Stochastic and variational approach to finite difference approximation of Hamilton-Jacobi equations

Stochastic and variational approach to finite difference approximation of Hamilton-Jacobi equations
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Hamilton-Jacobi 方程有限差分近似的随机和变分方法

DOI:
10.1090/mcom/3437
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发表时间:
2020
影响因子:
2
通讯作者:
Kohei Soga
Kohei Soga
中科院分区:
数学2区
文献类型:
--
作者:
Hidesato Kuroki;Kohei Soga;喜多 奈々緒;足立真訓;Sasaki Takiko;Masanori Adachi;Kohei Soga

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在此之前,作者提出了一种随机变分方法来求解双曲标量守恒律的Lax-Friedrichs有限差分格式以及相应的一维周期环境下具有凸哈密顿量和超线性哈密顿量的Hamilton-Jacobi方程,给出了格式稳定性和收敛的新结果[Soga,Math.公司。84(2015),629-651]。在本文中,我们将这些结果推广到高维情形。我们的框架和一个确定性的方案提供了在任意时间间隔内,同时对Hamilton-Jacobi方程、它们的空间导数和后向特征曲线的粘性解的近似。证明的基础是随机游动的随机变分,验证CFL型稳定性条件的变分问题极小值的先验有界性,以及双曲标度极限下随机游动的大数定律。用概率论的方法得到了逼近的收敛速度和收敛速度。这个想法让人想起[Fleming,J.Different]中介绍的随机和变分方法的消失粘性方法。等式5(1969)515-530]。参考文献
Previously, the author presented a stochastic and variational approach to the Lax-Friedrichs finite difference scheme applied to hyperbolic scalar conservation laws and the corresponding Hamilton-Jacobi equations with convex and superlinear Hamiltonians in the one-dimensional periodic setting, showing new results on the stability and convergence of the scheme [Soga, Math. Comp. 84 (2015), 629–651]. In the current paper, we extend these results to the higher dimensional setting. Our framework with a deterministic scheme provides approximation of viscosity solutions of Hamilton-Jacobi equations, their spatial derivatives and the backward characteristic curves at the same time, within an arbitrary time interval. The proof is based on stochastic calculus of variations with random walks, a priori boundedness of minimizers of the variational problems that verifies a CFL type stability condition, and the law of large numbers for random walks under the hyperbolic scaling limit. Convergence of approximation and the rate of convergence are obtained in terms of probability theory. The idea is reminiscent of the stochastic and variational approach to the vanishing viscosity method introduced in [Fleming, J. Differ. Eqs 5 (1969) 515–530]. References
DOI: 10.1016/j.na.2014.02.012
发表时间: 2014
影响因子: 1.4
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发表时间: 2016
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DOI: 10.1088/0951-7715/25/9/2401
发表时间: 2012
期刊: Nonlinearity
影响因子: 1.7
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