空间分数克莱因-戈登-扎哈罗夫方程的高阶能量守恒方法

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Science Pub Date : 2024-07-17 DOI:10.1016/j.jocs.2024.102391
Siqi Yang , Jianqiang Sun , Jie Chen
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引用次数: 0

摘要

通过引入新的辅助变量,将空间分数克莱因-戈登-扎哈罗夫方程转化为多折射结构系统。通过傅里叶伪谱法将满足多交映守恒、局部能量和动量守恒的多交映系统离散化为半离散多交映系统。将二阶多交错平均矢量场方法应用于半离散系统。得到了空间分数克莱因-戈登-扎哈罗夫方程的全离散能量保存方案。基于组成方法,还得到了 Riesz 空间分数 Klein-Gordon-Zakharov 方程的四阶能量守恒方案。数值实验证实,这些新方案具有长期计算能力,并能很好地保持方程的离散能量守恒特性。
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High order energy-preserving method for the space fractional Klein–Gordon-Zakharov equations

The space fractional Klein–Gordon-Zakharov equations are transformed into the multi-symplectic structure system by introducing new auxiliary variables. The multi-symplectic system, which satisfies the multi-symplectic conservation, local energy and momentum conservation, is discretizated into the semi-discrete multi-symplectic system by the Fourier pseudo-spectral method. The second order multi-symplectic average vector field method is applied to the semi-discrete system. The fully discrete energy preserving scheme of the space fractional Klein–Gordon-Zakharov equation is obtained. Based on the composition method, a fourth order energy preserving scheme of the Riesz space fractional Klein–Gordon-Zakharov equations is also obtained. Numerical experiments confirm that these new schemes can have computing ability for a long time and can well preserve the discrete energy conservation property of the equations.

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来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
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