标题： 解耦高阶网络中异质性和超边重叠在爆炸性传播中的作用 显示英文标题

标题： Disentangling the role of heterogeneity and hyperedge overlap in explosive contagion on higher-order networks

摘要： 我们引入基于组的分 compartment 建模（GBCM），这是一种用于高阶网络中不可逆传播的平均场框架，能够捕捉结构异质性和组大小之间的相关性。 通过数值模拟验证，GBCM 分析性地解耦了每个交互阶对全局流行病动力学的作用，揭示了异质性和阶间相关性如何共同塑造爆发的开始和爆炸性动力学的出现。 显示英文摘要

摘要： We introduce group-based compartmental modeling (GBCM), a mean-field framework for irreversible contagion in higher-order networks that captures structural heterogeneity and correlations across group sizes. Validated through numerical simulations, GBCM analytically disentangles the role of each interaction order to the global epidemic dynamics, revealing how heterogeneity and inter-order correlations jointly shape the onset of outbreaks and the emergence of explosive dynamics.