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The paper focuses on discrete-type approximations of solutions to non-homogeneous stochastic differential equations (SDEs) involving fractional Brownian motion (fBm). We prove that the rate of convergence for Euler approximations of…

Probability · Mathematics 2012-06-18 Yuliya Mishura , Georgiy Shevchenko

A fully discrete approximation of the linear stochastic wave equation driven by additive noise is presented. A standard finite element method is used for the spatial discretisation and a stochastic trigonometric scheme for the temporal…

Numerical Analysis · Mathematics 2013-03-05 D. Cohen , S. Larsson , M. Sigg

Solving the Fokker-Planck equation for high-dimensional complex dynamical systems remains a pivotal yet challenging task due to the intractability of analytical solutions and the limitations of traditional numerical methods. In this work,…

Machine Learning · Computer Science 2025-09-04 Naoufal El Bekri , Lucas Drumetz , Franck Vermet

This paper attempts to obtain necessary and sufficient conditions to solve the parabolic Anderson model with fractional Gaussian noises: $\frac{\partial}{\partial t}u(t,x)=\frac{1}{2}\Delta u(t,x)+u(t,x)\dot{W}(t,x)$, where $ {W}(t,x)$ is…

Probability · Mathematics 2024-08-01 Shuhui Liu , Yaozhong Hu , Xiong Wang

In this paper, we consider fractional parabolic equation of the form $ \frac{\partial u}{\partial t}=-(-\Delta)^{\frac{\alpha}{2}}u+u\dot W(t,x)$, where $-(-\Delta)^{\frac{\alpha}{2}}$ with $\alpha\in(0,2]$ is a fractional Laplacian and…

Probability · Mathematics 2016-04-13 Xia Chen , Yaozhong Hu , Jian Song , Xiaoming Song

Motivated by the evolution of a population in a slowly varying random environment, we consider the 1D Anderson model on finite volume, with viscosity $ \kappa > 0 $: $$ \partial_{t} u(t,x) = \kappa \Delta u(t,x) + \xi(t, x) u(t,x), \quad…

Probability · Mathematics 2021-10-01 Tommaso Rosati

Partially motivated by the recent papers of Conus, Joseph and Khoshnevisan [Ann. Probab. 41 (2013) 2225-2260] and Conus et al. [Probab. Theory Related Fields 156 (2013) 483-533], this work is concerned with the precise spatial asymptotic…

Probability · Mathematics 2016-03-31 Xia Chen

In this paper, we will present a strong (or pathwise) approximation of standard Brownian motion by a class of orthogonal polynomials. The coefficients that are obtained from the expansion of Brownian motion in this polynomial basis are…

Numerical Analysis · Mathematics 2020-05-21 James Foster , Terry Lyons , Harald Oberhauser

This paper analyzes a full discretization of a three-dimensional stochastic Allen-Cahn equation with multiplicative noise. The discretization combines the Euler scheme for temporal approximation and the finite element method for spatial…

Numerical Analysis · Mathematics 2024-11-27 Binjie Li , Qin Zhou

The infinitesimal generator (fractional Laplacian) of a process obtained by subordinating a killed Brownian motion catches the power-law attenuation of wave propagation. This paper studies the numerical schemes for the stochastic wave…

Numerical Analysis · Mathematics 2021-02-23 Xing Liu , Weihua Deng

We prove a formula for the speed of distance stationary random sequences. A particular case is the classical formula for the largest Lyapunov exponent of an i.i.d. product of two by two matrices in terms of a stationary measure on…

Probability · Mathematics 2017-10-04 Matias Carrasco , Pablo Lessa , Elliot Paquette

We propose and analyse a new type of fully discrete surface finite element approximation of a class of linear parabolic stochastic evolution equations with additive noise. Our discretization uses a surface finite element approximation of…

Numerical Analysis · Mathematics 2025-10-10 Øyvind Stormark Auestad , Geir-Arne Fuglstad , Annika Lang

We prove Feynman-Kac formulas for solutions to elliptic and parabolic boundary value and obstacle problems associated with a general Markov diffusion process. Our diffusion model covers several popular stochastic volatility models, such as…

Probability · Mathematics 2015-09-15 Paul M. N. Feehan , Ruoting Gong , Jian Song

We present a numerical method for the approximation of solutions for the class of stochastic differential equations driven by Brownian motions which induce stochastic variation in fixed directions. This class of equations arises naturally…

Numerical Analysis · Mathematics 2010-06-15 David F. Anderson , Jonathan C. Mattingly

In this paper, we derive a parabolic partial differential equation for the expected exit time of non-autonomous time-periodic non-degenerate stochastic differential equations. This establishes a Feynman-Kac duality between expected exit…

Probability · Mathematics 2021-03-12 Chunrong Feng , Huaizhong Zhao , Johnny Zhong

This work develops further a probabilist approach to the asymptotic behavior of growth-fragmentation semigroups via the Feynman-Kac formula, which was introduced in a joint article with A.R. Watson [4]. Here, it is first shown that the…

Probability · Mathematics 2018-04-16 Jean Bertoin

We study mean-field particle approximations of normalized Feynman-Kac semi-groups, usually called Fleming-Viot or Feynman-Kac particle systems. Assuming various large time stability properties of the semi-group uniformly in the initial…

Probability · Mathematics 2024-12-23 Lucas Journel , Mathias Rousset

We consider branching random walk in spatial random branching environment (BRWRE) in dimension one, as well as related differential equations: the Fisher-KPP equation with random branching and its linearized version, the parabolic Anderson…

Probability · Mathematics 2019-04-04 Jiří Černý , Alexander Drewitz

The paper is devoted to the construction of a probabilistic particle algorithm. This is related to nonlin-ear forward Feynman-Kac type equation, which represents the solution of a nonconservative semilinear parabolic Partial Differential…

Probability · Mathematics 2017-09-15 Anthony Le Cavil , Nadia Oudjane , Francesco Russo

An efficient method is presented as a means of an approximate, analytic time-dependent solution of the Fokker-Planck equation (FPE) for the Langevin model subjected to additive and multiplicative noise. We have assumed that the dynamical…

Statistical Mechanics · Physics 2008-10-19 Hideo Hasegawa