论文标题
简单复合物上的随机流行模型
Stochastic epidemic model on a simplicial complex
论文作者
论文摘要
具有成对连接的复杂网络已被广泛用于系统内交互的建模。尽管这些类型的模型能够在各种情况下捕获丰富的结构和不同的阶段，但在某些情况下，它们缺乏明确的高阶相互作用可能会导致。在这项工作中，定义了一个在简单络合物上的随机流行模型，从而推广了马尔可夫的SIR流行过程在网络上。通过直接模拟和平均场分析，已经表明，通过通过单纯形引入三阶交互，SIR模型可以在其动力学和固定状态相对于模型的成对版本显示重要的差异。
Complex networks with pairwise connections have been vastly used for the modeling of interactions within systems. Although these type of models are capable to capture rich structures and different phases within a great variety of situations, their lack of explicit higher order interactions might result, in some contexts, limited. In this work a stochastic epidemic model on a simplicial complex is defined, generalizing the known Markovian SIR epidemic process on networks. By direct simulations and mean field analysis is shown that already by the introduction of third order interactions through a simplex, the SIR model can display important differences in its dynamics and stationary states with respect to the pairwise version of the model.
