高阶网络的可控性

IF 2.8 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2024-09-17 DOI:10.1016/j.physa.2024.130108
Weiyuan Ma, Xionggai Bao, Chenjun Ma
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引用次数: 0

摘要

高阶网络可以全面描述群体间的相互作用,因此成为网络科学的一个新的探索领域。本文旨在深入研究高阶网络的可控性。高阶网络的拓扑特征是高阶交互,节点是高维动态系统。本文广泛探讨了高阶交互动态、节点动态、内部交互和外部控制输入对网络可控性的集体影响。通过应用矩阵理论和控制理论,提出了确定超图网络和简单复杂网络可控性的一些必要和/或充分条件。通过模拟实例,可以明显看出高阶网络系统的可控性比传统网络系统复杂得多,而高阶拓扑结构有助于提高可控性。值得注意的是,即使相应的传统网络无法控制外部输入,集成网络也能实现可控性。
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Controllability of higher-order networks

Higher-order networks can comprehensively describe interactions among groups, thus emerging as a novel area of exploration in network science. This paper aims to delve into the controllability of higher-order networks, where the network topology is characterized by higher-order interactions and the nodes are higher-dimensional dynamical systems. The collective effects on the network controllability from the dynamics of higher-order interactions, node dynamics, inner interactions, and external control inputs are extensively explored. By applying matrix theory and control theory, some necessary and/or sufficient conditions are developed to determine the controllability of hypergraph networks and simplicial complex networks. Through simulated examples, it becomes evident that the controllability of higher-order networked system is far more complicated than that of traditional networked systems and the higher-order topological structures facilitate the controllability. Remarkably, the integrated network can achieve controllability even when the corresponding traditional network is uncontrollable by external inputs.

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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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