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This paper discusses the non-parametric estimation of a non-linear reaction term in a semi-linear parabolic stochastic partial differential equation (SPDE). The estimator's consistency is due to the spatial ergodicity of the SPDE while the…

Probability · Mathematics 2025-01-09 Sascha Gaudlitz

This paper introduces a spatio-temporal resonator model and an inference method for detection and estimation of nearly periodic temporal phenomena in spatio-temporal data. The model is derived as a spatial extension of a stochastic harmonic…

Computation · Statistics 2013-12-23 Arno Solin , Simo Särkkä

In this note we introduce a new approach to rough and stochastic partial differential equations (RPDEs and SPDEs): we consider general Banach spaces as state spaces and -- for the sake of simiplicity -- finite dimensional sources of noise,…

Probability · Mathematics 2009-08-21 Josef Teichmann

Consider stochastic partial differential equations (SPDEs) with fully local monotone coefficients in a Gelfand triple $V\subseteq H \subseteq V^*$: \begin{align*} \left\{ \begin{aligned} dX(t) & = A(t,X(t))dt + B(t,X(t))dW(t), \quad t\in…

Probability · Mathematics 2025-08-07 Michael Röckner , Shijie Shang , Tusheng Zhang

We prove the existence and uniqueness of mild solution for the stochastic partial differential equation $$\left(\partial^\alpha - \textit{B} \right) u(t,x)= u(t,x) \cdot \dot{W}(t,x),$$ where $$\alpha \in (1/2, 1)\cup(1, 2);$$ $\textit{B}$…

Probability · Mathematics 2016-05-09 Guannan Hu

We consider stochastic wave equations in spatial dimensions $d \geq 4$. We assume that the driving noise is given by a Gaussian noise that is white in time and has some spatial correlation. When the spatial correlation is given by the Riesz…

Probability · Mathematics 2025-01-09 Masahisa Ebina

We study existence and uniqueness of a variational solution in terms of stochastic variational inequalities (SVI) to stochastic nonlinear diffusion equations with a highly singular diffusivity term and multiplicative Stratonovich…

Analysis of PDEs · Mathematics 2016-08-17 Ioana Ciotir , Jonas M. Tölle

In this paper, we aim to develop a new weak formulation that ensures well-posedness for a broad range of stochastic partial differential equations with pseudo-differential operators whose symbols depend only on time and spatial frequencies.…

Probability · Mathematics 2024-09-10 Jae-Hwan Choi , Ildoo Kim

We consider the numerical approximation of a general second order semi--linear parabolic stochastic partial differential equation (SPDEs) driven by space-time noise, for multiplicative and additive noise. We examine convergence of…

Numerical Analysis · Mathematics 2015-03-19 Gabriel J Lord , Antoine Tambue

We perturb with an additive Gaussian white noise the Hamiltonian system associated to a cubic anharmonic oscillator. The stochastic system is assumed to start from initial conditions that guarantee the existence of a periodic solution for…

Probability · Mathematics 2019-07-26 Enrico Bernardi , Alberto Lanconelli

In this paper, we investigate the existence and finite-time blow-up for the solution of a reaction-diffusion system of semilinear stochastic partial differential equations (SPDEs) subjected to a two-dimensional fractional Brownian motion…

Analysis of PDEs · Mathematics 2024-05-28 S. Sankar , Manil T. Mohan , S. Karthikeyan

Strong convergence rates for numerical approximations of semilinear stochastic partial differential equations (SPDEs) with smooth and regular nonlinearities are well understood in the literature. Weak convergence rates for numerical…

Probability · Mathematics 2016-12-13 Mario Hefter , Arnulf Jentzen , Ryan Kurniawan

A fully discrete approximation of the semi-linear stochastic wave equation driven by multiplicative noise is presented. A standard linear finite element approximation is used in space and a stochastic trigonometric method for the temporal…

Numerical Analysis · Mathematics 2015-11-26 Rikard Anton , David Cohen , Stig Larsson , Xiaojie Wang

In this paper, we establish a large deviation principle for a type of stochastic partial differential equations (SPDEs) with locally monotone coefficients driven by L\'evy noise. The weak convergence method plays an important role.

Probability · Mathematics 2016-06-08 Jie Xiong , Jianliang Zhai

We introduce a new class of numerical methods for solving McKean-Vlasov stochastic differential equations, which are relevant in the context of distribution-dependent or mean-field models, under super-linear growth conditions for both the…

Numerical Analysis · Mathematics 2025-02-10 Jiamin Jian , Qingshuo Song , Xiaojie Wang , Zhongqiang Zhang , Yuying Zhao

Elliptic stochastic differential equations (SDE) make sense when the coefficients are only continuous. We study the corresponding linearized SDE whose coefficients are not assumed to be locally bounded. This leads to existence of…

Probability · Mathematics 2010-08-09 Xin Chen , Xue-Mei Li

We study the time-dependent spatial averages of a critical stochastic partial differential equation, namely the stochastic heat equation in dimension $d\geq 3$ with noise white in time and colored in space with covariance kernel…

Probability · Mathematics 2024-11-15 Sefika Kuzgun , Ran Tao

The coefficients in a second order parabolic linear stochastic partial differential equation (SPDE) are estimated from multiple spatially localised measurements. Assuming that the spatial resolution tends to zero and the number of…

Statistics Theory · Mathematics 2024-07-26 Randolf Altmeyer , Anton Tiepner , Martin Wahl

This work aims to prove the small time large deviation principle (LDP) for a class of stochastic partial differential equations (SPDEs) with locally monotone coefficients in generalized variational framework. The main result could be…

Probability · Mathematics 2021-02-23 Shihu Li , Wei Liu , Yingchao Xie

In this paper we are interested in a quasi-linear hyperbolic stochastic differential equation (HSPDE) when the vector field is merely bounded and measurable. Although the deterministic counterpart of such equation may be ill-posed (in the…

Probability · Mathematics 2025-09-08 Antoine-Marie Bogso , Moustapha Dieye , Olivier Menoukeu Pamen , Frank Proske