A moderate deviation principle for 2-D stochastic Navier–Stokes equations driven by multiplicative Lévy noises ☆
TLDR
In this article, the authors established a moderate deviation principle for two-dimensional stochastic Navier-Stokes equations driven by multiplicative Levy noises and showed that the weak convergence method introduced by Budhiraja, Dupuis and Ganguly in [3] plays a key role.Citations
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Large and moderate deviation principles for McKean-Vlasov SDEs with jumps
TL;DR: In this paper, the authors considered MVSDEs with shifted driving Levy noise and established large and moderate deviation principles for MVS DEs driven by Levy noise, by identifying the right equations satisfied by the solutions of the corresponding skeleton equations and then replacing the noise by the elements of the Cameron Martin space.
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Moderate deviations for stochastic tidal dynamics equations with multiplicative Gaussian noise
TL;DR: In this article, the authors consider the stochastic tidal dynamics equations perturbed by multiplicative Gaussian noise and discuss some asymptotic behaviors, including a central limit theorem and a moderate deviation.
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Strong solutions for a stochastic model of two-dimensional second grade fluids driven by Lévy noise
TL;DR: In this article, the authors considered stochastic second grade fluids driven by Levy noise on a bounded domain of R 2 and established the global existence and uniqueness of strong probabilistic solutions.
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Well-posedness and large deviations for 2-D Stochastic Navier-Stokes equations with jumps
TL;DR: In this paper, the authors prove the existence and uniqueness of a strong (in both the probabilistic and PDEs sense) solution to the 2-D Stochastic Navier-Stokes equations driven by multiplicative L\'evy noise under local Lipschitz and one-sided linear growth assumptions on the coefficients of the stochastic perturbations.
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Large deviation principle for a class of SPDE with locally monotone coefficients
Wei Liu,Chunyan Tao,Jiahui Zhu +2 more
TL;DR: In this paper, the Laplace principle for stochastic partial differential equations with locally monotone coefficients was shown to be equivalent to the large deviation principle in the extended variational framework.
References
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Book
Large Deviations Techniques and Applications
Amir Dembo,Ofer Zeitouni +1 more
TL;DR: The LDP for Abstract Empirical Measures and applications-The Finite Dimensional Case and Applications of Empirically Measures LDP are presented.
Book
Stochastic differential equations and diffusion processes
TL;DR: In this article, Stochastic Differential Equations and Diffusion Processes are used to model the diffusion process in stochastic differential equations. But they do not consider the nonlinearity of diffusion processes.
Book
Navier-Stokes Equations: Theory and Numerical Analysis
TL;DR: This paper presents thediscretization of the Navier-Stokes Equations: General Stability and Convergence Theorems, and describes the development of the Curl Operator and its application to the Steady-State Naviers' Equations.
Journal ArticleDOI
Large deviations for the two-dimensional Navier-Stokes equations with multiplicative noise
Sivaguru S. Sritharan,P. Sundar +1 more
TL;DR: In this article, a Wentzell-Freidlin type large deviation principle is established for the two-dimensional Navier-Stokes equations perturbed by a multiplicative noise in both bounded and unbounded domains.
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Large Deviations for a Reaction-Diffusion Equation with Non-Gaussian Perturbations
TL;DR: In this article, the authors established a large deviations principle for the non-Gaussian stochastic reaction-diffusion equation (SRDE) in the supremum norm of the Holder norm.
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