Moderate deviation principle for stochastic Cahn-Hilliard equations with multiplicative Lévy noise

Abstract:

Moderate deviation principle is an important method for constructing asymptotic confidence intervals in statistical inference. This work aims at the moderate deviation principle for the stochastic Cahn-Hilliard equations driven by multiplicative Lévy noise. In these equations, the interaction of high order nonlinear term and jump noise results in the difficulty of dealing with the stochastic integral and deducing the exponential-type probability estimation. Nevertheless, with the help of classical weak convergence method, we estabish the moderate deviation principle underlying the verification of two moderate deviation conditions.