自推进粒子上的流行病过程：连续介质与基于智能体的建模
Epidemic processes on self-propelled particles: continuum and agent-based modelling
AI总结：
本文研究自推进粒子上的 SIS 流行病传播，结合连续介质理论与基于智能体模拟，揭示扩散运动使一至三维中的流行病转变均呈平均场类型。
摘要：
大多数传播过程都需要智能体之间在空间上接近。因此，移动智能体群体中传播动力学的稳态取决于流行病过程所涉及的时间与长度尺度，以及它们在空间中的运动之间的相互作用。我们在一个简单模型中分析了这种相互作用所产生的稳态性质；该模型描述自推进粒子（执行 Run-and-Tumble 运动）上的流行病传播（建模为 Susceptible-Infected-Susceptible 过程，即易感—感染—易感过程）。我们将注意力集中在扩散性的长时间区，发现智能体的运动定性地改变了以宏观比例感染智能体出现为特征的流行病转变的性质。事实上，对于在一维、二维和三维中扩散的智能体，该转变变为平均场类型；而在没有运动的情况下，流行病暴发取决于由智能体固定位置所决定的底层静态网络的维度。通过对系统进行连续介质描述所获得的洞见，由基于智能体模型的数值模拟加以验证。我们的工作旨在连接软活性物质物理学与理论流行病学，并可能引起这两个领域研究人员的兴趣。
英文摘要：
Most spreading processes require spatial proximity between agents. The stationary state of spreading dynamics in a population of mobile agents thus depends on the interplay between the time and length scales involved in the epidemic process and their motion in space. We analyze the steady properties resulting from such interplay in a simple model describing epidemic spreading (modeled as a Susceptible-Infected-Susceptible process) on self-propelled particles (performing Run-and-Tumble motion). Focusing our attention on the diffusive long-time regime, we find that the agents' motion changes qualitatively the nature of the epidemic transition characterized by the emergence of a macroscopic fraction of infected agents. Indeed, the transition becomes of the mean-field type for agents diffusing in one, two and three dimensions, while, in the absence of motion, the epidemic outbreak depends on the dimension of the underlying static network determined by the agents' fixed locations. The insights obtained from a continuum description of the system are validated by numerical simulations of an agent-based model. Our work aims at bridging soft active matter physics and theoretical epidemiology, and may be of interest for researchers in both communities.
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