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Estimation of a deterministic quantity observed in non-Gaussian additive noise is explored via order statistics approach. More specifically, we study the estimation problem when measurement noises either have positive supports or follow a…

Signal Processing · Electrical Eng. & Systems 2020-07-15 Kamiar Radnosrati , Gustaf Hendeby , Fredrik Gustafsson

We indicate that the nonlinear Schr\"odinger equation with white noise dispersion possesses stochastic symplectic and multi-symplectic structures. Based on these structures, we propose the stochastic symplectic and multi-symplectic methods,…

Numerical Analysis · Mathematics 2017-04-10 Jianbo Cui , Jialin Hong , Zhihui Liu , Weien Zhou

Various approaches to stochastic processes exist, noting that key properties such as measurability and continuity are not trivially satisfied. We introduce a new theory for Gaussian processes using improper linear functionals. Using a…

Statistics Theory · Mathematics 2020-10-15 Niels Lundtorp Olsen

White noise is a fundamental and fairly well understood stochastic process that conforms the conceptual basis for many other processes, as well as for the modeling of time series. Here we push a fresh perspective toward white noise that,…

Statistical Mechanics · Physics 2023-01-04 Alvaro Diaz-Ruelas

We study the bottom of the spectrum of the Anderson Hamiltonian $\mathcal{H}_L := -\partial_x^2 + \xi$ on $[0,L]$ driven by a white noise $\xi$ and endowed with either Dirichlet or Neumann boundary conditions. We show that, as…

Probability · Mathematics 2019-05-09 Laure Dumaz , Cyril Labbé

Consider a system of $n$ weakly interacting particles driven by independent Brownian motions. In many instances, it is well known that the empirical measure converges to the solution of a partial differential equation, usually called…

Probability · Mathematics 2020-07-28 Florian Bechtold , Fabio Coppini

Properties of systems driven by white non-Gaussian noises can be very different from these systems driven by the white Gaussian noise. We investigate stationary probability densities for systems driven by $\alpha$-stable L\'evy type noises,…

Statistical Mechanics · Physics 2009-11-13 B. Dybiec , E. Gudowska-Nowak , I. M. Sokolov

This short note is devoted to establishing the almost sure central limit theorem for the parabolic/hyperbolic Anderson models driven by colored-in-time Gaussian noises, completing recent results on quantitative central limit theorems for…

Probability · Mathematics 2025-04-01 Panqiu Xia , Guangqu Zheng

In this two-paper series, we prove the invariance of the Gibbs measure for a three-dimensional wave equation with a Hartree nonlinearity. The novelty lies in the singularity of the Gibbs measure with respect to the Gaussian free field. In…

Analysis of PDEs · Mathematics 2025-06-03 Bjoern Bringmann

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 paper, we consider a semi-linear stochastic strongly damped wave equation driven by additive Gaussian noise. Following a semigroup framework, we establish existence, uniqueness and space-time regularity of a mild solution to such…

Numerical Analysis · Mathematics 2020-08-10 Ruisheng Qi , Xiaojie Wang

We construct and study the Yang-Mills measure in two dimensions. According to the informal description given by the physicists, it is a probability measure on the space of connections modulo gauge transformations on a principal bundle with…

Probability · Mathematics 2007-05-23 Thierry Levy

In this paper, we study spatial averages for the parabolic Anderson model in the Skorohod sense driven by rough Gaussian noise, which is colored in space and time. We include the case of a fractional noise with Hurst parameters $H_0$ in…

Probability · Mathematics 2021-04-14 David Nualart , Xiaoming Song , Guangqu Zheng

A new image denoising algorithm to deal with the additive Gaussian white noise model is given. Like the non-local means method, the filter is based on the weighted average of the observations in a neighborhood, with weights depending on the…

Other Statistics · Statistics 2011-11-04 Qiyu Jin , Ion Grama , Quansheng Liu

In this paper, we establish the existence and uniqueness of invariant measures for a class of semilinear stochastic partial differential equations driven by multiplicative noise on a bounded domain. The main results can be applied to SPDEs…

Probability · Mathematics 2018-12-12 Zhao Dong , Rangrang Zhang

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

Based on the statistical dynamical mean field theory, we investigate, in a generic model for a strongly coupled disordered electron-phonon system, the competition between polaron formation and Anderson localization. The statistical…

Strongly Correlated Electrons · Physics 2007-05-23 Franz X. Bronold , Andreas Alvermann , Holger Fehske

We prove Strichatz inequalities for the Schr{\"o}dinger equation and the wave equation with multiplicative noise on a two-dimensional manifold. This relies on the Anderson Hamiltonian H described using high order paracontrolled calculus. As…

Analysis of PDEs · Mathematics 2024-03-13 Antoine Mouzard , Immanuel Zachhuber

We study the asymptotics of Allen-Cahn-type bistable reaction-diffusion equations which are additively perturbed by a stochastic forcing (time white noise). The conclusion is that the long time, large space behavior of the solutions is…

Analysis of PDEs · Mathematics 2019-09-13 Pierre-Louis Lions , Panagiotis E. Souganidis

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
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