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We prove a Freidlin-Wentzell large deviation principle for general stochastic evolution equations with small perturbation multiplicative noises. In particular, our general result can be used to deal with a large class of quasi linear…

Probability · Mathematics 2008-01-14 Jiagang Ren , Xicheng Zhang

We prove a sample path Large Deviation Principle (LDP) for a class of jump processes whose rates are not uniformly Lipschitz continuous in phase space. Building on it we further establish the corresponding Wentzell-Freidlin (W-F) (infinite…

Probability · Mathematics 2017-10-24 Andrea Agazzi , Amir Dembo , Jean-Pierre Eckmann

In this article, we consider diffusion approximations for a general class of stochastic recursions. Such recursions arise as models for population growth, genetics, financial securities, multiplicative time series, numerical schemes and…

Probability · Mathematics 2016-01-13 David Kelly

In this paper we present a novel approach towards variance reduction for discretised diffusion processes. The proposed approach involves specially constructed control variates and allows for a significant reduction in the variance for the…

Probability · Mathematics 2017-12-05 Denis Belomestny , Stefan Häfner , Mikhail Urusov

Transition path theory (TPT) for diffusion processes is a framework for analysing the transitions of multiscale ergodic diffusion processes between disjoint metastable subsets of state space. Most methods for applying TPT involve the…

Numerical Analysis · Mathematics 2021-03-31 Nada Cvetković , Tim Conrad , Han Cheng Lie

The goal of this paper is to supplement the large deviation principle of the Freidlin--Wentzell theory on exit problems for diffusion processes with results of classical central limit theorem kind. We describe a class of situations where…

Probability · Mathematics 2013-10-23 Yuri Bakhtin , Andrzej Swiech

In this article we establish a large deviation principle for the family {\nu_{\epsilon}:\epsilon \in (0,1)} of distributions of the scaled stochastic processes {P_{-\log\sqrt{\epsilon}}Z_t}_{t\leq 1}, where (Z_t)_{t\in \lbrack 0,1]} is a…

Probability · Mathematics 2009-04-06 Z. Qian , C. Xu

In this article we establish a large deviation principle for the empirical measures of a simple spatially inhomogeneous random walk on $\overline{\mathbb{Z}}$, the two-point compactification of $\mathbb{Z}$. The classical Donsker--Varadhan…

Probability · Mathematics 2026-05-27 Jan-Luka Fatras

This paper reinterprets Freidlin-Wentzell's variational construction of the rate function in the large deviation principle for invariant measures from the weak KAM perspective. Through a one-dimensional irreversible diffusion process on a…

Analysis of PDEs · Mathematics 2023-10-12 Yuan Gao , Jian-Guo Liu

We prove a center manifold theorem for rough partial differential equations (rough PDEs). The class of rough PDEs we consider contains as a key subclass reaction-diffusion equations driven by nonlinear multiplicative noise, where the…

Probability · Mathematics 2021-11-11 Christian Kuehn , Alexandra Neamtu

This paper is concerned with the general theme of relating the Large Deviation Principle (LDP) for the invariant measures of stochastic processes to the associated sample path LDP. It is shown that if the sample path deviation function…

Probability · Mathematics 2023-08-10 Anatolii A. Puhalskii

We revisit strong approximation theory from a new perspective, culminating in a proof of the Koml\'os-Major-Tusn\'ady embedding theorem for the simple random walk. The proof is almost entirely based on a series of soft arguments and easy…

Probability · Mathematics 2010-07-05 Sourav Chatterjee

For overdamped Langevin systems subjected to weak thermal noise and nonconservative forces, we establish a connection between Freidlin-Wentzell large deviations theory and stochastic thermodynamics. First, we derive a series expansion of…

Statistical Mechanics · Physics 2024-09-13 Davide Santolin , Nahuel Freitas , Massimiliano Esposito , Gianmaria Falasco

We establish a Sanov type large deviation principle for an ensemble of interacting Brownian rough paths. As application a large deviations for the ($k$-layer, enhanced) empirical measure of weakly interacting diffusions is obtained. This in…

Probability · Mathematics 2019-04-23 Jean-Dominique Deuschel , Peter K. Friz , Mario Maurelli , Martin Slowik

A one dimensional fractional diffusion model with the Riemann-Liouville fractional derivative is studied. First, a second order discretization for this derivative is presented and then an unconditionally stable weighted average finite…

Numerical Analysis · Mathematics 2011-09-13 Ercília Sousa , Can Li

T. Lyons' rough path theory is something like a deterministic version of K. Ito's theory of stochastic differential equations, combined with ideas from K. T. Chen's theory of iterated path integrals. In this article we survey rough path…

Probability · Mathematics 2016-02-11 Yuzuru Inahama

We prove that the stationary measure associated to a boundary driven exclusion process in any dimension satisfies a large deviation principle with rate function given by the quasi potential of the Freidlin and Wentzell theory.

Probability · Mathematics 2009-08-14 Jonathan Farfan

In this paper, we revisit the proof of the large deviations principle of Wiener chaoses partially given by Borel, and then by Ledoux in its full form. We show that some heavy-tail phenomena observed in large deviations can be explained by…

Probability · Mathematics 2017-06-21 Fanny Augeri

The behavior of slow-fast diffusions as the separation of scale diverges is a well-studied problem in the literature. In this short paper, we revisit this problem and obtain a new proof of existing strong quantitative convergence estimates…

Optimization and Control · Mathematics 2025-10-28 Sumith Reddy Anugu , Vivek S. Borkar

This article concerns the large deviations regime and the consequent solution of the Kramers problem for a two-time scale stochastic system driven by a common jump noise signal perturbed in small intensity $\varepsilon>0$ and with…

Probability · Mathematics 2022-07-15 Pedro Catuogno , André de Oliveira Gomes