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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

In this paper, we established a large deviation principle for stochastic models of incompressible second grade fluids. The weak convergence method introduced by \cite{Budhiraja-Dupuis} plays an important role.

Probability · Mathematics 2015-06-04 Jianliang Zhai , Tusheng Zhang

We establish a Freidlin-Wentzell type large deviation principle (LDP) for a class of stochastic partial differential equations with locally monotone coefficients driven by L\'evy noise. Our results essentially improve a recent work on this…

Probability · Mathematics 2024-01-23 Weina Wu , Jianliang Zhai , Jiahui Zhu

In this article, we investigate an interacting particle system featuring random intensities, individual noise, and environmental noise, commonly referred to as stochastic point vortex model. The model serves as an approximation for the…

Probability · Mathematics 2024-02-06 Yufei Shao , Xianliang Zhao

The aim of this paper is threefold. Firstly, we prove the existence and the uniqueness of a global strong (in both the probabilistic and the PDE senses) $\mathrm{H}^{1}_2$-valued solution to the 2D stochastic Navier-Stokes equations (SNSEs)…

Probability · Mathematics 2021-10-06 Zdzislaw Brzezniak , Xuhui Peng , Jianliang Zhai

We consider a stochastic 2D Navier-Stokes equation in a bounded domain. The random force is assumed to be non-degenerate and periodic in time, its law has a support localised with respect to both time and space. Slightly strengthening the…

Probability · Mathematics 2022-05-10 Xuhui Peng , Lihu Xu

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 stochastic 2D Euler equations with $L^2$-initial vorticity and driven by L\'evy transport noise in the Marcus sense. Under a suitable scaling limit of the noises, we prove that the weak solutions converge weakly to the unique…

Probability · Mathematics 2025-10-16 Dejun Luo , Feifan Teng

We study the averaging principle for a family of multiscale stochastic dynamical systems. The fast and slow components of the systems are driven by two independent stable L\'evy noises, whose stable indexes may be different. The…

Dynamical Systems · Mathematics 2023-11-14 Yanjie Zhang , Qiao Huang , Xiao Wang , Zibo Wang , Jinqiao Duan

In this paper, we establish the large deviation principle for 3D stochastic primitive equations with small perturbation multiplicative noise. The proof is mainly based on the weak convergence approach.

Probability · Mathematics 2016-06-14 Zhao Dong , Jianliang Zhai , Rangrang Zhang

We consider point vortex systems on the two dimensional torus perturbed by environmental noise. It is shown that, under a suitable scaling of the noises, weak limit points of the empirical measures are solutions to the vorticity formulation…

Probability · Mathematics 2022-03-09 Franco Flandoli , Dejun Luo

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

In this paper we prove the existence of weak martingale solutions to the stochastic Navier-Stokes Equations driven by pure jump L\'evy processes. Our proof consists of two parts. In the first one, mostly classical, we recall a priori…

Probability · Mathematics 2025-06-02 Zdzisław Brzeźniak , Tomasz Kosmala , Elżbieta Motyl , Paul Razafimandimby

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

In this paper, we consider McKean-Vlasov stochastic differential equations (MVSDEs) driven by L\'evy noise. By identifying the right equations satisfied by the solutions of the MVSDEs with shifted driving L\'evy noise, we build up a…

Probability · Mathematics 2020-11-18 Wei Liu , Yulin Song , Jianliang Zhai , Tusheng Zhang

We characterize the behavior of stochastic Navier-Stokes on $\mathbb{T} \times [-1,1]$ with Navier boundary conditions at high Reynolds number when initialized near Couette flow subject to small additive stochastic forcing. We take additive…

Analysis of PDEs · Mathematics 2026-03-03 Ryan Arbon , Jacob Bedrossian

The phenomenon of dissipation enhancement by transport noise is shown for stochastic 2D Navier-Stokes equations in velocity form. In the 3D case, suppression of blow-up is proved for stochastic Navier-Stokes equations in vorticity form; in…

Probability · Mathematics 2023-10-03 Dejun Luo

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

We establish the uniqueness and the asymptotic stability of the invariant measure for the two dimensional Navier Stokes equations driven by a multiplicative noise which is either bounded or with a sublinear or a linear growth. We work on an…

Probability · Mathematics 2023-07-10 Benedetta Ferrario , Margherita Zanella

We consider the Navier-Stokes system in two and three space dimensions perturbed by transport noise and subject to periodic boundary conditions. The noise arises from perturbing the advecting velocity field by space-time dependent noise…

Analysis of PDEs · Mathematics 2018-08-02 Martina Hofmanová , James-Michael Leahy , Torstein Nilssen