolation, and the cluster size distribution is consistent with first-order percolation.Comment: 12 pages, 8 figures, version accepted by PLoS ONE, online supplement added as appendi
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