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In this paper, we establish a central limit theorem and a moderate deviations for 2D stochastic primitive equations with multiplicative noise. The proof is mainly based on the weak convergence approach.

Probability · Mathematics 2017-07-10 Rangrang Zhang , Guoli Zhou

The present paper is devoted to the large deviation principle (LDP), with particular emphasis on the regularity of the quasi-potential for densities of stationary and quasi-stationary distributions of randomly perturbed dynamical systems.…

Dynamical Systems · Mathematics 2025-06-24 Chenchen Mou , Weiwei Qi , Zhongwei Shen , Yingfei Yi

In this paper, under a one-sided Lipschitz condition on the drift coefficient we adopt (via contraction principle) a exponential approximation argument to investigate large deviations for neutral stochastic functional differential…

Probability · Mathematics 2019-03-18 Yongqiang Suo , Chenggui Yuan

Dynamical system models with delayed dynamics and small noise arise in a variety of applications in science and engineering. In many applications, stable equilibrium or periodic behavior is critical to a well functioning system. Sufficient…

Probability · Mathematics 2017-10-27 David Lipshutz

A large deviation principle is established for a two-scale stochastic system in which the slow component is a continuous process given by a small noise finite dimensional It\^{o} stochastic differential equation, and the fast component is a…

Probability · Mathematics 2017-05-09 Amarjit Budhiraja , Paul Dupuis , Arnab Ganguly

We prove two Large deviations principles (LDP) in the zone of moderate deviation probabilities. First we establish LDP for the conditional distributions of moderate deviations of empirical bootstrap measures given empirical probability…

Statistics Theory · Mathematics 2014-05-22 Mikhail Ermakov

This paper is mainly concerned with a kind of fractional stochastic evolution equations driven by L\'evy noise in a bounded domain. We first state the well-posedness of the problem via iterative approximations and energy estimates. Then,…

Probability · Mathematics 2025-01-28 Jiaohui Xu , Tomás Caraballo , José Valero

We mainly investigate the log-Harnack inequality for the reflected stochastic partial differential equation driven by multiplicative noises based on the gradient estimate of the associated Markov semigroup. To do it, the penalization method…

Probability · Mathematics 2020-07-22 Bin Xie

Sample path large deviations for the laws of the solutions of stochastic nonlinear Schrodinger equations when the noise converges to zero are presented. The noise is a complex additive gaussian noise. It is white in time and colored space…

Analysis of PDEs · Mathematics 2007-11-08 Eric Gautier

We study a variant of the Fisher-KPP equation with nonlocal dispersal. Using the theory of large deviations, we show the emergence of a "Bramson-like" logarithmic delay for the linearised equation with step-like initial data. We conclude…

Analysis of PDEs · Mathematics 2024-01-19 Nathanaël Boutillon

This work focuses on the regularization by nonlinear noise for a class of partial differential equations that may only have local solutions. In particular, we obtain the global existence, uniqueness and the Feller property for stochastic 3D…

Probability · Mathematics 2025-07-28 Wei Hong , Shihu Li , Wei Liu

We establish a microscopic convexity principle for nonlinear elliptic and parabolic partial differential equations in general form.

Analysis of PDEs · Mathematics 2015-05-13 Baojun Bian , Pengfei Guan

In this paper, we consider stochastic reaction-diffusion equations with super-linear drift on the real line $\mathbb{R}$ driven by space-time white noise. A Freidlin-Wentzell large deviation principle is established by a modified weak…

Probability · Mathematics 2025-02-12 Yue Li , Shijie Shang , Jianliang Zhai

This paper establishes a Freidlin-Wentzell large deviation principle for stochastic differential equations(SDEs) under locally weak monotonicity conditions and Lyapunov conditions. We illustrate the main result of the paper by showing that…

Probability · Mathematics 2021-10-14 Jian Wang , Hao Yang , Jianliang Zhai , Tusheng Zhang

In this paper we consider the Allen-Cahn equation perturbed by a stochastic flux term and prove a large deviation principle. Using an associated stochastic flow of diffeomorphisms the equation can be transformed to a parabolic partial…

Probability · Mathematics 2015-01-19 Martin Heida , Matthias Röger

We prove the small-noise large deviation principle for the three-dimensional primitive equations with transport noise and turbulent pressure. Transport noise is important for geophysical fluid dynamics applications, as it takes into account…

Probability · Mathematics 2025-12-23 Antonio Agresti , Esmée Theewis

By comparing the original equations with the corresponding stationary ones, the moderate deviation principle (MDP) is established for unbounded additive functionals of several different models of distribution dependent SDEs, with…

Probability · Mathematics 2021-01-26 Panpan Ren , Shen Wang

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

We are dealing with the validity of a large deviation principle for a class of reaction-diffusion equations with polynomial nonlinearity, perturbed by a Gaussian random forcing. We are here interested in the regime where both the strength…

Probability · Mathematics 2017-05-02 Sandra Cerrai , Arnaud Debussche

This article introduces the splitting method to systems responding to rough paths as external stimuli. The focus is on nonlinear partial differential equations with rough noise but we also cover rough differential equations. Applications to…

Probability · Mathematics 2010-08-04 Peter Friz , Harald Oberhauser
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