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Related papers: Level-3 large deviations for the white-forced 2D N…

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We deal with a class of abstract nonlinear stochastic models, which covers many 2D hydrodynamical models including 2D Navier-Stokes equations, 2D MHD models and 2D magnetic B\'enard problem and also some shell models of turbulence. We first…

Probability · Mathematics 2011-12-15 Igor Chueshov , Annie Millet

The asymptotic analysis of a class of stochastic partial differential equations (SPDEs) with fully locally monotone coefficients covering a large variety of physical systems, a wide class of quasilinear SPDEs and a good number of fluid…

Probability · Mathematics 2022-12-13 Ankit Kumar , Manil T. Mohan

The paper concerns itself with establishing large deviation principles for a sequence of stochastic integrals and stochastic differential equations driven by general semimartingales in infinite-dimensional settings. The class of…

Probability · Mathematics 2017-08-25 Arnab Ganguly

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 the first part of this article, we obtain a linear system whose the solution solves the time-independent incompressible Navier-Stokes system for the special case in which the external forces vector is a gradient. In a second step we…

General Mathematics · Mathematics 2019-08-27 Fabio Botelho

In the present paper, we prove convergence rates for the pressure of the Local Discontinuous Galerkin (LDG) approximation, proposed in Part I of the paper, of systems of $p$-Navier-Stokes type and $p$-Stokes type with $p\in (2,\infty)$. The…

Numerical Analysis · Mathematics 2023-03-24 Alex Kaltenbach , Michael Růžička

In this paper, we study large deviation principles of nonlinear filtering for McKean-Vlasov stochastic differential equations. First of all, we establish the large deviation principle for the space-distribution dependent Zakai equation by a…

Probability · Mathematics 2023-08-15 Huijie Qiao , Shengqing Zhu

In this work, we investigate a system of interacting particles governed by a set of stochastic differential equations. Our main goal is to rigorously demonstrate that the empirical measure associated with the particle system converges…

Probability · Mathematics 2025-08-12 Filippo Giovagnini , Dan Crisan

For an arbitrary negative Schwarzian unimodal map with non-flat critical point, we establish the level-2 Large Deviation Principle (LDP) for empirical distributions. We also give an example of a multimodal map for which the level-2 LDP does…

Dynamical Systems · Mathematics 2026-03-18 Hiroki Takahasi , Masato Tsujii

In this article, we established a large deviation principle for invariant measures of solutions of stochastic partial differential equations with two reflecting walls driven by space-time white noise.

Probability · Mathematics 2012-04-02 Tusheng Zhang

We consider the incompressible 2D Navier-Stokes equations with periodic boundary conditions driven by a deterministic time periodic forcing and a degenerate stochastic forcing. We show that the system possesses a unique ergodic periodic…

Dynamical Systems · Mathematics 2021-05-04 Rongchang Liu , Kening Lu

This thesis is devoted to the study of ergodicity and large deviations for the stochastic nonlinear wave (NLW) equation with smooth white noise in 3D. Under some standard growth and dissipativity assumptions on the nonlinearity, we show…

Analysis of PDEs · Mathematics 2015-11-30 Davit Martirosyan

This work is concerned with Freidlin-Wentzell type large deviation principle for a family of multi-scale quasilinear and semilinear stochastic partial differential equations. Employing the weak convergence method and Khasminskii's time…

Probability · Mathematics 2021-08-23 Wei Hong , Shihu Li , Wei Liu

In this paper, we establish the pseudospectral bound for the linearized operator of the Navier-Stokes equations around the 3D Kolmogorov flow. Using the pseudospectral bound and the wave operator method introduced in [LWZ], we prove the…

Analysis of PDEs · Mathematics 2018-01-18 Te Li , Dongyi Wei , Zhifei Zhang

The large time behavior of the unique strong solution to the barotropic compressible Navier-Stokes system is studied with large external forces and initial data, where the shear viscosity is a positive constant and the bulk one is…

Analysis of PDEs · Mathematics 2023-10-25 Xinyu Fan , Jing Li , Xue Wang

We establish a large deviation principle for the solutions of a class of stochastic partial differential equations with non-Lipschitz continuous coefficients. As an application, the large deviation principle is derived for super-Brownian…

Probability · Mathematics 2012-05-11 Parisa Fatheddin , Jie Xiong

High-order time-stepping schemes are crucial for simulating incompressible fluid flows due to their ability to capture complex turbulent behavior and unsteady motion. In this work, we propose a third-order accurate numerical scheme for the…

Numerical Analysis · Mathematics 2025-12-22 Kelong Cheng , Jingwei Sun , Hong Zhang

We analyze the two-dimensional incompressible Navier-Stokes equations on a smooth, bounded domain with Navier boundary conditions. Starting from an initial vorticity in $L^p$ with $p>2$, we show strong convergence of the vorticity in the…

Analysis of PDEs · Mathematics 2025-11-07 Josef Demmel , Emil Wiedemann

The convective Brinkman-Forchheimer (CBF) equations characterize the motion of incompressible fluid flows in a saturated porous medium. The small noise asymptotic for the two-time-scale stochastic convective Brinkman-Forchheimer (SCBF)…

Probability · Mathematics 2020-10-20 Manil T. Mohan

We establish a comprehensive sample path large deviation principle (LDP) for log-processes associated with multivariate time-inhomogeneous stochastic volatility models. Examples of models for which the new LDP holds include Gaussian models,…

Probability · Mathematics 2022-11-15 Archil Gulisashvili
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