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We consider the 2D stochastic Navier-Stokes equations driven by noise that has the regularity of space-time white noise but doesn't exactly coincide with it. We show that, provided that the intensity of the noise is sufficiently weak at…

Probability · Mathematics 2025-10-22 Martin Hairer , Wenhao Zhao

In this paper we study 3D Navier-Stokes (NS) equation driven by space-time white noise by using regularity structure theory introduced in [Hai14] and paracontrolled distribution proposed in [GIP13]. We obtain local existence and uniqueness…

Probability · Mathematics 2017-01-05 Rongchan Zhu , Xiangchan Zhu

Stochastic Navier--Stokes equations in a thin three-dimensional domain are considered, driven by additive noise. The convergence of martingale solution of the stochastic Navier--Stokes equations in a thin three-dimensional domain to the…

Probability · Mathematics 2020-08-18 Zdzisław Brzeźniak , Gaurav Dhariwal , Quoc Thong Le Gia

We consider the Navier-Stokes equations in $\mathbb R^d$ ($d=2,3$) with a stochastic forcing term which is white noise in time and coloured in space; the spatial covariance of the noise is not too regular, so It\^o calculus cannot be…

Probability · Mathematics 2015-10-14 Zdzislaw Brzezniak , Benedetta Ferrario

We establish global-in-time existence and non-uniqueness of probabilistically strong solutions to the three dimensional Navier--Stokes system driven by space-time white noise. In this setting, solutions are expected to have space regularity…

Analysis of PDEs · Mathematics 2021-12-30 Martina Hofmanová , Rongchan Zhu , Xiangchan Zhu

We prove ergodicity of the finite dimensional approximations of the three dimensional Navier-Stokes equations, driven by a random force. The forcing noise acts only on a few modes and some algebraic conditions on the forced modes are found…

Probability · Mathematics 2007-05-23 M. Romito

In this paper we study approximations to 3D Navier-Stokes (NS) equation driven by space-time white noise by paracontrolled distribution proposed in [GIP13]. A solution theory for this equation has been developed recently in [ZZ14] based on…

Probability · Mathematics 2014-09-18 Rongchan Zhu , 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

We prove that every Markov solution to the three dimensional Navier-Stokes equation with periodic boundary conditions driven by additive Gaussian noise is uniquely ergodic. The convergence to the (unique) invariant measure is exponentially…

Mathematical Physics · Physics 2009-11-13 Marco Romito

We consider the Navier-Stokes equation on a two dimensional torus with a random force which is white noise in time, and excites only a finite number of modes. The number of excited modes depends on the viscosity $\nu$, and grows like…

Mathematical Physics · Physics 2007-05-23 J. Bricmont , A. Kupiainen , R. Lefevere

We construct a local in time spatially real-analytic solution to the 2D and 3D stochastic Navier--Stokes equation driven by a spatially real-analytic multiplicative and transport noise but emanating from an initial condition that is only…

Analysis of PDEs · Mathematics 2024-07-15 Dan Crisan , Prince Romeo Mensah

We are concerned with the three dimensional navier-stokes equations driven by a general multiplicative noise. For every divergence free and mean free initial condition in L2, we establish existence of infinitely many global-in-time…

Probability · Mathematics 2025-05-13 Huaxiang Lv , Yichun Zhu

We establish a general criterion which ensures exponential mixing of parabolic Stochastic Partial Differential Equations (SPDE) driven by a non additive noise which is white in time and smooth in space. We apply this criterion on two…

Analysis of PDEs · Mathematics 2007-05-23 Cyril Odasso

We prove the strong Feller property and exponential mixing for 3D stochastic Navier-Stokes equation driven by mildly degenerate noises (i.e. all but finitely many Fourier modes are forced) via Kolmogorov equation approach.

Probability · Mathematics 2010-01-30 Sergio Albeverio , Arnaud Debussche , Lihu Xu

The objective of this note is to present the results from the two recent papers. We study the Navier--Stokes equation on the two--dimensional torus when forced by a finite dimensional white Gaussian noise. We give conditions under which…

Probability · Mathematics 2007-05-23 Martin Hairer , Jonathan C. Mattingly , Etienne Pardoux

In this paper we are concerned with the 2D incompressible Navier-Stokes equations driven by space-time white noise. We establish existence of infinitely many global-in-time probabilistically strong and analytically weak solutions $u$ for…

Probability · Mathematics 2023-04-18 Huaxiang Lü , Xiangchan Zhu

We prove that the any Markov solution to the 3D stochastic Navier-Stokes equations driven by a mildly degenerate noise (i.e.all but finitely many Fourier modes are forced) is uniquely ergodic. This follows by proving strong Feller…

Probability · Mathematics 2009-12-10 Lihu Xu , Marco Romito

We propose and study a temporal, and spatio-temporal discretisation of the 2D stochastic Navier--Stokes equations in bounded domains supplemented with no-slip boundary conditions. Considering additive noise, we base its construction on the…

Numerical Analysis · Mathematics 2022-03-23 Dominic Breit , Andreas Prohl

We consider stationary solutions of the three dimensional Navier--Stokes equations (NS3D) with periodic boundary conditions and driven by an external force which might have a deterministic and a random part. The random part of the force is…

Analysis of PDEs · Mathematics 2007-05-23 Cyril Odasso

We consider a family of stochastic 2D Euler equations in vorticity form on the torus, with transport type noises and $L^2$-initial data. Under a suitable scaling of the noises, we show that the solutions converge weakly to that of the…

Probability · Mathematics 2021-08-11 Franco Flandoli , Lucio Galeati , Dejun Luo
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