arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1901.09288math.PRcs.NAmath.NA
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随机 Burgers 方程的存在性、唯一性与数值逼近

Existence, uniqueness, and numerical approximations for stochastic Burgers equations

Sara Mazzonetto, Diyora Salimova

AI总结:

本文针对具有非全局单调非线性的随机偏微分方程,提出涵盖温和解存在性、唯一性、正则性与数值逼近的一体化命题,并利用显式时空离散格式证明其收敛性,最终应用于带时空白噪声的随机 Burgers 方程。

摘要:

在本文中,我们提出了一个一体化命题,涵盖了一类具有非全局单调非线性的随机偏微分方程(SPDEs)温和解的存在性、唯一性、正则性及数值逼近。该结果的证明利用了现有的完全显式时空离散逼近格式的性质,特别是其满足适当的先验估计这一事实。作为副产品,我们得到了该逼近格式对所考虑 SPDEs 温和解的几乎必然收敛和强收敛。最后,我们将本文的主要结果应用于带时空白噪声的随机 Burgers 方程。

英文摘要:

In this paper we propose an all-in-one statement which includes existence, uniqueness, regularity, and numerical approximations of mild solutions for a class of stochastic partial differential equations (SPDEs) with non-globally monotone nonlinearities. The proof of this result exploits the properties of an existent fully explicit space-time discrete approximation scheme and, in particular, the fact that it satisfies suitable a priori estimates. As a byproduct we obtain almost sure and strong convergence of the approximation scheme to the mild solutions of the considered SPDEs. We conclude by applying the main result of the paper to the stochastic Burgers equations with space-time white noise.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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