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We introduce and analyze a broad class of continuous directed polymers in $\mathbb{R}^d$ driven by Gaussian environments that are white in time and spatially correlated, under Dalang's condition. Using an It\^o-renormalized…

Probability · Mathematics 2026-03-09 Le Chen , Cheng Ouyang , Samy Tindel , Panqiu Xia

We prove a large deviation principle for the sequence of push-forwards of empirical measures in the setting of Riesz potential interactions on compact subsets K in R^d with continuous external fields. Our results are valid for base measures…

Classical Analysis and ODEs · Mathematics 2016-10-27 Tom Bloom , Norman Levenberg , Franck Wielonsky

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 establish a Freidlin-Wentzell type large deviation principle (LDP) for a class of stochastic partial differential equations with locally monotone coefficients driven by L\'evy noise. Our results essentially improve a recent work on this…

Probability · Mathematics 2024-01-23 Weina Wu , Jianliang Zhai , Jiahui Zhu

We introduce a variational theory for processes adapted to the multi-dimensional Brownian motion filtration that provides a differential structure allowing to describe infinitesimal evolution of Wiener functionals at very small scales. The…

Probability · Mathematics 2017-12-01 Dorival Leão , Alberto Ohashi , Alexandre B. Simas

Suppose $ E$ is a space with a null-recurrent Markov kernel $ P$. Furthermore, suppose there are infinite particles with variable weights on $ E$ performing a random walk following $ P$. Let $ X_{t}$ be a weighted functional of the position…

Probability · Mathematics 2010-12-01 Souvik Ghosh

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

In this paper we consider examples of positive generalized Wiener functions and we establish a large deviation principle for the generalized multiple intersection local time of the multidimensional Brownian motion.

Probability · Mathematics 2025-07-18 Andrey A. Dorogovtsev , Naoufel Salhi

We study the large deviation function of the displacement of a Brownian particle confined on a ring. In the zero noise limit this large deviation function has a cusp at zero velocity given by the Freidlin-Wentzell theory. We develop a WKB…

Statistical Mechanics · Physics 2019-02-20 Karel Proesmans , Bernard Derrida

Polynomial chaos is a powerful technique for propagating uncertainty through ordinary and partial differential equations. Random variables are expanded in terms of orthogonal polynomials and differential equations are derived for the…

Computation · Statistics 2014-06-18 José Miguel Pasini , Tuhin Sahai

We study the convergence to the multiple Wiener-It\^{o} integral from processes with absolutely continuous paths. More precisely, consider a family of processes, with paths in the Cameron-Martin space, that converges weakly to a standard…

Probability · Mathematics 2007-12-27 Xavier Bardina , Maria Jolis , Ciprian Tudor

A criterion for proving a strong form of propagation of chaos on the path space, known as entropy chaos, for a general interacting diffusion system is proposed. Our analysis focuses on the class of conservative diffusions introduced by…

Probability · Mathematics 2026-04-17 Luigi Borasi , Francesco Carlo De Vecchi , Stefania Ugolini

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 consider Gaussian random waves on hyperbolic spaces and establish variance asymptotics and central limit theorems for a large class of their integral functionals, both in the high-frequency and large domain limits. Our strategy of proof…

Probability · Mathematics 2023-02-14 Francesco Grotto , Giovanni Peccati

We introduce order-based diffusion processes as the solutions to multidimensional stochastic differential equations, with drift coefficient depending only on the ordering of the coordinates of the process and diffusion matrix proportional…

Probability · Mathematics 2014-03-11 Benjamin Jourdain , Julien Reygner

We prove a maximal-type large deviation principle for dynamical systems with arbitrarily slow polynomial mixing rates. Also several applications, particularly to billiard systems, are presented.

Dynamical Systems · Mathematics 2022-08-09 Leonid A. Bunimovich , Yaofeng Su

The sample paths of white noise are proved to be elements of certain Besov spaces with dominating mixed smoothness. Unlike in isotropic spaces, here the regularity does not get worse with increasing space dimension. Consequently, white…

Probability · Mathematics 2020-05-25 Felix Hummel

We prove a Freidlin-Wentzell result for stochastic differential equations in infinite-dimensional Hilbert spaces perturbed by a cylindrical Wiener process. We do not assume the drift to be Lipschitz continuous, but only continuous with at…

Probability · Mathematics 2022-08-03 Umberto Pappalettera

We investigate the effects of random perturbations on fully chaotic open systems. Perturbations can be applied to each trajectory independently (white noise) or simultaneously to all trajectories (random map). We compare these two scenarios…

Chaotic Dynamics · Physics 2015-05-12 Tamas Bodai , Eduardo G. Altmann , Antonio Endler

We revisit Wschebor's theorems on small increments for processes with scaling and stationary properties and deduce large deviation principles.

Probability · Mathematics 2019-07-05 Jose R. Leon , José León , Alain Rouault