具有衰减、扩散和对流的连续时间网络模型
Models of Continuous-Time Networks with Tie Decay, Diffusion, and Convection
摘要：
离散时间的时间网络的研究已经产生了大量的见解，时间依赖的网络系统在各种各样的应用。然而，对于许多复杂系统，建立网络的连续时间模型并将其与相关的离散模型进行比较是有用的。在本文中，我们研究了几个连续时间网络模型，并检查他们的离散近似数值和解析。为了考虑连续时间网络，我们将图中的每条边与一个依赖于时间的联系强度相关联，该联系强度可以取连续的非负值，并在最近的交互之后随时间衰减。我们调查如何平均领带强度随时间的演变在几个模型中，我们探索-数值和分析-标准出现一个巨大的连接组件在这些模型中。我们还简要地研究了我们的连续时间网络的相互作用模式对传染病的一个可治愈的传染病模型中的传染动力学的影响。
英文摘要：
The study of temporal networks in discrete time has yielded numerous insights into time-dependent networked systems in a wide variety of applications. For many complex systems, however, it is useful to develop continuous-time models of networks and to compare them to associated discrete models. In this paper, we study several continuous-time network models and examine discrete approximations of them both numerically and analytically. To consider continuous-time networks, we associate each edge in a graph with a time-dependent tie strength that can take continuous non-negative values and decays in time after the most recent interaction. We investigate how the mean tie strength evolves with time in several models, and we explore -- both numerically and analytically -- criteria for the emergence of a giant connected component in some of these models. We also briefly examine the effects of interaction patterns of our continuous-time networks on contagion dynamics in a susceptible-infected-recovered model of an infectious disease.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
