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In this paper we consider the Lagrangian Averaged Navier-Stokes Equations, also known as, LANS-$\alpha$ Navier-Stokes model on the two dimensional torus. We assume that the noise is a cylindrical Wiener process and its coefficient is…

Analysis of PDEs · Mathematics 2021-07-27 Z. I. Ali , P. A. Razafimandimby , T. A. Tegegn

This paper is concerned with stochastic incompressible Navier-Stokes equations with multiplicative noise in two dimensions with respect to periodic boundary conditions. Based on the Helmholtz decomposition of the multiplicative noise,…

Numerical Analysis · Mathematics 2022-11-28 Hailong Qiu

In this paper, we investigate the convergence of solutions of a stochastic representation of the three-dimensional Navier-Stokes equations to those of their primitive equations counterpart. Our analysis covers both weak and strong…

Analysis of PDEs · Mathematics 2026-02-05 Arnaud Debussche , Étienne Mémin , Antoine Moneyron

In this paper we establish the large deviation principle for the the two-dimensional stochastic Navier-Stokes equations with anisotropic viscosity both for small noise and for short time. The proof for large deviation principle is based on…

Probability · Mathematics 2020-06-01 Bingguang Chen , Xiangchan Zhu

In this paper, we show the existence and uniqueness of a strong solution to stochastic 3D tamed Navier-Stokes equations driven by multiplicative Levy noise with periodic boundary conditions. Then we establish the large deviation principles…

Probability · Mathematics 2020-02-24 Zhao Dong , Rangrang Zhang

By using the weak convergence method, we establish the large and moderate deviation principles for the multivalued McKean-Vlasov SDEs with non-Lipschitz coefficients driven by L\'{e}vy noise in this paper. The Bihari's inequality is used to…

Probability · Mathematics 2025-12-25 Lingyan Cheng , Caihong Gu , Wei Liu , Fengwu Zhu

This work focuses on topics related to Hamiltonian stochastic differential equations with L\'{e}vy noise. We first show that the phase flow of the stochastic system preserves symplectic structure, and propose a stochastic version of…

Dynamical Systems · Mathematics 2019-07-24 Pingyuan Wei , Ying Chao , Jinqiao Duan

In this work we establish a Freidlin-Wentzell type large deviation principle for stochastic nonlinear Schr\"{o}dinger equation, with either focusing or defocusing nonlinearity, driven by nonlinear multiplicative L\'evy noise in the Marcus…

Probability · Mathematics 2024-08-19 Jiahui Zhu , Wei Liu , Jianliang Zhai

In this paper we prove that the stochastic Navier-Stokes equations with stable L\'evy noise generates a random dynamical systems. Then we prove the existence of random attractor for the Navier-Stokes equations on 2D spheres under stable…

Probability · Mathematics 2019-10-22 Leanne Dong

In this paper, we establish a large deviation principle for stochastic differential delay equations driven by both Brownian motions and Poisson random measures. The weak convergence method plays an important role.

Probability · Mathematics 2016-11-01 Yumeng Li , Ran Wang , Nian Yao , Shuguang Zhang

We establish a large deviation principle (LDP) for a class of stochastic porous media equations driven by L\'{e}vy-type noise on a $\sigma$-finite measure space $(E,\mathcal{B}(E),\mu)$, with the Laplacian replaced by a negative definite…

Probability · Mathematics 2023-12-07 Weina Wu , Jianliang Zhai

Martingale solutions of stochastic Navier-Stokes equations in 2D and 3D possibly unbounded domains, driven by the L\'evy noise consisting of the compensated time homogeneous Poisson random measure and the Wiener process are considered.…

Probability · Mathematics 2012-09-03 Elżbieta Motyl

Recently, extracting data-driven governing laws of dynamical systems through deep learning frameworks has gained a lot of attention in various fields. Moreover, a growing amount of research work tends to transfer deterministic dynamical…

Machine Learning · Statistics 2022-07-05 Cheng Fang , Yubin Lu , Ting Gao , Jinqiao Duan

In this paper, we establish the ergodicity for stochastic 2D Navier-Stokes equations driven by a highly degenerate pure jump L\'evy noise. The noise could appear in as few as four directions. This gives an affirmative anwser to a…

Probability · Mathematics 2024-05-02 Xuhui Peng , Jianliang Zhai , Tusheng Zhang

In this work we prove the existence and uniqueness of the strong solution to the two-dimensional stochastic magneto-hydrodynamic system perturbed by Levy noise. The local monotonicity arguments have been ex- ploited in the proofs. The…

Probability · Mathematics 2014-12-22 Utpal Manna , Manil T. Mohan

This work proposes an efficient, linear, and fully decoupled pressure-correction scheme for the 2D stochastic Navier-Stokes equations with multiplicative noise and Dirichlet boundary condition. Leveraging the auxiliary variable approach,…

Numerical Analysis · Mathematics 2025-11-20 Can Huang , Weiwen Wang , Chuanju Xu

We consider a stochastic model of incompressible non-Newtonian fluids of second grade on a bounded domain of $\mathbb{R}^2$ driven by L\'evy noise. Applying the variational approach, global existence and uniqueness of strong probabilistic…

Probability · Mathematics 2017-01-03 Shijie Shang , Jianliang Zhai , Tusheng Zhang

In this paper, we proved a central limit theorem and established a moderate deviation principle for a perturbed stochastic wave equation defined on $[0,T]\times \rr^3$. This equation is driven by a Gaussian noise, white in time and…

Probability · Mathematics 2017-10-03 L. Cheng , R. Li , R. Wang , N. Yao

In this paper, we establish a moderate deviations principle for the Langevin dynamics with strong damping. The weak convergence approach plays an important role in the proof.

Probability · Mathematics 2018-02-05 Lingyan Cheng , Ruinan Li , Wei Liu

The goal of this paper is to study the Moderate Deviation Principle (MDP) for a system of stochastic reaction-diffusion equations with a time-scale separation in slow and fast components and small noise in the slow component. Based on weak…

Probability · Mathematics 2022-02-03 Ioannis Gasteratos , Michael Salins , Konstantinos Spiliopoulos