The symbolic partition with generalized Koopman analysis

IF 5.6 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Haipeng Li , Pengfei Guo , Yueheng Lan
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引用次数: 0

Abstract

Symbolic dynamics serves the study of chaotic systems as a crucial tool, prompting extensive research on a proper partition of the phase space. However, the majority of prevailing methods are empirical and based either on construction of manifolds or on specific orbits. A spectral consideration based on evolution operators, such as the Koopman operator, remains underexplored. Here, we propose an alternative method for the symbolic partition based on the Koopman operator, the left eigenfunctions of which turn out closely related to the stretching and folding mechanism of chaos generation and thus provide novel means to identify a partition boundary. To avoid wild oscillations in eigenfunctions, a generalized Koopman analysis is developed to enable a local spectral computation for refining a partition. This new framework is successfully demonstrated in several typical dynamical systems including 1-D chaotic maps, the well-known Hénon maps with different parameters and a 3-D hyperchaotic map as well as a periodically driven Duffing system, with or without small noisy perturbation. Thus, the proposed technique is highly flexible and good for chaotic systems in multi-dimensions with diverse complexities.
广义Koopman分析的符号划分
符号动力学作为混沌系统研究的重要工具,促进了对相空间合理划分的广泛研究。然而,大多数流行的方法都是经验性的,要么基于流形的构造,要么基于特定的轨道。基于演化算子(如Koopman算子)的频谱考虑仍未得到充分探索。本文提出了一种基于Koopman算子的符号划分方法,该方法的左特征函数与混沌产生的拉伸和折叠机制密切相关,从而为划分边界的识别提供了一种新的方法。为了避免特征函数中的野振荡,提出了一种广义的库普曼分析方法,使局部谱计算成为可能。该框架已成功地在具有或不具有小噪声扰动的一维混沌映射、不同参数的h非定常混沌映射、三维超混沌映射以及周期驱动Duffing系统中得到验证。因此,该方法具有很高的灵活性,适用于复杂程度不同的多维混沌系统。
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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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