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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

In this paper, we establish a large deviation principle for a type of stochastic partial differential equations (SPDEs) with locally monotone coefficients driven by L\'evy noise. The weak convergence method plays an important role.

Probability · Mathematics 2016-06-08 Jie Xiong , Jianliang Zhai

Large deviation principle by the weak convergence approach is established for the stochastic nonlinear Schrodinger equation in one-dimension and as an application the exit problem is investigated.

Analysis of PDEs · Mathematics 2019-11-04 Parisa Fatheddin , Zhaoyang Qiu

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 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 consider a class of reflected stochastic differential equations for which the constraint is not on the paths of the solution but on its law. We establish a small noise large deviation principle, a large deviation for short…

Probability · Mathematics 2023-03-27 Ping Chen , Jianliang Zhai

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 consider a planar viscous shock for a scalar viscous conservation law with a strictly convex flux in multi-dimensional setting, where the transversal direction is periodic. We first show the contraction property for any solutions…

Analysis of PDEs · Mathematics 2025-01-20 Moon-Jin Kang , HyeonSeop Oh

This paper is concerned with the large deviation principle of the stochastic reaction-diffusion lattice systems defined on the N-dimensional integer set, where the nonlinear drift term is locally Lipschitz continuous with polynomial growth…

Dynamical Systems · Mathematics 2023-05-12 Bixiang Wang

We are interested in viscous scalar conservation laws with a white-in-time but spatially correlated stochastic forcing. The equation is assumed to be one-dimensional and periodic in the space variable, and its flux function to be locally…

Analysis of PDEs · Mathematics 2020-04-27 Sofiane Martel , Julien Reygner

In this paper, we investigate the uniform large deviation principle of the fractional stochastic reaction-diffusion equation on the entire space R^n as the noise intensity approaches zero. The nonlinear drift term is dissipative and has a…

Probability · Mathematics 2024-06-14 Bixiang Wang

We find a representation of smooth solutions to the Cauchy problem for a scalar multidimensional conservation law as small diffusion limit of a stochastic perturbation along characteristics. It helps, in particular, to study the process of…

Analysis of PDEs · Mathematics 2012-10-11 S. Albeverio , O. Rozanova

In this paper, we establish a large deviation principle for 2D stochastic Chemotaxis-Navier-Stokes equation perturbed by a small multiplicative noise. The main difficulties come from the lack of a suitable compact embedding into the space…

Probability · Mathematics 2024-06-25 Yunfeng Chen , Xuhui Peng , Jianliang Zhai

In this paper, we consider the large deviations of invariant measure for the 3D stochastic hyperdissipative Navier-Stokes equations driven by additive noise. The unique ergodicity of invariant measure as a preliminary result is proved using…

Analysis of PDEs · Mathematics 2023-07-11 Zhaoyang Qiu , Hui Liu , Chengfeng Sun

We demonstrate the large deviation property for the mild solutions of stochastic evolution equations with monotone nonlinearity and multiplica- tive noise. This is achieved using the recently developed weak convergence method, in studying…

Probability · Mathematics 2010-03-17 Hassan Dadashi-Arani , Bijan Z. Zangeneh

Large deviations principles characterize the exponential decay rates of the probabilities of rare events. Cerrai and Rockner [13] proved that systems of stochastic reaction-diffusion equations satisfy a large deviations principle that is…

Probability · Mathematics 2021-08-11 Michael Salins

We demonstrate the large deviation principle in the small noise limit for the mild solution of stochastic evolution equations with monotone nonlinearity. A recently developed method, weak convergent method, has been employed in studying the…

Probability · Mathematics 2013-09-10 Hassan Dadashi

We prove a large deviation principle for stochastic differential equations driven by semimartingales, with additive controls. Conditions are given in terms of characteristics of driven semimartingales, so that if the noise-control pairs…

Probability · Mathematics 2024-08-13 Qiao Huang , Wei Wei , Jinqiao Duan

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

We establish the well-posedness of the Neumann problem for stochastic conservation laws with multiplicative noise. As a major step for establishing the uniqueness of the kinetic solution to the referred problem we establish the new strong…

Analysis of PDEs · Mathematics 2020-07-30 Hermano Frid , Yachun Li , Daniel Marroquin , João F. C. Nariyoshi , Zirong Zeng