English

Small time asymptotics for a class of stochastic partial differential equations with fully monotone coefficients forced by multiplicative Gaussian noise

Probability 2022-12-27 v1

Abstract

The main goal of this article is to study the effect of small, highly nonlinear, unbounded drifts (small time large deviation principle (LDP) based on exponential equivalence arguments) for a class of stochastic partial differential equations (SPDEs) with fully monotone coefficients driven by multiplicative Gaussian noise. The small time LDP obtained in this paper is applicable for various quasi-linear and semilinear SPDEs such as porous medium equations, Cahn-Hilliard equation, 2D Navier-Stokes equations, convection-diffusion equation, 2D liquid crystal model, power law fluids, Ladyzhenskaya model, pp-Laplacian equations, etc., perturbed by multiplicative Gaussian noise.

Keywords

Cite

@article{arxiv.2212.12896,
  title  = {Small time asymptotics for a class of stochastic partial differential equations with fully monotone coefficients forced by multiplicative Gaussian noise},
  author = {Ankit Kumar and Manil T. Mohan},
  journal= {arXiv preprint arXiv:2212.12896},
  year   = {2022}
}