Abstract
Throughout the last two decades, complex systems have been modeled as complex networks by capturing pairwise interactions. However, as research has progressed, it has been shown that many systems would lose much useful information after modeling the pairwise interaction relationship. According to study results, higher-order interactions are becoming more generally accepted as an essential element of complex systems. Hypergraphs may be used to explore the relationships between higher-order structures and functions in complex systems and capture higher-order interactions. After the initial failure of a hypergraph network, cascading failures may occur, just as they can with a simple network. Previous research has concentrated on random initial failures, and how hypergraph networks adapt to targeted attacks remains unanswered. In this research, we build a mathematical framework to explore the robustness of hypergraph networks against targeted attacks based on the magnitude of the hyperedge’s cardinality. We discovered that when the probability of large cardinality hyperedges being deleted grows, the network becomes more fragile.
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