发表机构
Western Norway University of Applied Sciences; Université de Moncton; Université de Douala(挪威西部应用科学大学; 蒙克顿大学; 杜阿拉大学)
机构由 AI 辅助整理,请以论文原文为准。AI 中文总结
本文针对 Hurst 参数 H<1/2 的分数布朗运动驱动的半线性随机偏微分方程,建立了温和解的适定性与正则性,并分析了随机指数积分器的强收敛性,推导出依赖 H 的时间收敛速率,数值实验验证了理论结果。
AI 中文摘要
分数布朗运动为建模具有反持久时间相关性的随机现象提供了一个有用的框架,这类现象出现在异常扩散、水文学、金融和地球物理过程等应用中。本文研究一类由加性分数布朗运动驱动的半线性随机偏微分方程,其 Hurst 参数 $H\in(0,\frac12)$。我们建立了温和解的适定性和时空正则性,并研究了时间离散化的随机指数积分器的强收敛性。该分析允许线性算子为非自伴的,并将解析半群估计与分数布朗运动相关的典型希尔伯特空间结构以及 Malliavin 微积分相结合,以处理噪声的低时间正则性。我们推导出一个依赖于 $H$ 的强时间收敛速率,在最大空间正则性下达到 $H+\frac12$。针对具有非均匀达西流的随机对流-扩散-反应问题的数值实验证实了理论时间收敛速率。我们还使用蒙特卡洛方法估计了不同 Hurst 参数 $H\in(0,\frac12)$ 下解的均值。
英文摘要
Fractional Brownian motion provides a useful framework for modeling random phenomena with anti-persistent temporal correlations that arise in applications such as anomalous diffusion, hydrology, finance, and geophysical processes. In this paper, we study a class of semilinear stochastic partial differential equations driven by additive fractional Brownian motion with Hurst parameter $H\in(0,\frac12)$. We establish the well-posedness and space-time regularity of the mild solution and investigate the strong convergence of a stochastic exponential integrator for the temporal discretization. The analysis allows the linear operator to be non-self-adjoint and combines analytic semigroup estimates with the canonical Hilbert-space structure associated with fractional Brownian motion and Malliavin calculus to handle the low temporal regularity of the noise. We derive an $H$-dependent strong temporal convergence rate, which reaches $H+\frac12$ under maximal spatial regularity. Numerical experiments for a stochastic advection--diffusion--reaction problem with heterogeneous Darcy flow confirm the theoretical temporal convergence rates. We also estimate the mean of the solution with different Hurst parameters $H\in(0,\frac12)$ using the Monte Carlo method.