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.
Onaga, Tomokatsu; Gleeson, James P.; Masuda, Naoki(American Physical Society, 2017)
Social contact networks underlying epidemic processes in humans and animals are highly dynamic. The spreading of infections on such temporal networks can differ dramatically from spreading on static networks. We theoretically ...
Gleeson, James P.; Durrett, Rick(Nature Publishing Group, 2017)
An avalanche or cascade occurs when one event causes one or more subsequent events,
which in turn may cause further events in a chain reaction. Avalanching dynamics are studied in many disciplines, with a recent focus on ...
O'Sullivan, David J.P.; Garduño-Hernández, Guillermo; Gleeson, James P.; Beguerisse-Díaz, Mariano(The Royal Society, 2017)
We examine the relationship between social structure and sentiment through the analysis of a large collection of tweets about the Irish Marriage Referendum of 2015. We obtain the
sentiment of every tweet with the hashtags ...
Khoury, Maria; Gleeson, James P.; Sancho, J. M.; Lacasta, A. M.; Lindenberg, Katja(American Physical Society, 2009)
Transport and diffusion of particles on modulated surfaces is a nonequilibrium problem which is receiving a great deal of attention due to its technological applications, but analytical calculations are scarce. In earlier ...
Gleeson, James P.(American Physical Society, 2002)
Recently Vlad et al. [Phys. Rev. E. 63, 066304 (2001)] applied the method of decorrelation trajectories to
the transport of tracers in stochastic velocity fields with constant drift, and found that the average ...
