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We determine with positive probability the Hausdorff dimension of the level sets of a class of Navier-Stokes \alpha-models at finite viscosity, forced by mildly rough Gaussian white noise.

Probability · Mathematics 2013-08-21 Lorenzo Baglioni , Marco Romito

We prove pathwise large deviation principles of slow variables in slow-fast systems in the limit of time-scale separation tending to infinity. In the limit regime we consider, the convergence of the slow variable to its deterministic limit…

Probability · Mathematics 2020-11-25 Richard C. Kraaij , Mikola C. Schlottke

In this paper, we first prove the global well-posedness of a scaled anisotropic Navier-Stokes system and the hydrostatic Navier-Stokes system in a 2-D striped domain with small analytic data in the tangential variable. Then we justify the…

Analysis of PDEs · Mathematics 2019-04-10 M. Paicu , P. Zhang , Z. Zhang

This paper concerns the 3-dimensional Lagrangian Navier-Stokes $\alpha$ model and the limiting Navier-Stokes system on smooth bounded domains with a class of vorticity-slip boundary conditions and the Navier-slip boundary conditions. It…

Analysis of PDEs · Mathematics 2015-06-05 Yuelong Xiao , Zhouping Xin

In this paper, we study the large deviation principle of invariant measures of stochastic reaction-diffusion lattice systems driven by multiplicative noise. We first show that any limit of a sequence of invariant measures of the stochastic…

Probability · Mathematics 2024-05-07 Bixiang Wang

We study small noise large deviation asymptotics for stochastic differential equations with a multiplicative noise given as a fractional Brownian motion $B^H$ with Hurst parameter $H>\frac12$. The solutions of the stochastic differential…

Probability · Mathematics 2020-06-18 Amarjit Budhiraja , Xiaoming Song

We study two problems. First, we consider the large deviation behavior of empirical measures of certain diffusion processes as, simultaneously, the time horizon becomes large and noise becomes vanishingly small. The law of large numbers…

Probability · Mathematics 2023-09-14 Amarjit Budhiraja , Pavlos Zoubouloglou

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 utilize the weak convergence method to establish the Freidlin--Wentzell large deviations principle (LDP) for stochastic delay differential equations (SDDEs) with super-linearly growing coefficients, which covers a large class of cases…

Probability · Mathematics 2022-01-04 Diancong Jin , Ziheng Chen , Tau Zhou

We discuss the Donsker-Varadhan theory of large deviations in the framework of Hamiltonian systems thermostated by a Gaussian stochastic coupling. We derive a general formula for the Donsker-Varadhan large deviation functional for dynamics…

Mathematical Physics · Physics 2009-11-13 T. Bodineau , R. Lefevere

For finite size Markov chains, the Donsker-Varadhan theory fully describes the large deviations of the time averaged empirical measure. We are interested in the extension of the Donsker-Varadhan theory for a large size non-equilibrium…

Probability · Mathematics 2024-05-06 Thierry Bodineau , Benoit Dagallier

We establish the large deviation principle for the slow variables in slow-fast dynamical system driven by both Brownian noises and L\'evy noises. The fast variables evolve at much faster time scale than the slow variables, but they are…

Dynamical Systems · Mathematics 2022-11-22 Shenglan Yuan , René Schilling , Jinqiao Duan

In this paper, we study the large deviation principle (LDP) for obstacle problems governed by a T-monotone operator and small multiplicative stochastic reaction. Our approach relies on a combination of new sufficient condition to prove LDP…

Probability · Mathematics 2024-10-11 Yassine Tahraoui

We prove unconditional long-time stability for a particular velocity-vorticity discretization of the 2D Navier-Stokes equations. The scheme begins with a formulation that uses the Lamb vector to couple the usual velocity-pressure system to…

Analysis of PDEs · Mathematics 2015-11-26 Timo Heister , Maxim A. Olshanskii , Leo G. Rebholz

In this paper, we modified the three dimensional Navier-Stokes equations by adding a l-Laplacian. We provide upper bounds on the two-dimensional Hausdorff measure the level sets of the vorticity of solutions. We express them in terms of the…

Analysis of PDEs · Mathematics 2010-12-30 Abdelhafid Younsi

This work addresses some asymptotic behavior of solutions to the stochastic convective Brinkman-Forchheimer (SCBF) equations perturbed by multiplicative Gaussian noise in bounded domains. Using a weak convergence approach of Budhiraja and…

Probability · Mathematics 2021-06-02 Manil T. Mohan

We introduce a framework to justify hydrodynamic limits of the Vlasov-Navier-Stokes system. We specifically study high friction regimes, which take into account the fact that particles of the dispersed phase are light (resp. small) compared…

Analysis of PDEs · Mathematics 2021-03-12 Daniel Han-Kwan , David Michel

This paper presents the variational discretization of the compressible Navier-Stokes-Fourier system, in which the viscosity and the heat conduction terms are handled within the variational approach to nonequilibrium thermodynamics as…

Differential Geometry · Mathematics 2022-02-09 Benjamin Couéraud , François Gay-Balmaz

Our aim is to unify and extend the large deviation upper and lower bounds for the occupation times of a Markov process with $L_2$ semigroups under minimal conditions on the state space and the process trajectories; for example, no strong…

Probability · Mathematics 2008-09-24 Naresh Jain , Nicolai Krylov

Stochastic Navier-Stokes equations in 2D and 3D possibly unbounded domains driven by a multiplicative Gaussian noise are considered. The noise term depends on the unknown velocity and its spatial derivatives. The existence of a martingale…

Probability · Mathematics 2017-01-03 Zdzisław Brzeźniak , Elżbieta Motyl
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