Starnini Michele, Gleeson James P, Boguñá Marián
Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain.
Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, 08028 Barcelona, Spain.
Phys Rev Lett. 2017 Mar 24;118(12):128301. doi: 10.1103/PhysRevLett.118.128301.
A general formalism is introduced to allow the steady state of non-Markovian processes on networks to be reduced to equivalent Markovian processes on the same substrates. The example of an epidemic spreading process is considered in detail, where all the non-Markovian aspects are shown to be captured within a single parameter, the effective infection rate. Remarkably, this result is independent of the topology of the underlying network, as demonstrated by numerical simulations on two-dimensional lattices and various types of random networks. Furthermore, an analytic approximation for the effective infection rate is introduced, which enables the calculation of the critical point and of the critical exponents for the non-Markovian dynamics.
引入了一种通用形式体系,以使网络上非马尔可夫过程的稳态简化为同一基质上的等效马尔可夫过程。详细考虑了疫情传播过程的示例,其中所有非马尔可夫方面都被证明可包含在单个参数即有效感染率中。值得注意的是,这一结果与基础网络的拓扑结构无关,二维晶格和各种类型随机网络上的数值模拟证明了这一点。此外,引入了有效感染率的解析近似,这使得能够计算非马尔可夫动力学的临界点和临界指数。