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

Ran Wang; Jie Xiong; Lihu Xu

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arXiv · 1601.06270

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

Ran Wang·Jie Xiong·Lihu Xu

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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.

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Ran Wang, Jie Xiong, Lihu Xu. 2016-01-23. Large deviation principle of occupation measures for Non-linear monotone SPDEs. https://arxiv.org/abs/1601.06270

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