Split-step quintic uniform algebraic trigonometric tension b-spline collocation method for cubic Ginzburg-Landau equations

IF 2.5 2区 数学 Q1 MATHEMATICS, APPLIED
Jinsong Shi , Kaysar Rahman , Jiawen Deng
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引用次数: 0

Abstract

This paper proposes a novel numerical framework for solving the one- and multi-dimensional cubic Ginzburg-Landau (CGL) equation by integrating the quintic Uniform Algebraic Trigonometric (UAT) tension B-spline collocation method with the Strang splitting technique. The approach decomposes the original equation into two nonlinear subproblems and one or more linear subproblems via a time-splitting strategy, achieving second-order temporal accuracy. The linear subproblems are resolved using the quintic UAT tension B-spline collocation method to ensure fourth-order spatial accuracy, while the nonlinear subproblems are solved analytically, forming an unconditionally stable scheme. The framework is extendable to other nonlinear PDEs, such as the Schrödinger equation, Kuramoto-Tsuzuki equation, and reaction-diffusion systems, enabling efficient simulations of complex systems in physics, engineering, and materials science. Numerical experiments and comparative analysis validate its accuracy, high convergence orders, and computational efficiency, establishing it as a new high-performance tool for solving such nonlinear PDEs.
三次金兹堡-朗道方程的分步五次一致代数三角张力b样条配点法
将五次统一代数三角(UAT)张力b样条配点法与Strang分裂技术相结合,提出了求解一维和多维三次Ginzburg-Landau (CGL)方程的一种新的数值框架。该方法通过时间分裂策略将原方程分解为两个非线性子问题和一个或多个线性子问题,实现了二阶时间精度。采用五次UAT张力b样条配点法求解线性子问题,保证了四阶空间精度;采用解析法求解非线性子问题,形成了无条件稳定格式。该框架可扩展到其他非线性偏微分方程,如Schrödinger方程、Kuramoto-Tsuzuki方程和反应扩散系统,能够有效地模拟物理、工程和材料科学中的复杂系统。数值实验和对比分析验证了该方法的精度、高收敛阶数和计算效率,使其成为求解此类非线性偏微分方程的新型高性能工具。
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来源期刊
Computers & Mathematics with Applications
Computers & Mathematics with Applications 工程技术-计算机:跨学科应用
CiteScore
5.10
自引率
10.30%
发文量
396
审稿时长
9.9 weeks
期刊介绍: Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).
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