Large deviations for locally monotone stochastic partial differential equations driven by Lévy noise

Fuente: arXiv
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Auteurs principaux: Wu, Weina, Zhai, Jianliang, Zhu, Jiahui
Format: Preprint
Publié: 2024
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author Wu, Weina
Zhai, Jianliang
Zhu, Jiahui
author_facet Wu, Weina
Zhai, Jianliang
Zhu, Jiahui
contents We establish a Freidlin-Wentzell type large deviation principle (LDP) for a class of stochastic partial differential equations with locally monotone coefficients driven by Lévy noise. Our results essentially improve a recent work on this topic (Bernoulli, 2018) by the second named author of this paper and his collaborator, because we drop the compactness embedding assumptions, and we also make the conditions for the coefficient of the noise term more specific and weaker. To obtain our results, we utilize an improved sufficient criteria of Budhiraja, Chen, Dupuis, and Maroulas for functions of Poisson random measures, and the techniques introduced by the first and second named authors of this paper in \cite{WZSIAM} play important roles. As an application, for the first time, the Freidlin-Wentzell type LDPs for many SPDEs driven by Lévy noise in unbounded domains of $\mathbb{R}^d$, which are generally lack of compactness embeddings properties, are achieved, like e.g., stochastic $p$-Laplace equation, stochastic Burgers-type equations, stochastic 2D Navier-Stokes equations, stochastic equations of non-Newtonian fluids, etc.
format Preprint
id arxiv_https___arxiv_org_abs_2401_11385
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Large deviations for locally monotone stochastic partial differential equations driven by Lévy noise
Wu, Weina
Zhai, Jianliang
Zhu, Jiahui
Probability
We establish a Freidlin-Wentzell type large deviation principle (LDP) for a class of stochastic partial differential equations with locally monotone coefficients driven by Lévy noise. Our results essentially improve a recent work on this topic (Bernoulli, 2018) by the second named author of this paper and his collaborator, because we drop the compactness embedding assumptions, and we also make the conditions for the coefficient of the noise term more specific and weaker. To obtain our results, we utilize an improved sufficient criteria of Budhiraja, Chen, Dupuis, and Maroulas for functions of Poisson random measures, and the techniques introduced by the first and second named authors of this paper in \cite{WZSIAM} play important roles. As an application, for the first time, the Freidlin-Wentzell type LDPs for many SPDEs driven by Lévy noise in unbounded domains of $\mathbb{R}^d$, which are generally lack of compactness embeddings properties, are achieved, like e.g., stochastic $p$-Laplace equation, stochastic Burgers-type equations, stochastic 2D Navier-Stokes equations, stochastic equations of non-Newtonian fluids, etc.
title Large deviations for locally monotone stochastic partial differential equations driven by Lévy noise
topic Probability
url https://arxiv.org/abs/2401.11385