伪相位差引导振荡器之间的额外连接以实现同步

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-10-19 DOI:10.1016/j.chaos.2024.115617
Daekyung Lee , Jong-Min Park , Heetae Kim
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引用次数: 0

摘要

在复杂系统中,同步对从生物到技术的各种系统(网络)的协调运行起着至关重要的作用。在动态网络中,节点之间的链接可以在网络中新建立,实现新的互动。因此,了解如何增强系统的同步状态非常重要,尤其是在添加新连接时。本研究采用同步对齐函数(SAF)和调整李亚普诺夫函数(ALF)评估新连接的影响,研究通过优化连接添加来增强同步性的方法。通过应用 ALF 方法比较潜在的链接添加,我们确定了两个有助于提高链接添加效果的关键因素:线性化动力学中的稳态阶段(我们将其命名为伪稳态阶段)和网络的结构属性。通过将这些方法应用于不同的网络拓扑结构,包括巴拉巴西-阿尔伯特模型、厄尔多斯-雷尼模型和卡莱树模型,我们发现了相位差在促进同步中的主导作用。这一探索提供了对网络同步动态的新见解,突出了特定因素对增强网络一致性的关键影响。我们的发现还为进一步研究有针对性的网络优化策略奠定了基础。
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Pseudo-phase difference guides additional connection between oscillators for synchrony
In complex systems, synchronization plays a pivotal role underlying the coherent operation of various systems (networks) ranging from biology to technology. In a dynamic network, a link between nodes can be newly created implementing a new interaction in the network. Therefore, it is of great importance to understand how to enhance the synchronized state of a system especially when adding a new connection. This study investigates ways to enhance synchronization through optimal link addition, employing the Synchrony Alignment Function (SAF) and Adjusted Lyapunov Function (ALF) that assess the effects of new connections. By applying the ALF method to compare potential link additions, we identify two key factors that contribute to the effectiveness of link addition: the steady-state phase in the linearized dynamics, which we named the pseudo-steady-state phase, and the structural attributes of the network. By applying these methods across diverse network topologies, including Barabási–Albert, Erdős–Rényi, and Cayley tree models, we uncover the dominant role of the phase difference in promoting synchronization. This exploration offers new insights into the dynamics of network synchronization, highlighting the critical impact of specific factors on the efficacy of enhancing network coherence. Our findings also lay a foundation for further research into targeted strategies for network optimization.
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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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