带波算子的非线性薛定谔方程的基于能量的非连续伽勒金方法

IF 2.8 2区 数学 Q1 MATHEMATICS, APPLIED
Kui Ren, Lu Zhang, Yin Zhou
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引用次数: 0

摘要

SIAM 数值分析期刊》,第 62 卷,第 6 期,第 2459-2483 页,2024 年 12 月。 摘要。本文针对带波算子的非线性薛定谔方程开发了一种基于能量的非连续伽勒金(EDG)方法。研究的重点是该方法的能量守恒或能量消耗行为,以及我们设计的一些与网格无关的简单数值通量。我们建立了能量规范中的误差估计,这需要仔细选择涉及位移变量时间导数的辅助方程的弱表述。收敛分析的一个关键部分是利用确定位移变量均值的方程,建立位移变量近似误差时间导数的[数学]误差边界。通过使用一种特殊的弱公式,我们证明即使在处理原始问题中的非线性特性时,也可以为未知数的时间演化建立一个线性系统。我们进行了数值实验来证明该方案在 [math] 规范下的最佳收敛性。这些实验涉及数值通量的特定选择和近似空间的特定选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Energy-Based Discontinuous Galerkin Method for the Nonlinear Schrödinger Equation with Wave Operator
SIAM Journal on Numerical Analysis, Volume 62, Issue 6, Page 2459-2483, December 2024.
Abstract. This work develops an energy-based discontinuous Galerkin (EDG) method for the nonlinear Schrödinger equation with the wave operator. The focus of the study is on the energy-conserving or energy-dissipating behavior of the method with some simple mesh-independent numerical fluxes we designed. We establish error estimates in the energy norm that require careful selection of a weak formulation for the auxiliary equation involving the time derivative of the displacement variable. A critical part of the convergence analysis is to establish the [math] error bounds for the time derivative of the approximation error in the displacement variable by using the equation that determines its mean value. Using a special weak formulation, we show that one can create a linear system for the time evolution of the unknowns even when dealing with nonlinear properties in the original problem. Numerical experiments were performed to demonstrate the optimal convergence of the scheme in the [math] norm. These experiments involved specific choices of numerical fluxes combined with specific choices of approximation spaces.
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来源期刊
CiteScore
4.80
自引率
6.90%
发文量
110
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Numerical Analysis (SINUM) contains research articles on the development and analysis of numerical methods. Topics include the rigorous study of convergence of algorithms, their accuracy, their stability, and their computational complexity. Also included are results in mathematical analysis that contribute to algorithm analysis, and computational results that demonstrate algorithm behavior and applicability.
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