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Related papers: Stochastic PDEs with heavy-tailed noise

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In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise…

Probability · Mathematics 2010-10-12 Eulalia Nualart , Lluís Quer-Sardanyons

We consider a system of d non-linear stochastic heat equations in spatial dimension 1 driven by d-dimensional space-time white noise. The non-linearities appear both as additive drift terms and as multipliers of the noise. Using techniques…

Probability · Mathematics 2007-05-23 Robert C. Dalang , Davar Khoshnevisan , Eulalia Nualart

We consider stochastic heat equations with fractional Laplacian on $\mathbb{R}^d$. Here, the driving noise is generalized Gaussian which is white in time but spatially homogenous and the spatial covariance is given by the Riesz kernels. We…

Probability · Mathematics 2015-10-13 Kunwoo Kim

We consider a nonlinear stochastic partial differential equation (SPDE) that takes the form of the Camassa--Holm equation perturbed by a convective, position-dependent, noise term. We establish the first global-in-time existence result for…

Analysis of PDEs · Mathematics 2024-01-08 Luca Galimberti , Helge Holden , Kenneth H. Karlsen , Peter H. C. Pang

We consider nonlinear parabolic SPDEs of the form $\partial_t u=-(-\Delta)^{\alpha/2} u + b(u) +\sigma(u)\dot w$, where$\dot w$ denotes space-time white noise. The functions $b$ and $\sigma$ are both locally Lipschitz continuous. Under some…

Probability · Mathematics 2012-08-23 Mohammud Foondun , Rana Parshad

In this paper, we study the stochastic heat equation driven by a multiplicative space-time $G$-white noise within the framework of sublinear expectations. The existence and uniqueness of the mild solution are proved. By generalizing the…

Probability · Mathematics 2026-03-13 Xiaojun Ji , Shige Peng

In this paper, we consider a quasi-linear stochastic heat equation on $[0,1]$, with Dirichlet boundary conditions and controlled by the space-time white noise. We formally replace the random perturbation by a family of noisy inputs…

Probability · Mathematics 2009-07-16 Xavier Bardina , Maria Jolis , Lluis Quer-Sardanyons

In this paper we investigate a nonlinear stochastic partial differential equation (spde in short) perturbed by a space-correlated Gaussian noise in arbitrary dimension $d\geq1$, with a non-Lipschitz coefficient noisy term. The equation…

Probability · Mathematics 2011-04-29 Lahcen Boulanba , Mohamed Mellouk

In this article we consider the stochastic heat equation $u_{t}-\Delta u=\dot B$ in $(0,T) \times \bR^d$, with vanishing initial conditions, driven by a Gaussian noise $\dot B$ which is fractional in time, with Hurst index $H \in (1/2,1)$,…

Probability · Mathematics 2008-08-01 Raluca Balan , Ciprian Tudor

We consider a semilinear stochastic heat equation in spatial dimension at least $3$, forced by a noise that is white in time with a covariance kernel that decays like $\lvert x\rvert^{-2}$ as $\lvert x\rvert\to\infty$. We show that in an…

Probability · Mathematics 2025-09-30 Alexander Dunlap , Martin Hairer , Xue-Mei Li

Consider the stochastic heat equation $\partial_tu=\mathscr{L}u+\lambda\sigma(u)\xi$, where $\mathscr{L}$ denotes the generator of a L\'{e}vy process on a locally compact Hausdorff Abelian group $G$, $\sigma:\mathbf{R}\to\mathbf{R}$ is…

Probability · Mathematics 2015-09-10 Davar Khoshnevisan , Kunwoo Kim

In this note we consider stochastic heat equation with general additive Gaussian noise. Our aim is to derive some necessary and sufficient conditions on the Gaussian noise in order to solve the corresponding heat equation. We investigate…

Probability · Mathematics 2018-03-22 Yaozhong Hu , Yanghui Liu , Samy Tindel

Although stochastic optimization is central to modern machine learning, the precise mechanisms underlying its success, and in particular, the precise role of the stochasticity, still remain unclear. Modelling stochastic optimization…

Machine Learning · Statistics 2020-06-12 Liam Hodgkinson , Michael W. Mahoney

We consider a class of semilinear Volterra type stochastic evolution equation driven by multiplicative Gaussian noise. The memory kernel, not necessarily analytic, is such that the deterministic linear equation exhibits a parabolic…

Probability · Mathematics 2016-02-25 Boris Baeumer , Matthias Geissert , Mihaly Kovacs

We consider the stochastic wave and heat equations with affine multiplicative Gaussian noise which is white in time and behaves in space like the fractional Brownian motion with index $H \in (\frac14,\frac12)$. The existence and uniqueness…

Probability · Mathematics 2016-02-01 Raluca M. Balan , Maria Jolis , Lluís Quer-Sardanyons

In this article, we study the stochastic wave equation in spatial dimensions $d \le 2$ with multiplicative L\'evy noise that can have infinite $p$-th moments. Using the past light-cone property of the wave equation, we prove the existence…

Probability · Mathematics 2024-09-04 Juan J. Jiménez

In this paper, we study a class of nonlinear space-time fractional stochastic kinetic equations in $\mathbb{R}^d$ with Gaussian noise which is white in time and homogeneous in space. This type of equation constitutes an extension of the…

Probability · Mathematics 2022-01-19 Junfeng Liu

We study the solution to a nonlinear stochastic heat equation in $d\geq 3$. The equation is driven by a Gaussian multiplicative noise that is white in time and smooth in space. For a small coupling constant, we prove (i) the solution…

Probability · Mathematics 2020-08-24 Yu Gu , Jiawei Li

We study stochastic Volterra equations in Hilbert spaces driven by cylindrical Gaussian noise. We derive a mild formulation for the stochastic Volterra equation, prove the equivalence of mild and strong solutions, the existence and…

Probability · Mathematics 2023-11-14 Luigi Amedeo Bianchi , Stefano Bonaccorsi , Martin Friesen

For the nonlinear stochastic partial differential equation which is driven by multiplicative noise of the form \[D_t^\beta u = \left[ { - {{\left( { - \Delta } \right)}^s}u + \zeta \left( u \right)} \right]dt + A\sum\limits_{m \in Z_0^d}…

Probability · Mathematics 2022-11-18 Fei Gao , Xinyi Xie , Hui Zhan