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We consider a stochastic Cahn-Hilliard partial differential equation driven by a space-time white noise. We prove the Large Deviations Principle (LDP) for the law of the solutions in the H\"older norm. We use the weak convergence approach…

Probability · Mathematics 2017-08-29 Lahcen Boulanba , Mohamed Mellouk

We study the large deviations principle (LDP) of Donsker-Varadhan type for the white-forced Navier-Stokes system in a bounded domain. Under the assumption that the noise is non-degenerate, we establish level-2 and level-3 LDPs with rate…

Analysis of PDEs · Mathematics 2025-06-18 Meng Zhao

We consider conditional McKean-Vlasov stochastic differential equations (SDEs), such as the ones arising in the large-system limit of mean field games and particle systems with mean field interactions when common noise is present. The…

Probability · Mathematics 2020-04-02 Daniel Lacker , Mykhaylo Shkolnikov , Jiacheng Zhang

This paper is devoted to the problem of approximating non-linear Stochastic Partial Differential Equations (SPDEs) via interacting particle systems. In particular, we consider the Stochastic McKean-Vlasov equation, which is the…

Probability · Mathematics 2024-04-12 Letizia Angeli , Dan Crisan , Martin Kolodziejczyk , Michela Ottobre

In the first part of the paper we develop the sensitivity analysis for the nonlinear McKean-Vlasov diffusions stressing precise estimates of growth of solutions and their derivatives with respect to the initial data, under rather general…

Probability · Mathematics 2017-12-06 Vassili Kolokoltsov , Marianna Troeva

We study the stochastic Allen-Cahn equation driven by a noise term with intensity $\sqrt{\varepsilon}$ and correlation length $\delta$ in two and three spatial dimensions. We study diagonal limits $\delta, \varepsilon \to 0$ and describe…

Probability · Mathematics 2016-06-02 Martin Hairer , Hendrik Weber

We study the large deviations of a simple noise-perturbed dynamical system having continuous sets of steady states, which mimick those found in some partial differential equations related, for example, to turbulence problems. The system is…

Statistical Mechanics · Physics 2012-06-05 Freddy Bouchet , Hugo Touchette

We investigate a class of stochastic partial differential equations of reaction-diffusion type defined on graphs, which can be derived as the limit of SPDEs on narrow planar channels. In the first part, we demonstrate that this limit can be…

Probability · Mathematics 2024-03-21 Sandra Cerrai , Wen-Tai Hsu

In this paper, we study the connection between a general class of Conditional Mckean-Vlasov Stochastic Differential Equations (CMVSDEs) and its corresponding (infinite dimensional) Conditional Fokker-Planck Equation. The CMVSDE under…

Probability · Mathematics 2025-06-19 Qi Feng , Jin Ma

We establish the moderate deviation principle for the solutions of a class of stochastic partial differential equations with non-Lipschitz continuous coefficients. As an application, we derive the moderate deviation principle for two…

Probability · Mathematics 2016-11-04 Parisa Fatheddin , Jie Xiong

In this paper, we study averaging principle for a class of McKean-Vlasov stochastic differential equations (SDEs) that contain multiplicative fractional noise with Hurst parameter $H > $ 1/2 and highly oscillatory drift coefficient. Here…

Probability · Mathematics 2023-06-06 Bin Pei , Lifang Feng , Min Han

In this paper, we study well-posedness of McKean-Vlasov stochastic differential equations (SDE) whose drift depends pointwisely on marginal density and satisfies a local integrability condition in time-space variables. The drift and noise…

Probability · Mathematics 2025-11-20 Anh-Dung Le , Stéphane Villeneuve

This work focus on the large deviation principle for a two-time scale McKean-Vlasov system with jumps. Based on the variational framework of the McKean-Vlasov system with jumps, it is turned into weak convergence for the controlled system.…

Probability · Mathematics 2024-01-02 Xiaoyu Yang , Yong Xu

In this paper, we establish a moderate deviation principle for an abstract nonlinear equation forced by random noise of L\'evy type. This type of equation covers many hydrodynamical models, including stochastic 2D Navier-Stokes equations,…

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

This work is devoted to studying asymptotic behaviors for Volterra type McKean-Vlasov stochastic differential equations with small noise. By applying the weak convergence approach, we establish the large and moderate deviation principles.…

Probability · Mathematics 2024-10-11 Shanqi Liu , Yaozhong Hu , Hongjun Gao

The large deviation principle is established for the distributions of a class of generalized stochastic porous media equations for both small noise and short time.

Probability · Mathematics 2007-05-23 Michael Röckner , Feng-Yu Wang , Liming Wu

We establish a process level large deviation principle for systems of interacting Bessel-like diffusion processes. By establishing weak uniqueness for the limiting non-local SDE of McKean-Vlasov type, we conclude that the latter describes…

Probability · Mathematics 2013-03-14 Tomoyuki Ichiba , Mykhaylo Shkolnikov

In this paper, we provide a criterion on uniform large deviation principles (ULDP) for stochastic differential equations under locally weak monotone conditions and Lyapunov conditions, which can be applied to stochastic systems with…

Probability · Mathematics 2024-09-05 Jian Wang , Hao Yang

In this paper, we present a sufficient condition for the large deviation criteria of Budhiraja, Dupuis and Maroulas for functionals of Brownian motions. We then establish a large deviation principle for obstacle problems of quasi-linear…

Probability · Mathematics 2017-12-07 Anis Matoussi , Wissal Sabbagh , Tusheng Zhang

In this paper, we establish a large deviation principle for stochastic differential delay equations driven by both Brownian motions and Poisson random measures. The weak convergence method plays an important role.

Probability · Mathematics 2016-11-01 Yumeng Li , Ran Wang , Nian Yao , Shuguang Zhang