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We study the solutions of the stochastic heat equation with multiplicative space-time white noise. We prove a comparison theorem between the solutions of stochastic heat equations with the same noise coefficient which is H\"{o}lder…

Probability · Mathematics 2017-06-14 Leonid Mytnik , Eyal Neuman

This paper studies the zero-noise limit of high-dimensional small-noise diffusion processes governed by the stochastic differential equation (SDE): \[ dX_{t}^{\varepsilon }=b(X_{t}^{\varepsilon })\,dt+\varepsilon \,dW_{t}, \quad…

Probability · Mathematics 2026-03-12 Liangquan Zhang

Existence, uniqueness, and regularity of a strong solution are obtained for stochastic PDEs with a colored noise $F$ and its super-linear diffusion coefficient: $$ du=(a^{ij}u_{x^ix^j}+b^iu_{x^i}+cu)dt+\xi|u|^{1+\lambda}dF, \quad…

Probability · Mathematics 2021-01-06 Jae-Hwan Choi , Beom-Seok Han

By using a change of scale and space, we study a class of stochastic differential equations (SDEs) whose solutions are drift--perturbed and exhibit behaviour analogous to standard Brownian motion including to the Law of the Iterated…

Probability · Mathematics 2013-10-11 John A. D. Appleby , Huizhong Appleby-Wu

This paper is devoted to order-one explicit approximations of random periodic solutions to multiplicative noise driven stochastic differential equations (SDEs) with non-globally Lipschitz coefficients. The existence of the random periodic…

Probability · Mathematics 2025-01-06 Yujia Guo , Xiaojie Wang , Yue Wu

We consider the approximation via modulation equations for nonlinear SPDEs on unbounded domains with additive space time white noise. Close to a bifurcation an infinite band of eigenvalues changes stability, and we study the impact of small…

Probability · Mathematics 2019-10-30 Luigi Amedeo Bianchi , Dirk Blömker , Guido Schneider

We consider a diffusion in a Gaussian random environment that is white in time and study the large-scale behavior of the quenched density with respect to the Lebesgue measure. We show that under diffusive rescaling, the fluctuations of the…

Probability · Mathematics 2025-10-20 Sotirios Kotitsas , Dejun Luo , Mario Maurelli

We analyze the nonlinear stochastic heat equation driven by heavy-tailed noise in free space and arbitrary dimension. The existence of a solution is proved even if the noise only has moments up to an order strictly smaller than its…

Probability · Mathematics 2019-03-26 Carsten Chong

Stochastic Partial Differential Equations (SPDEs) driven by random noise play a central role in modeling physical processes with rough spatio-temporal dynamics, such as turbulence flows, superconductors, and quantum dynamics. Although…

Machine Learning · Computer Science 2026-05-18 Yuantu Zhu , Zheyan Li , Dai Shi , Luke Thompson , Oliver Nash , Jose Miguel Lara Rangel , Siran Li , Bingguang Chen , Rongchan Zhu , Qi Meng , Hao Ni

We study stochastic differential equations(SDEs) with a small perturbation parameter. Under the dissipative condition on the drift coefficient and the local Lipschitz condition on the drift and diffusion coefficients we prove the existence…

Probability · Mathematics 2022-05-05 Luca Di Persio , Yuri Kondratiev , Viktorya Vardanyan

In this article, we continue the investigations initiated by the first author in Balan (2015) related to the study of stochastic partial differential equations (SPDEs) with L\'evy colored noise on $\mathbb{R}_{+} \times \mathbb{R}^d$. This…

Probability · Mathematics 2026-01-12 Raluca M. Balan , Juan J. Jiménez

We consider a general class of SPDEs in $\mathbb{R}^d$ driven by a Gaussian spatially homogeneous noise which is white in time. We provide sufficient conditions on the coefficients and the spectral measure associated to the noise ensuring…

Probability · Mathematics 2012-06-18 Lluis Quer-Sardanyons

We study a system of two reflected SPDEs which share a moving boundary. The equations describe competition at an interface and are motivated by the modelling of the limit order book in financial markets. The derivative of the moving…

Probability · Mathematics 2019-03-13 Ben Hambly , Jasdeep Kalsi

We study the notions of mild solution and generalized solution to a linear stochastic partial differential equation driven by a pure jump symmetric L\'evy white noise. We identify conditions for existence for these two kinds of solutions,…

Probability · Mathematics 2018-09-27 Robert C. Dalang , Thomas Humeau

We put forward a new method for proving weak uniqueness of stochastic equations with singular drifts driven by a non-Markov or infinite-dimensional noise. We apply our method to study stochastic heat equation (SHE) driven by Gaussian…

Probability · Mathematics 2025-04-01 Oleg Butkovsky , Leonid Mytnik

Consider stochastic partial differential equations (SPDEs) with fully local monotone coefficients in a Gelfand triple $V\subseteq H\subseteq V^*$ $$ \left\{ \begin{align} &dX_t=A(t,X_t)dt+B(t,X_t)dW_t,\ t\in (0,T]\\\\& X_0=x\in H,…

Probability · Mathematics 2024-01-11 Tianyi Pan , Shijie Shang , Jianliang Zhai , Tusheng Zhang

In this paper, we consider a new approach for semi-discretization in time and spatial discretization of a class of semi-linear stochastic partial differential equations (SPDEs) with multiplicative noise. The drift term of the SPDEs is only…

Numerical Analysis · Mathematics 2023-07-10 Yukun Li , Liet Vo , Guanqian Wang

We study stochastic reaction--diffusion equation $$ \partial_tu_t(x)=\frac12 \partial^2_{xx}u_t(x)+b(u_t(x))+\dot{W}_{t}(x), \quad t>0,\, x\in D $$ where $b$ is a generalized function in the Besov space…

Probability · Mathematics 2022-02-14 Siva Athreya , Oleg Butkovsky , Khoa Lê , Leonid Mytnik

We consider optimal control of a new type of non-local stochastic partial differential equations (SPDEs). The SPDEs have space interactions, in the sense that the dynamics of the system at time $t$ and position in space x also depend on the…

Optimization and Control · Mathematics 2021-07-01 Nacira Agram , Astrid Hilbert , Khouloud Makhlouf , Bernt Øksendal

We propose a novel framework for discovering Stochastic Partial Differential Equations (SPDEs) from data. The proposed approach combines the concepts of stochastic calculus, variational Bayes theory, and sparse learning. We propose the…

Machine Learning · Statistics 2023-06-29 Yogesh Chandrakant Mathpati , Tapas Tripura , Rajdip Nayek , Souvik Chakraborty