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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 work we consider solutions to stochastic partial differential equations with transport noise, which are known to converge, in a suitable scaling limit, to solution of the corresponding deterministic PDE with an additional viscosity…

Probability · Mathematics 2023-05-04 Lucio Galeati , Dejun Luo

In this paper, we establish a large deviation principle for a type of stochastic partial differential equations (SPDEs) with locally monotone coefficients driven by L\'evy noise. The weak convergence method plays an important role.

Probability · Mathematics 2016-06-08 Jie Xiong , Jianliang Zhai

We are dealing with the validity of a large deviation principle for the two-dimensional Navier-Stokes equation, with periodic boundary conditions, perturbed by a Gaussian random forcing. We are here interested in the regime where both the…

Probability · Mathematics 2016-03-09 Sandra Cerrai , Arnaud Debussche

We study the stochastic Leray-{\alpha} model of Euler equations with transport noise. We first use weak convergence approach to show the large deviations of the stochastic Leray-{\alpha} model of Euler equations in a suitable scaling limit.…

Analysis of PDEs · Mathematics 2023-05-09 Yong Chen , Yuanyuan Gong

In this paper we study the stochastic Navier-Stokes equation with artificial compressibility. The main results of this work are the existence and uniqueness theorem for strong solutions and the limit to incompressible flow. These results…

Probability · Mathematics 2010-12-07 Utpal Manna , Jose-Luis Menaldi , Sivaguru S. Sritharan

In the first part of the note we analyze the long time behaviour of a two dimensional stochastic Navier--Stokes equations system on a torus with a degenerate, one dimensional noise. In particular, for some initial data and noises we…

Probability · Mathematics 2021-08-27 Z. Brzeźniak , T. Komorowski , S. Peszat

In this paper we show the strong convergence of a fully explicit space-time discrete approximation scheme for the solution process of the two-dimensional incompressible stochastic Navier-Stokes equations on the torus driven by additive…

Probability · Mathematics 2018-09-07 Sara Mazzonetto

This paper investigates the pathwise uniform convergence in probability of fully discrete finite-element approximations for the two-dimensional stochastic Navier-Stokes equations with multiplicative noise, subject to no-slip boundary…

Numerical Analysis · Mathematics 2025-02-11 Binjie Li , Xiaoping Xie , Qin Zhou

In this paper we study the stochastic Navier-Stokes equations on the $d$-dimensional torus with transport noise, which arise in the study of turbulent flows. Under very weak smoothness assumptions on the data we prove local well-posedness…

Analysis of PDEs · Mathematics 2023-12-12 Antonio Agresti , Mark Veraar

We study the large deviations principle (LDP) of Donsker-Varadhan type for the white-forced Navier-Stokes system in a bounded domain. Under the assumption that the noise is non-degenerate, we establish level-2 and level-3 LDPs with rate…

Analysis of PDEs · Mathematics 2025-06-18 Meng Zhao

We study the compressible Navier-Stokes system driven by physically relevant transport noise, where the noise influences both the continuity and momentum equations. Our approach is based on transforming the system into a partial…

Analysis of PDEs · Mathematics 2025-04-15 D. Breit , E. Feireisl , M. Hofmanova , P. B. Mucha

We demonstrate the large deviation principle in the small noise limit for the mild solution of stochastic evolution equations with monotone nonlinearity. A recently developed method, weak convergent method, has been employed in studying the…

Probability · Mathematics 2013-09-10 Hassan Dadashi

Rio gave a concise bound for the central limit theorem in the Vaserstein distances, which is a ratio between some higher moments and some powers of the variance. As a corollary, it gives an estimate for the normal approximation of the small…

Probability · Mathematics 2019-10-15 Xiling Zhang

We consider a 2D stochastic wave equation driven by a Gaussian noise, which is temporally white and spatially colored described by the Riesz kernel. Our first main result is the functional central limit theorem for the spatial average of…

Probability · Mathematics 2021-07-29 Raul Bolaños Guerrero , David Nualart , Guangqu Zheng

The work concerns deviation estimates for multivalued McKean-Vlasov stochastic differential equations. First of all, we prove the large deviation principle for them by the weak convergence approach. Then the central limit theorem for them…

Probability · Mathematics 2022-08-10 Kun Fang , Huijie Qiao

We study a model of interacting particles represented by a system of N stochastic differential equations. We establish that the mollified empirical distribution of the system converges uniformly with respect to both time and spatial…

Probability · Mathematics 2025-10-09 Filippo Giovagnini , Dan Crisan

A stochastic description of solutions of the Navier-Stokes equation is investigated. These solutions are represented by laws of finite dimensional semi-martingales and characterized by a weak Euler- Lagrange condition. A least action…

Probability · Mathematics 2016-02-12 Ana Bela Cruzeiro , Rémi Lassalle

The planar Navier-Stokes equation exhibits, in absence of external forces, a trivial asymptotics in time. Nevertheless the appearence of coherent structures suggests non-trivial intermediate asymptotics which should be explained in terms of…

Analysis of PDEs · Mathematics 2015-05-13 E. Caglioti , M. Pulvirenti , F. Rousset

Loosely speaking, the Navier-Stokes-$\alpha$ model and the Navier-Stokes equations differ by a spatial filtration parametrized by a scale denoted $\alpha$. Starting from a strong two-dimensional solution to the Navier-Stokes-$\alpha$ model…

Analysis of PDEs · Mathematics 2022-10-06 Jad Doghman , Ludovic Goudenège