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

2016/01/23 by Ran Wang, Jie Xiong, Wang, Ran +3 · 1 citation
Computer Science · Economics, Econometrics and Finance · Mathematics · #60F10 #60H15 #60J75 #Advanced Mathematical Modeling in Engineering #FOS: Mathematics #Probability (math.PR) #Stochastic processes and financial applications #Stochastic processes and statistical mechanics

paper · pdf · doi:10.48550/arxiv.1601.06270

openalex publication_date 2016/01/23 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

Abstract

Using the hyper-exponential recurrence criterion, a large deviation principle for the occupation measure is derived for a class of non-linear monotone stochastic partial differential equations. The main results are applied to many concrete SPDEs such as stochastic p-Laplace equation, stochastic porous medium equation, stochastic fast-diffusion equation, and even stochastic real Ginzburg-Landau equation driven by α-stable noises.

Citations

• An Introduction to Stochastic PDEs

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