University of Limerick Institutional Repository

Browsing MACSI - Mathematics Application Consortium for Science & Industry by Title

DSpace Repository

Browsing MACSI - Mathematics Application Consortium for Science & Industry by Title

Sort by: Order: Results:

  • Gleeson, James P. (American Physical Society, 2013)
    A wide class of binary-state dynamics on networks-including, for example, the voter model, the Bass diffusion model, and threshold models-can be described in terms of transition rates (spin-flip probabilities) that depend ...
  • Gleeson, James P. (American Physical Society, 2009)
    Analytical results are derived for the bond percolation threshold and the size of the giant connected component in a class of random networks with nonzero clustering. The network's degree distribution and clustering spectrum ...
  • Hackett, Adam W.; Melnik, Sergey; Gleeson, James P. (American Physical Society, 2011)
    We present an analytical approach to determining the expected cascade size in a broad range of dynamical models on the class of random networks with arbitrary degree distribution and nonzero clustering introduced previously ...
  • Hackett, Adam W.; Gleeson, James P. (American Physical Society, 2013)
    We present an analytical approach to determining the expected cascade size in a broad range of dynamical models on the class of highly clustered random graphs introduced by Gleeson [J. P. Gleeson, Phys. Rev. E 80, 036107 ...
  • Gleeson, James P.; Ward, Jonathan A; O'Sullivan, Kevin P; Lee, William T. (American Physical Society, 2014)
    Heavy-tailed distributions of meme popularity occur naturally in a model of meme diffusion on social networks. Competition between multiple memes for the limited resource of user attention is identified as the mechanism ...
  • 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 ...
  • Melnik, Sergey; Porter, Mason A; Mucha, Peter J; Gleeson, James P. (American Institute of Physics, 2014)
    We develop a new ensemble of modular random graphs in which degree-degree correlations can be different in each module, and the inter-module connections are defined by the joint degree-degree distribution of nodes for each ...
  • Gleeson, James P. (American Physical Society, 2011)
    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 ...
  • Melnik, Sergey; Ward, Jonathan A; Gleeson, James P.; Porter, Mason A (American Institute of Physics, 2013)
    The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide ...
  • Cellai, Davide; López, Eduardo; Zhou, Jie; Gleeson, James P.; Bianconi, Ginestra (American Physical Society, 2013)
    From transportation networks to complex infrastructures, and to social and communication networks, a large variety of systems can be described in terms of multiplexes formed by a set of nodes interacting through different ...
  • Gleeson, James P. (2009)
    The motion of overdamped particles in a one-dimensional spatially-periodic potential is considered. The potential is also randomly-fluctuating in time, due to multiplicative colored noise terms, and has a deterministic ...
  • Melnik, Sergey; Hackett, Adam W.; Porter, Mason A; Mucha, Peter J; Gleeson, James P. (American Physical Society, 2011)
    We demonstrate that a tree-based theory for various dynamical processes operating on static, undirected networks yields extremely accurate results for several networks with high levels of clustering. We find that such a ...

Search DSpace


Browse

My Account

Statistics