{"title":"Correlation between transition probability and network structure in epidemic model","authors":"Chao-Ran Cai , Dong-Qian Cai","doi":"10.1016/j.chaos.2025.116142","DOIUrl":null,"url":null,"abstract":"<div><div>In discrete-time dynamics, it is frequently assumed that the transition probabilities (e.g., the recovery probability) are independent of the network structure. However, there is a lack of empirical evidence to support this claim in large time intervals. This paper presents the nonlinear relations between the rates (in continuous-time dynamics) and probabilities of the susceptible–infected–susceptible model on annealed and static networks. It is shown that the transition probabilities are affected not only by the rates and the time interval, but also by the network structure. The correctness of the nonlinear relations on networks is verified based on theoretical calculation and Monte Carlo simulation.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"194 ","pages":"Article 116142"},"PeriodicalIF":5.3000,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos Solitons & Fractals","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0960077925001559","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
In discrete-time dynamics, it is frequently assumed that the transition probabilities (e.g., the recovery probability) are independent of the network structure. However, there is a lack of empirical evidence to support this claim in large time intervals. This paper presents the nonlinear relations between the rates (in continuous-time dynamics) and probabilities of the susceptible–infected–susceptible model on annealed and static networks. It is shown that the transition probabilities are affected not only by the rates and the time interval, but also by the network structure. The correctness of the nonlinear relations on networks is verified based on theoretical calculation and Monte Carlo simulation.
期刊介绍:
Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.