MACSI, Department of Mathematics & Statistics, University of Limerick, Ireland.
Phys Rev Lett. 2011 Aug 5;107(6):068701. doi: 10.1103/PhysRevLett.107.068701. Epub 2011 Aug 4.
Binary-state dynamics (such as the susceptible-infected-susceptible (SIS) model of disease spread, or Glauber spin dynamics) on random networks are accurately approximated using master equations. Standard mean-field and pairwise theories are shown to result from seeking approximate solutions of the master equations. Applications to the calculation of SIS epidemic thresholds and critical points of nonequilibrium spin models are also demonstrated.
在随机网络上，二进制状态动力学（如疾病传播的易感染-感染-易感染（SIS）模型或格拉伯尔自旋动力学）可以通过主方程进行精确逼近。标准的平均场和对关联理论是通过寻求主方程的近似解得到的。还展示了这些理论在计算 SIS 流行病阈值和非平衡自旋模型临界点方面的应用。
