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The parabolic Anderson model in a dynamic random environment: Basic properties of the quenched Lyapunov exponent

D. Erhard, F. den Hollander, G. Maillard (2014)

Annales de l'I.H.P. Probabilités et statistiques

In this paper we study the parabolic Anderson equation u ( x , t ) / t = κ 𝛥 u ( x , t ) + ξ ( x , t ) u ( x , t ) , x d , t 0 , where the u -field and the ξ -field are -valued, κ [ 0 , ) is the diffusion constant, and 𝛥 is the discrete Laplacian. The ξ -field plays the role of adynamic random environmentthat drives the equation. The initial condition u ( x , 0 ) = u 0 ( x ) , x d , is taken to be non-negative and bounded. The solution of the parabolic Anderson equation describes the evolution of a field of particles performing independent simple random walks with binary branching: particles jump...

The parabolic-parabolic Keller-Segel equation

Kleber Carrapatoso (2014/2015)

Séminaire Laurent Schwartz — EDP et applications

I present in this note recent results on the uniqueness and stability for the parabolic-parabolic Keller-Segel equation on the plane, obtained in collaboration with S. Mischler in [11].

The proportional likelihood ratio order and applications.

Héctor M. Ramos Romero, Miguel Angel Sordo Díaz (2001)

Qüestiió

In this paper, we introduce a new stochastic order between continuous non-negative random variables called the PLR (proportional likelihood ratio) order, which is closely related to the usual likelihood ratio order. The PLR order can be used to characterize random variables whose logarithms have log-concave (log-convex) densities. Many income random variables satisfy this property and they are said to have the IPLR (increasing proportional likelihood ratio) property (DPLR property). As an application,...

The quenched invariance principle for random walks in random environments admitting a bounded cycle representation

Jean-Dominique Deuschel, Holger Kösters (2008)

Annales de l'I.H.P. Probabilités et statistiques

We derive a quenched invariance principle for random walks in random environments whose transition probabilities are defined in terms of weighted cycles of bounded length. To this end, we adapt the proof for random walks among random conductances by Sidoravicius and Sznitman (Probab. Theory Related Fields129 (2004) 219–244) to the non-reversible setting.

The renormalization transformation for two-type branching models

D. A. Dawson, A. Greven, F. den Hollander, Rongfeng Sun, J. M. Swart (2008)

Annales de l'I.H.P. Probabilités et statistiques

This paper studies countable systems of linearly and hierarchically interacting diffusions taking values in the positive quadrant. These systems arise in population dynamics for two types of individuals migrating between and interacting within colonies. Their large-scale space–time behavior can be studied by means of a renormalization program. This program, which has been carried out successfully in a number of other cases (mostly one-dimensional), is based on the construction and the analysis of...

The scaling limits of a heavy tailed Markov renewal process

Julien Sohier (2013)

Annales de l'I.H.P. Probabilités et statistiques

In this paper we consider heavy tailed Markov renewal processes and we prove that, suitably renormalised, they converge in law towards the α -stable regenerative set. We then apply these results to the strip wetting model which is a random walk S constrained above a wall and rewarded or penalized when it hits the strip [ 0 , ) × [ 0 , a ] where a is a given positive number. The convergence result that we establish allows to characterize the scaling limit of this process at criticality.

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