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Tail estimates for homogenization theorems in random media

Daniel Boivin (2009)

ESAIM: Probability and Statistics

Consider a random environment in d given by i.i.d. conductances. In this work, we obtain tail estimates for the fluctuations about the mean for the following characteristics of the environment: the effective conductance between opposite faces of a cube, the diffusion matrices of periodized environments and the spectral gap of the random walk in a finite cube.

The discrete-time parabolic Anderson model with heavy-tailed potential

Francesco Caravenna, Philippe Carmona, Nicolas Pétrélis (2012)

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

We consider a discrete-time version of the parabolic Anderson model. This may be described as a model for a directed ( 1 + d ) -dimensional polymer interacting with a random potential, which is constant in the deterministic direction and i.i.d. in the d orthogonal directions. The potential at each site is a positive random variable with a polynomial tail at infinity. We show that, as the size of the system diverges, the polymer extremity is localized almost surely at one single point which grows ballistically....

The infinite valley for a recurrent random walk in random environment

Nina Gantert, Yuval Peres, Zhan Shi (2010)

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

We consider a one-dimensional recurrent random walk in random environment (RWRE). We show that the – suitably centered – empirical distributions of the RWRE converge weakly to a certain limit law which describes the stationary distribution of a random walk in an infinite valley. The construction of the infinite valley goes back to Golosov, see Comm. Math. Phys.92 (1984) 491–506. As a consequence, we show weak convergence for both the maximal local time and the self-intersection local time of the...

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 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 spread of a catalytic branching random walk

Philippe Carmona, Yueyun Hu (2014)

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

We consider a catalytic branching random walk on that branches at the origin only. In the supercritical regime we establish a law of large number for the maximal position M n : For some constant α , M n n α almost surely on the set of infinite number of visits of the origin. Then we determine all possible limiting laws for M n - α n as n goes to infinity.

Transience/recurrence and the speed of a one-dimensional random walk in a “have your cookie and eat it” environment

Ross G. Pinsky (2010)

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

Consider a variant of the simple random walk on the integers, with the following transition mechanism. At each site x, the probability of jumping to the right is ω(x)∈[½, 1), until the first time the process jumps to the left from site x, from which time onward the probability of jumping to the right is ½. We investigate the transience/recurrence properties of this process in both deterministic and stationary, ergodic environments {ω(x)}x∈Z. In deterministic environments, we also study the speed...

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