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We prove the large deviations principle (LDP) for the law of the solutions to a class of semilinear stochastic partial differential equations driven by multiplicative noise. Our proof is based on the weak convergence approach and…

Probability · Mathematics 2016-07-05 Mohammud Foondun , Leila Setayeshgar

We explore the potential of a formulation of the Navier-Stokes equations incorporating a random description of the small-scale velocity component. This model, established from a version of the Reynolds transport theorem adapted to a…

Fluid Dynamics · Physics 2016-11-11 S. Kadri Harouna , E. Mémin

The primary goal of this paper is to prove a near-martingale optional stopping theorem and establish solvability and large deviations for a class of anticipating linear stochastic differential equations. We prove the existence and…

Probability · Mathematics 2022-04-06 Hui-Hsiung Kuo , Pujan Shrestha , Sudip Sinha , Padmanabhan Sundar

We consider a stochastic version of the point vortex system, in which the fluid velocity advects single vortices intermittently for small random times. Such system converges to the deterministic point vortex dynamics as the rate at which…

Probability · Mathematics 2023-11-28 Andrea Agazzi , Francesco Grotto , Jonathan C. Mattingly

Current fluctuations in boundary-driven diffusive systems are, in many cases, studied using hydrodynamic theories. Their predictions are then expected to be valid for currents which scale inversely with the system size. To study this…

Statistical Mechanics · Physics 2016-05-26 Yongjoo Baek , Yariv Kafri , Vivien Lecomte

We study a simple magnetohydrodynamical approach in which hydrodynamics and MHD turbulence are coupled in a shell model, with given dynamo constrains in the large scales. We consider the case of a low Prandtl number fluid for which the…

Earth and Planetary Astrophysics · Physics 2015-05-13 Roberto Benzi , Jean-Francois Pinton

We consider the Navier-Stokes equation on the 2D torus, with a stochastic forcing term which is a cylindrical fractional Wiener noise of Hurst parameter $H$. Following [3,8] which dealt with the case $1/2$, we prove a local existence and…

Analysis of PDEs · Mathematics 2018-12-14 Benedetta Ferrario , Christian Olivera

A large deviation principle is established for a general class of stochastic flows in the small noise limit. This result is then applied to a Bayesian formulation of an image matching problem, and an approximate maximum likelihood property…

Statistics Theory · Mathematics 2010-02-24 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

This work concerns about multiscale multivalued McKean-Vlasov stochastic systems. First of all, we use a contractive mapping principle to establish the well-posedness for fully coupled multivalued McKean-Vlasov stochastic systems under…

Probability · Mathematics 2025-09-30 Huijie Qiao

We present a linear, second order fully discrete numerical scheme on a staggered grid for a thermodynamically consistent hydrodynamic phase field model of binary compressible fluid flow mixtures derived from the generalized Onsager…

Numerical Analysis · Mathematics 2019-07-24 Xueping Zhao , Qi Wang

In this paper we explicate a method of quantum hydrodynamics (QHD) for the study of the quantum evolution of a system of polarized particles. Though we focused primarily on the two-dimension physical systems, the method is valid for…

Mesoscale and Nanoscale Physics · Physics 2013-05-29 P. A. Andreev , L. S. Kuzmenkov , M. I. Trukhanova

In this manuscript, we extend Constantin-Iyer's Lagrangian formulation of Navier-Stokes Equation to a wider class of hydrodynamic models. Moreover, we prove that such Lagrangian formulation is naturally derived from a stochastic…

Analysis of PDEs · Mathematics 2025-12-02 Anna Mazzucato , Anping Pan

We propose a kinetic framework for single-component non-ideal isothermal flows. Starting from a kinetic model for a non-ideal fluid, we show that under conventional scaling the Navier-Stokes equations with a non-ideal equation of state are…

Fluid Dynamics · Physics 2022-12-14 S. A. Hosseini , B. Dorschner , I. V. Karlin

We study the tamed magnetohydrodynamics equations, introduced recently in a paper by the author, perturbed by multiplicative Wiener noise of transport type on the whole space $\mathbb{R}^{3}$ and on the torus $\mathbb{T}^{3}$. In a first…

Analysis of PDEs · Mathematics 2020-04-24 Andre Schenke

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 paper we prove several results related to the existence and uniqueness of solution to coupled highly nonlinear stochastic partial differential equations (PDEs). These equations are motivated by the dynamics of nematic liquid…

Probability · Mathematics 2016-10-05 Zdzislaw Brzeźniak , Erika Hausenblas , Paul Razafimandimby

In this paper, we prove the global well-posedness and interior regularity for the 2D Navier-Stokes equations driven by a fractional noise acting as an inhomogeneous Dirichlet-type boundary condition. The model describes a vertical slice of…

Analysis of PDEs · Mathematics 2025-06-17 Antonio Agresti , Alexandra Blessing , Eliseo Luongo

We study inviscid limits of invariant measures for the 2D Stochastic Navier-Stokes equations. As shown in \cite{Kuksin2004} the noise scaling $\sqrt{{\nu}}$ is the only one which leads to non-trivial limiting measures, which are invariant…

Analysis of PDEs · Mathematics 2013-02-05 Nathan Glatt-Holtz , Vladimir Sverak , Vlad Vicol

Strong solutions of the non-stationary Navier-Stokes equations under non-linearized slip or leak boundary conditions are investigated. We show that the problems are formulated by a variational inequality of parabolic type, to which…

Analysis of PDEs · Mathematics 2012-01-24 Takahito Kashiwabara

The Whittaker 2d growth model is a triangular continuous Markov diffusion process that appears in many scientific contexts. It has been theoretically intriguing to establish a large deviation principle for this 2d process with a scaling…

Probability · Mathematics 2020-09-29 Jun Gao , Jie Ding