Newton conjugate gradient method for discrete nonlinear Schrödinger equations

IF 5.6 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2025-03-20 DOI:10.1016/j.chaos.2025.116302
Rujiang Li, Xiangyu Kong, Wencai Wang, Yongtao Jia, Ying Liu
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Abstract

Discrete nonlinear Schrödinger equations (DNLSEs) are fundamental in describing wave dynamics in nonlinear lattices across various systems, including optics and cold atomic physics. With the advent of topological phases of matter, the DNLSEs that characterize nonlinear topological states and topological solitons in nonlinear topological systems have become increasingly complex. Newton’s method, which is a traditional approach to solve the DNLSEs, faces significant challenges in solving these intricate nonlinear problems. Here, we propose the Newton conjugate gradient (NCG) method as an efficient alternative for solving the DNLSEs. By combining Newton iterations with conjugate gradient iterations, the NCG method achieves a comparable number of iterations to Newton’s method but is significantly faster overall and better suited at finding complex solutions. Using bulk solitons in a nonlinear photonic Chern insulator as an example, we demonstrate that the NCG method is particularly well-suited for solving DNLSEs that describe nonlinear topological systems. The NCG method serves as a powerful tool for investigating nonlinear topological states and topological solitons in even more complex nonlinear topological systems.
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离散非线性Schrödinger方程的牛顿共轭梯度法
离散非线性Schrödinger方程(dnlse)是描述包括光学和冷原子物理在内的各种系统的非线性晶格中的波动动力学的基础。随着物质拓扑相的出现,表征非线性拓扑状态和非线性拓扑系统中拓扑孤子的dnlse变得越来越复杂。牛顿法是求解深度神经网络问题的传统方法,但在求解这些复杂的非线性问题时面临着巨大的挑战。在这里,我们提出牛顿共轭梯度(NCG)方法作为求解dnlse的有效替代方法。通过结合牛顿迭代和共轭梯度迭代,NCG方法实现了与牛顿方法相当的迭代次数,但总体上要快得多,更适合于寻找复杂的解。以非线性光子陈氏绝缘子中的体孤子为例,我们证明了NCG方法特别适合于求解描述非线性拓扑系统的dnlse。NCG方法是研究更复杂的非线性拓扑系统中的非线性拓扑状态和拓扑孤子的有力工具。
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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