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The paper concerns itself with establishing large deviation principles for a sequence of stochastic integrals and stochastic differential equations driven by general semimartingales in infinite-dimensional settings. The class of…

Probability · Mathematics 2017-08-25 Arnab Ganguly

We derive an annealed large deviation principle for the normalised local times of a continuous-time random walk among random conductances in a finite domain in $\Z^d$ in the spirit of Donsker-Varadhan \cite{DV75}. We work in the interesting…

Probability · Mathematics 2011-04-11 Wolfgang König , Michele Salvi , Tilman Wolff

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

This article develops the viscosity solution approach to the large deviation principle for the following two- and three-dimensional stochastic convective Brinkman-Forchheimer equations on the torus $\mathbb{T}^d,\ d\in\{2,3\}$ with small…

Probability · Mathematics 2025-10-02 Sagar Gautam , Manil T. Mohan

We establish the large deviation principle for a topological Markov shift over infinite alphabet which satisfies strong combinatorial assumptions called ``finite irreducibility'' or ``finite primitiveness''. More precisely, we assume the…

Dynamical Systems · Mathematics 2019-03-19 Hiroki Takahasi

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

This paper is devoted to studying the averaging principle for stochastic differential equations with slow and fast time-scales, where the drift coefficients satisfy local Lipschitz conditions with respect to the slow and fast variables, and…

Probability · Mathematics 2020-08-19 Wei Liu , Michael Röckner , Xiaobin Sun , Yingchao Xie

We study the numerical approximation of time-dependent, possibly degenerate, second-order Hamilton-Jacobi-Bellman equations in bounded domains with nonhomogeneous Dirichlet boundary conditions. It is well known that convergence towards the…

Numerical Analysis · Mathematics 2025-03-27 Elisabetta Carlini , Athena Picarelli , Francisco J. Silva

The large deviation principle on phase space is proved for a class of Markov processes known as random population dynamics with catastrophes. In the paper we study the process which corresponds to the random population dynamics with linear…

Probability · Mathematics 2019-11-18 A. Logachov , O. Logachova , A. Yambartsev

We establish large deviation estimates related to the Dynkin--Lamperti theorem, which is a distributional limit theorem for the position of a subordinator immediately before it crosses a fixed level. Our approach relies on the theory of…

Probability · Mathematics 2025-11-11 Toru Sera

Let L be a positive line bundle over a projective complex manifold X. Consider the space of holomorphic sections of the tensor power of order p of L. The determinant of a basis of this space, together with some given probability measure on…

Complex Variables · Mathematics 2016-03-14 Tien-Cuong Dinh , Viet-Anh Nguyen

We prove a large-deviation principle (LDP) for the sample paths of jump Markov processes in the small noise limit when, possibly, all the jump rates vanish uniformly, but slowly enough, in a region of the state space. We further discuss the…

Probability · Mathematics 2021-02-26 Andrea Agazzi , Luisa Andreis , Robert I. A. Patterson , D. R. Michiel Renger

In this paper, we study large deviation principles of nonlinear filtering for McKean-Vlasov stochastic differential equations. First of all, we establish the large deviation principle for the space-distribution dependent Zakai equation by a…

Probability · Mathematics 2023-08-15 Huijie Qiao , Shengqing Zhu

The goal of this paper is to study the Moderate Deviation Principle (MDP) for a system of stochastic reaction-diffusion equations with a time-scale separation in slow and fast components and small noise in the slow component. Based on weak…

Probability · Mathematics 2022-02-03 Ioannis Gasteratos , Michael Salins , Konstantinos Spiliopoulos

In many stochastic models, the observables of interest are naturally encoded in double transforms (e.g., Laplace transforms) that couple spatial and temporal variables. Notably, the double transform often provides the only analytically…

Probability · Mathematics 2026-05-21 Giampaolo Cristadoro , Gaia Pozzoli

In this paper, we consider a class of nonautonomous multi-scale stochastic partial differential equations with fully local monotone coefficients. By introducing the evolution system of measures for time-inhomogeneous Markov semigroups, we…

Probability · Mathematics 2025-09-03 Mengyu Cheng , Xiaobin Sun , Yingchao Xie

In this article, we develop a framework to study the large deviation principle for matrix models and their quantized versions, by tilting the measures using the limits of spherical integrals obtained in [46,47]. As examples, we obtain 1. a…

Probability · Mathematics 2023-04-25 Serban Belinschi , Alice Guionnet , Jiaoyang Huang

In recent work [1] we uncovered intriguing connections between Otto's characterisation of diffusion as entropic gradient flow [16] on one hand and large-deviation principles describing the microscopic picture (Brownian motion) on the other.…

Analysis of PDEs · Mathematics 2014-03-05 Stefan Adams , Nicolas Dirr , Mark A. Peletier , Johannes Zimmer

We establish the (level-1) large deviation principles for three kinds of means associated with the backward continued fraction expansion. We show that: for the harmonic and geometric means, the rate functions vanish exactly at one point;…

Dynamical Systems · Mathematics 2019-12-30 Hiroki Takahasi

This paper is devoted to the problem of sample path large deviations for the Markov processes on R_+^N having a constant but different transition mechanism on each boundary set {x:x_i=0 for i\notin\Lambda, x_i>0 for i\in\Lambda}. The global…

Probability · Mathematics 2007-05-23 Irina Ignatiouk-Robert