Large deviation principle of occupation measures for non-linear monotone SPDEs

• 作者: Ran Wang Jie Xiong Lihu Xu
• 来源期刊: 中国科学：数学（英文版）
• 年，卷（期）: 2021,（4）
• 所属期刊栏目: Articles
• 页码范围: 799-822
• 页数: 24页
• 语种: 英文

摘要

Using the hyper-exponential recurrence criterion,we establish the occupation measures' large deviation principle for a class of non-linear monotone stochastic partial differential equations (SPDEs) driven by Wiener noise,including the stochastic p-Laplace equation,the stochastic porous medium equation and the stochastic fast-diffusion equation.We also propose a framework for verifying hyper-exponential recurrence,and apply it to study the large deviation problems for strong dissipative SPDEs.These SPDEs can be stochastic systems driven by heavy-tailed α-stable process.