稳健性(进化)
级联故障
级联
相互依存的网络
单调函数
计算机科学
复杂网络
复杂系统
相互依存
分布式计算
统计物理学
拓扑(电路)
数学
物理
组合数学
人工智能
工程类
化学
功率(物理)
电力系统
量子力学
化学工程
法学
政治学
数学分析
生物化学
万维网
基因
作者
Lei Chen,Yanpeng Zhu,Fanyuan Meng,Run-Ran Liu
出处
期刊:Chaos
[American Institute of Physics]
日期:2024-04-01
卷期号:34 (4)
被引量:4
摘要
The failures of individual agents can significantly impact the functionality of associated groups in interconnected systems. To reveal these impacts, we develop a threshold model to investigate cascading failures in double-layer hypergraphs with interlayer interdependence. We hypothesize that a hyperedge disintegrates when the proportion of failed nodes within it exceeds a threshold. Due to the interdependence between a node and its replica in the other layer, the disintegrations of these hyperedges could trigger a cascade of events, leading to an iterative collapse across these two layers. We find that double-layer hypergraphs undergo abrupt, discontinuous first-order phase transitions during systemic collapse regardless of the specific threshold value. Additionally, the connectivity measured by average cardinality and hyperdegree plays a crucial role in shaping system robustness. A higher average hyperdegree always strengthens system robustness. However, the relationship between system robustness and average cardinality exhibits non-monotonic behaviors. Specifically, both excessively small and large average cardinalities undermine system robustness. Furthermore, a higher threshold value can boost the system’s robustness. In summary, our study provides valuable insights into cascading failure dynamics in double-layer hypergraphs and has practical implications for enhancing the robustness of complex interdependent systems across domains.
科研通智能强力驱动
Strongly Powered by AbleSci AI