177,104 research outputs found

    Speed of Parallel Processing for Random Task Graphs

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    The random graph model of parallel computation introduced by Gelenbe et al. depends on three parameters: n, the number of tasks (vertices); F, the common distribution of Ti,. . . , T,, the task processing times, and p = p,, the probability for a given i < j that task i must be completed before task j is started. The total processing time is R,,, the maximum sum of T,’s along directed paths of the graph. We study the large n behavior of Rn when np,, grows sublinearly but superlogarithmically, the regime where the longest directed path contains about enp,, tasks. For an exponential (mean one) F, we prove that R,, is about 4np,. The “discrepancy” between 4 and e is a large deviation effect. Related results are obtained when np,, grows exactly logarithmically and when F is not exponential, but has a tail which decays (at least) exponentially fast

    Quantum Methods for Interacting Particle Systems II, Glauber Dynamics for Ising Spin Systems

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    Using the formalism and the results described in [QMPS I] and in [QMPS III], we discuss the approach to termodynamic equilibrium for discrete spin systems in a framework that generalizes the one originally proposed by R. Glauber. Ergodicity for the process is proved by providing a lower bound extimate for their exponetial rate of convergence to equilibrium, in the high temperature regime. We give application to some (not necessarily ferromagnetic ) Ising-spin models. These results also gives an upper bound for the critical temperature of the d-dimensional Ising model, which in dimension two coincides with the real critical value calculated by the static approach

    The Brownian Web: Convergence and Characterisation

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    The Brownian web (BW) is the random network formally consisting of the paths of coalescing one-dimensional Brownian motions starting from every space-time point in ?×?. We extend the earlier work of Arratia and of Tóth and Werner by providing a new characterization which is then used to obtain convergence results for the BW distribution, including convergence of the system of all coalescing random walks to the BW under diffusive space-time scaling
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