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

The main goal of this paper 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, and [Formula: see text]-Laplacian equations, perturbed by multiplicative Gaussian noise.