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We investigate synchronization by noise for stochastic differential equations (SDEs) driven by a fractional Brownian motion (fbm) with Hurst index $H\in(0,1)$. Provided that the SDE has a negative top Lyapunov exponent, we show that a weak…

Probability · Mathematics 2026-03-16 Alexandra Blessing , Mazyar Ghani Varzaneh

The main purpose of this paper is to study the problem of determining initial condition of nonlinear parabolic equation from noisy observations of the final condition. We introduce a regularized method to establish an approximate solution.…

Analysis of PDEs · Mathematics 2017-11-30 Erkan Nane , Nguyen Huy Tuan

This work is devoted to non-linear stochastic Schr\"odinger equations with multiplicative fractional noise, where the stochastic integral is defined following the Riemann-Stieljes approach of Z\"ahle. Under the assumptions that the initial…

Analysis of PDEs · Mathematics 2013-04-01 Olivier Pinaud

In the paper, we address parametric and non-parametric estimation for nonlinear stochastic differential equations with additive Hermite noise with possibly nonlinear scaling. We assume that a single trajectory of the solution is observed…

Statistics Theory · Mathematics 2025-06-23 Petr Coupek , Pavel Kriz

On a closed Riemannian manifold, we construct a family of intrinsic Gaussian noises indexed by a regularity parameter $\alpha\geq0$ to study the well-posedness of the parabolic Anderson model. We show that with rough initial conditions, the…

Probability · Mathematics 2025-12-17 Hongyi Chen , Cheng Ouyang

We consider the Anderson Hamiltonian (AH) and the parabolic Anderson model (PAM) with white noise and Dirichlet boundary condition on a bounded planar domain $D\subset\mathbb R^2$. We compute the small time asymptotics of the AH's…

Probability · Mathematics 2026-03-31 Pierre Yves Gaudreau Lamarre , Yuanyuan Pan

We consider stochastic dynamics of a particle on a plane in presence of two noises and a confining parabolic potential - an analog of the experimentally-relevant Brownian Gyrator (BG) model. In contrast to the standard BG model, we suppose…

Statistical Mechanics · Physics 2025-12-16 Timothée Herbeau , Leonid Pastur , Pascal Viot , Gleb Oshanin

We study the bi-parameter local linearization of the one-dimensional nonlinear stochastic wave equation driven by a Gaussian noise, which is white in time and has a spatially homogeneous covariance structure of Riesz-kernel type. We…

Probability · Mathematics 2025-10-03 Guoping Liu , Ran Wang

We develop and analyze a numerical method for stochastic time-fractional diffusion driven by additive fractionally integrated Gaussian noise. The model involves two nonlocal terms in time, i.e., a Caputo fractional derivative of order…

Numerical Analysis · Mathematics 2018-10-04 Bangti Jin , Yubin Yan , Zhi Zhou

This paper is devoted to the study of numerical approximation schemes for a class of parabolic equations on (0, 1) perturbed by a non-linear rough signal. It is the continuation of [8, 7], where the existence and uniqueness of a solution…

Probability · Mathematics 2016-03-01 Aurélien Deya

Estimating associations between spatial covariates and responses - rather than merely predicting responses - is central to environmental science, epidemiology, and economics. For instance, public health officials might be interested in…

Machine Learning · Statistics 2025-11-11 David R. Burt , Renato Berlinghieri , Stephen Bates , Tamara Broderick

The Cahn-Hilliard/Allen-Cahn equation with noise is a simplified mean field model of stochastic microscopic dynamics associated with adsorption and desorption-spin flip mechanisms in the context of surface processes. For such an equation we…

Probability · Mathematics 2022-10-13 Dimitra C. Antonopoulou , Geogia Karali , Annie Millet

In this work we establish weak convergence rates for temporal discretisations of stochastic wave equations with multiplicative noise, in particular, for the hyperbolic Anderson model. For this class of stochastic partial differential…

Probability · Mathematics 2024-05-24 Sonja Cox , Arnulf Jentzen , Felix Lindner

We implement a Laplace method for the renormalised solution to the generalised 2D Parabolic Anderson Model (gPAM) driven by a small spatial white noise. Our work rests upon Hairer's theory of regularity structures which allows to generalise…

Probability · Mathematics 2022-03-22 Peter K. Friz , Tom Klose

In this article, we study a numerical scheme for stochastic differential equations driven by fractional Brownian motion with Hurst parameter H in (1/4; 1/2). Towards this end, we apply Doss-Sussmann representation of the solution and an…

Probability · Mathematics 2019-04-08 H. Araya , J. A. León , S. Torres

We study the spatial homogenisation of parabolic linear stochastic PDEs exhibiting a two-scale structure both at the level of the linear operator and at the level of the Gaussian driving noise. We show that in some cases, in particular when…

Probability · Mathematics 2012-02-09 Martin Hairer , David Kelly

In this paper we study a class of stochastic partial differential equations in the whole space $\mathbb{R}^{d}$, with arbitrary dimension $d\geq 1$, driven by a Gaussian noise white in time and correlated in space. The differential operator…

Probability · Mathematics 2007-05-23 Lahcen Boulanba , M'hamed Eddahbi , Mohamed Mellouk

Both Wick-Ito-Skorokhod and Stratonovich interpretations of the parabolic Anderson model (PAM) lead to solutions that are real analytic as functions of the noise intensity e, and, in the limit e->0, the difference between the two solutions…

Analysis of PDEs · Mathematics 2018-09-18 Hyun-Jung Kim , Sergey V. Lototsky

We investigate the effect of diagonal disorder on bosons in an optical lattice described by an Anderson-Hubbard model at zero temperature. It is known that within Gutzwiller mean-field theory spatially resolved calculations suffer…

Disordered Systems and Neural Networks · Physics 2009-06-30 U. Bissbort , W. Hofstetter

We study the non-stationary Anderson parabolic problem on the lattice $Z^d$, i.e., the equation \begin{equation}\label{andersonmodel} \begin{aligned} \frac{\partial u}{\partial t} &=\varkappa \mathcal{A}u(t,x)+\xi_{t}(x)u(t,x) u(0,x)…

Probability · Mathematics 2023-01-10 Xiaoyun Chen , Dan Han , Stanislav Molchanov