亚临界无标度随机图上的选民模型

Pub Date : 2022-07-23 DOI:10.1002/rsa.21107
J. Fernley, Marcel Ortgiese
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引用次数: 2

摘要

选民模型是一个经典的相互作用粒子系统,它模拟了如何在网络中形成共识。我们分析了当底层图是一个亚临界无标度随机图时,选民模型的共识时间。此外,我们将模型推广到包含一个“温度”参数,以控制图如何影响意见变化的速度。温度和随机图结构之间的相互作用导致了一个非常丰富的相图,在不同的相中,底层几何结构的不同部分支配着达成一致的时间。最后,我们还考虑了一个话语选民模型,其中选民与他们的邻居讨论他们的意见。我们的证明依赖于众所周知的对偶性来合并随机漫步和对随机图结构的详细理解。
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Voter models on subcritical scale‐free random graphs
The voter model is a classical interacting particle system modelling how consensus is formed across a network. We analyze the time to consensus for the voter model when the underlying graph is a subcritical scale‐free random graph. Moreover, we generalize the model to include a “temperature” parameter controlling how the graph influences the speed of opinion change. The interplay between the temperature and the structure of the random graph leads to a very rich phase diagram, where in the different phases different parts of the underlying geometry dominate the time to consensus. Finally, we also consider a discursive voter model, where voters discuss their opinions with their neighbors. Our proofs rely on the well‐known duality to coalescing random walks and a detailed understanding of the structure of the random graphs.
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