Large deviations for random walk in a space–time product environment

Averaged Large Deviations for Random Walk in a Random Environment

Abstract. In his 2003 paper, Varadhan proves the averaged large deviation principle (LDP) for the mean velocity of a particle performing random walk in a random environment (RWRE) on Z with d ≥ 1, and gives a variational formula for the corresponding rate function Ia. Under the non-nestling assumption (resp. Kalikow’s condition), we show that Ia is strictly convex and analytic on a non-empty op...

Large Deviations for Random Walk in a Random Environment

In this work, we study the large deviation properties of random walk in a random environment on Z with d ≥ 1. We start with the quenched case, take the point of view of the particle, and prove the large deviation principle (LDP) for the pair empirical measure of the environment Markov chain. By an appropriate contraction, we deduce the quenched LDP for the mean velocity of the particle and obta...

Quenched Large Deviations for Random Walk in a Random Environment

We take the point of view of a particle performing random walk with bounded jumps on Z in a stationary and ergodic random environment. We prove the quenched large deviation principle (LDP) for the pair empirical measure of the environment Markov chain. By an appropriate contraction, we deduce the quenched LDP for the mean velocity of the particle and obtain a variational formula for the corresp...

Large Deviations for Random Walk in a Space-time Product Environment

n≥0 where T denotes the shift on Ω. Conditioned on the particle having asymptotic mean velocity equal to any given ξ, we show that the empirical process of the environment Markov chain converges to a stationary process μ ξ under the averaged measure. When d ≥ 3 and ξ is sufficiently close to the typical velocity, we prove that averaged and quenched large deviations are equivalent and when condi...

Large Deviations for Random Walk in Random