97 research outputs found

    Ergodic properties of a model for turbulent dispersion of inertial particles

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    We study a simple stochastic differential equation that models the dispersion of close heavy particles moving in a turbulent flow. In one and two dimensions, the model is closely related to the one-dimensional stationary Schroedinger equation in a random delta-correlated potential. The ergodic properties of the dispersion process are investigated by proving that its generator is hypoelliptic and using control theory

    Capacity of Time-Slotted ALOHA Packetized Multiple-Access Systems Over the AWGN Channel

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    Analysis of equilibrium states of Markov solutions to the 3D Navier-Stokes equations driven by additive noise

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    We prove that every Markov solution to the three dimensional Navier-Stokes equation with periodic boundary conditions driven by additive Gaussian noise is uniquely ergodic. The convergence to the (unique) invariant measure is exponentially fast. Moreover, we give a well-posedness criterion for the equations in terms of invariant measures. We also analyse the energy balance and identify the term which ensures equality in the balance.Comment: 32 page

    Persistence for stochastic difference equations: A mini-review

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    Understanding under what conditions populations, whether they be plants, animals, or viral particles, persist is an issue of theoretical and practical importance in population biology. Both biotic interactions and environmental fluctuations are key factors that can facilitate or disrupt persistence. One approach to examining the interplay between these deterministic and stochastic forces is the construction and analysis of stochastic difference equations Xt+1=F(Xt,ξt+1)X_{t+1}=F(X_t,\xi_{t+1}) where XtRkX_t \in \R^k represents the state of the populations and ξ1,ξ2,...\xi_1,\xi_2,... is a sequence of random variables representing environmental stochasticity. In the analysis of these stochastic models, many theoretical population biologists are interested in whether the models are bounded and persistent. Here, boundedness asserts that asymptotically XtX_t tends to remain in compact sets. In contrast, persistence requires that XtX_t tends to be "repelled" by some "extinction set" S0RkS_0\subset \R^k. Here, results on both of these proprieties are reviewed for single species, multiple species, and structured population models. The results are illustrated with applications to stochastic versions of the Hassell and Ricker single species models, Ricker, Beverton-Holt, lottery models of competition, and lottery models of rock-paper-scissor games. A variety of conjectures and suggestions for future research are presented.Comment: Accepted for publication in the Journal of Difference Equations and Application

    Optimal scaling of average queue sizes in an input-queued switch: an open problem

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    We review some known results and state a few versions of an open problem related to the scaling of the total queue size (in steady state) in an n×n input-queued switch, as a function of the port number n and the load factor ρ. Loosely speaking, the question is whether the total number of packets in queue, under either the maximum weight policy or under an optimal policy, scales (ignoring any logarithmic factors) as O(n/(1 − ρ)).National Science Foundation (U.S.) (Grant CCF-0728554

    Billiards in a general domain with random reflections

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    We study stochastic billiards on general tables: a particle moves according to its constant velocity inside some domain DRd{\mathcal D} \subset {\mathbb R}^d until it hits the boundary and bounces randomly inside according to some reflection law. We assume that the boundary of the domain is locally Lipschitz and almost everywhere continuously differentiable. The angle of the outgoing velocity with the inner normal vector has a specified, absolutely continuous density. We construct the discrete time and the continuous time processes recording the sequence of hitting points on the boundary and the pair location/velocity. We mainly focus on the case of bounded domains. Then, we prove exponential ergodicity of these two Markov processes, we study their invariant distribution and their normal (Gaussian) fluctuations. Of particular interest is the case of the cosine reflection law: the stationary distributions for the two processes are uniform in this case, the discrete time chain is reversible though the continuous time process is quasi-reversible. Also in this case, we give a natural construction of a chord "picked at random" in D{\mathcal D}, and we study the angle of intersection of the process with a (d1)(d-1)-dimensional manifold contained in D{\mathcal D}.Comment: 50 pages, 10 figures; To appear in: Archive for Rational Mechanics and Analysis; corrected Theorem 2.8 (induced chords in nonconvex subdomains

    Stationary distributions for diffusions with inert drift

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    Consider reflecting Brownian motion in a bounded domain in Rd{\mathbb R^d} that acquires drift in proportion to the amount of local time spent on the boundary of the domain. We show that the stationary distribution for the joint law of the position of the reflecting Brownian motion and the value of the drift vector has a product form. Moreover, the first component is uniformly distributed on the domain, and the second component has a Gaussian distribution. We also consider more general reflecting diffusions with inert drift as well as processes where the drift is given in terms of the gradient of a potential
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