Large time asymptotics for the parabolic Anderson model driven by spatially correlated noise

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Authors

Colleges, School and Institutes

Abstract

In this paper we study the linear stochastic heat equation, also known as parabolic Anderson model, in multidimension driven by a Gaussian noise which is white in time and it has a correlated spatial covariance. Examples of such covariance include the Riesz kernel in any dimension and the covariance of the fractional Brownian motion with Hurst parameter H∈(14,12] in dimension one. First we establish the existence of a unique mild solution and we derive a Feynman–Kac formula for its moments using a family of independent Brownian bridges and assuming a general integrability condition on the initial data. In the second part of the paper we compute Lyapunov exponents, lower and upper exponential growth indices in terms of a variational quantity. The last part of the paper is devoted to study the phase transition property of the Anderson model.

Details

Original languageEnglish
Pages (from-to)1305-1340
JournalAnnales de l'institut Henri Poincare (B) Probability and Statistics
Volume53
Issue number3
Publication statusPublished - Jul 2017