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We perform and extend real-time numerical simulation of a low-dimensional scalar field theory or a quantum mechanical system using stochastic quantization. After a brief review of the quantization method and the complex Langevin dynamics,…

High Energy Physics - Phenomenology · Physics 2015-01-30 Ryoji Anzaki , Kenji Fukushima , Yoshimasa Hidaka , Takashi Oka

The aim of this note is to propose a novel numerical scheme for drift-less one dimensional stochastic differential equations of It\^o's type driven by standard Brownian motion. Our approximation method is equivalent to the well known…

Probability · Mathematics 2024-07-24 Alberto Lanconelli , Berk Tan Perçin

In this work, we explore a time-fractional diffusion equation of order $\alpha \in (0,1)$ with a stochastic diffusivity parameter. We focus on efficient estimation of the expected values (considered as an infinite dimensional integral on…

Numerical Analysis · Mathematics 2024-09-04 Josef Dick , Hecong Gao , William McLean , Kassem Mustapha

In this article, we consider the stochastic wave equation in spatial dimension $d=1$, with linear term $\sigma(u)=u$ multiplying the noise. This equation is driven by a Gaussian noise which is white in time and fractional in space with…

Probability · Mathematics 2023-07-04 Raluca M. Balan , Jingyu Huang , Xiong Wang , Panqiu Xia , Wangjun Yuan

We consider the stochastic Allen--Cahn equation perturbed by smooth additive Gaussian noise in a spatial domain with smooth boundary in dimension $d\le 3$, and study the semidiscretisation in time of the equation by an Euler type split-step…

Numerical Analysis · Mathematics 2018-04-27 Mihály Kovács , Stig Larsson , Fredrik Lindgren

In this paper, we propose and analyze an explicit time-stepping scheme for a spatial discretization of stochastic Cahn--Hilliard equation with additive noise. The fully discrete approximation combines a spectral Galerkin method in space…

Numerical Analysis · Mathematics 2023-08-31 Meng Cai , Ruisheng Qi , Xiaojie Wang

We study a nonlinear stochastic partial differential equation whose solution is the conditional log-Laplace functional of a superprocess in a random environment. We establish its existence and uniqueness by smoothing out the nonlinear term…

Probability · Mathematics 2016-09-07 Jie Xiong

The stochastic time-fractional equation $\partial_t \psi -\Delta\partial_t^{1-\alpha} \psi = f + \dot W$ with space-time white noise $\dot W$ is discretized in time by a backward-Euler convolution quadrature for which the sharp-order error…

Numerical Analysis · Mathematics 2018-08-09 Max Gunzburger , Buyang Li , Jilu Wang

The aim of this contribution is to address the convergence study of a time and space approximation scheme for an Allen-Cahn problem with constraint and perturbed by a multiplicative noise of It\^o type. The problem is set in a bounded…

Numerical Analysis · Mathematics 2025-09-03 Caroline Bauzet , Cédric Sultan , Guy Vallet , Aleksandra Zimmermann

This paper studies the nonlinear one-dimensional stochastic heat equation driven by a Gaussian noise which is white in time and which has the covariance of a fractional Brownian motion with Hurst parameter 1/4\textless{}H\textless{}1/2 in…

Probability · Mathematics 2015-05-20 Yaozhong Hu , Jingyu Huang , Khoa Lê , David Nualart , Samy Tindel

A time-domain numerical code based on the constitutive relations of nonlinear acoustics for simulating ultrasound propagation is presented. To model frequency power law attenuation, such as observed in biological media, multiple relaxation…

In this paper we investigate the numerical solution of stochastic partial differential equations (SPDEs) for a wider class of stochastic equations. We focus on non-diagonal colored noise instead of the usual space-time white noise. By…

Numerical Analysis · Mathematics 2013-11-12 Dirk Blömker , Minoo Kamrani

In this paper, a weak Local Linearization scheme for Stochastic Differential Equations (SDEs) with multiplicative noise is introduced. First, for a time discretization, the solution of the SDE is locally approximated by the solution of the…

Numerical Analysis · Mathematics 2015-06-19 J. C. Jimenez , C. Mora , M. Selva

In this work, we demonstrate the Wong-Zakai approximation results for two and three dimensional stochastic convective Brinkman-Forchheimer (SCBF) equations forced by Hilbert space valued Wiener noise on bounded domains. Even though the…

Probability · Mathematics 2022-02-24 Kush Kinra , Manil T. Mohan

In this paper, we study a class of stochastic partial differential equations (SPDEs) driven by space-time fractional noises. Our method consists in studying first the nonlocal SPDEs and showing then the convergence of the family of these…

Probability · Mathematics 2014-09-17 Ying Hu , Yiming Jiang , Zhongmin Qian

In this paper we consider the numerical approximation of a general second order semi-linear parabolic partial differential equation. Equations of this type arise in many contexts, such as transport in porous media. Using finite element…

Numerical Analysis · Mathematics 2020-11-18 Jean Daniel Mukam , Antoine Tambue

Strong convergence rates for (temporal, spatial, and noise) numerical approximations of semilinear stochastic evolution equations (SEEs) with smooth and regular nonlinearities are well understood in the scientific literature. Weak…

Probability · Mathematics 2021-11-02 Daniel Conus , Arnulf Jentzen , Ryan Kurniawan

Many simulations of stochastic processes require colored noises: I describe here an exact numerical method to simulate power-law noises: the method can be extended to more general colored noises, and is exact for all time steps, even when…

Computational Physics · Physics 2007-05-23 Edoardo Milotti

In this paper we construct space-time full discretizations of stochastic Allen-Cahn equations driven by space-time white noise on 2D torus. The approximations are implemented by tamed exponential Euler discretization in time and spectral…

Probability · Mathematics 2024-06-07 Ting Ma , Lifei Wang , Huanyu Yang

Numerical methods for stochastic partial differential equations typically estimate moments of the solution from sampled paths. Instead, we shall directly target the deterministic equations satisfied by the first and second moments, as well…

Numerical Analysis · Mathematics 2020-11-17 Kristin Kirchner