论文标题

复杂网络中依赖持续时间扩散动力学的分层粗粒方法

Hierarchical Coarse-grained Approach to the Duration-dependent Spreading Dynamics in Complex Networks

论文作者

Chen, Jin-Fu, Du, Yi-Mu, Dong, Hui, Sun, Chang-Pu

论文摘要

已经提出了各种粗粒模型来研究网络中的扩散动力学。需要一个微观理论来将扩散动态与个体行为联系起来。在这封信中,我们通过将微观动力学分解为两个基本过程,即衰老过程和接触过程来统一复杂网络上不同传播动态的描述。得出了微观动力学方程,以描述网络上各个节点的动力学。持续时间粗粒(DCG)方法的层次结构可用于研究持续时间依赖性过程,其中过渡速率取决于状态上个体节点的持续时间。这种形式主义应用于流行病扩散,可用于再现不同的流行模型,例如,易感感染的被恢复和易感感染感染敏感的模型,并与相应的宏观扩散参数与显微镜过渡率相关联。 DCG方法使我们能够以任意持续时间依赖的恢复和感染率获得一般SIS模型的稳态。当前的层次形式主义也可用于描述信息和公众观点的传播,或在网络中建模可靠性理论。

Various coarse-grained models have been proposed to study the spreading dynamics in the network. A microscopic theory is needed to connect the spreading dynamics with the individual behaviors. In this letter, we unify the description of different spreading dynamics on complex networks by decomposing the microscopic dynamics into two basic processes, the aging process and the contact process. A microscopic dynamical equation is derived to describe the dynamics of individual nodes on the network. The hierarchy of a duration coarse-grained (DCG) approach is obtained to study duration-dependent processes, where the transition rates depend on the duration of an individual node on a state. Applied to the epidemic spreading, such formalism is feasible to reproduce different epidemic models, e.g., the susceptible-infected-recovered and the susceptible-infected-susceptible models, and to associate with the corresponding macroscopic spreading parameters with the microscopic transition rate. The DCG approach enables us to obtain the steady state of the general SIS model with arbitrary duration-dependent recovery and infection rates. The current hierarchical formalism can also be used to describe the spreading of information and public opinions, or to model a reliability theory in networks.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源