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Browsing Mathematics & Statistics by Author "Gleeson, James P."

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Browsing Mathematics & Statistics by Author "Gleeson, James P."

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  • Gleeson, James P.; Melnik, Sergey; Ward, Jonathan A; Porter, Mason A; Murcha, Peter J (American Physical Society, 2012)
    Mean-field analysis is an important tool for understanding dynamics on complex networks. However, surprisingly little attention has been paid to the question of whether mean-field predictions are accurate, and this is ...
  • Fennell, Peter G.; Gleeson, James P.; Cellai, Davide (American Physical Society, 2014)
    Facilitated spin models were introduced some decades ago to mimic systems characterized by a glass transition. Recent developments have shown that a class of facilitated spin models is also able to reproduce characteristic ...
  • Gleeson, James P.; Melnik, Sergey (American Physical Society, 2009)
    An analytical approach to calculating bond percolation thresholds, sizes of k-cores, and sizes of giant connected components on structured random networks with nonzero clustering is presented. The networks are generated ...
  • 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.; Cellai, Davide; Gomez, S.; Arenas, A.; Gleeson, James P. (American Physical Society, 2016)
    We present an analytical approach for bond percolation on multiplex networks and use it to determine the expected size of the giant connected component and the value of the critical bond occupation probability in these ...
  • Cassidy, Ailbhe (University of Limerick, 2019)
    We live in a world surrounded by networks. They are ubiquitous. Be it social media networks linking us to our friends, transportation networks interconnecting locations around the globe, or the metabolic network breaking ...
  • Hackett, Adam W. (University of Limerick, 2011)
    The network topologies on which many natural and synthetic systems are built provide ideal settings for the emergence of complex phenomena. One well-studied manifestation of this, called a cascade or avalanche, is observed ...
  • 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. (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 ...
  • 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 ...
  • 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 ...
  • Koher, Andreas; Lentz, Hartmut H.K.; Gleeson, James P. (American Physical Society, 2019)
    We present a contact-based model to study the spreading of epidemics by means of extending the dynamic message-passing approach to temporal networks. The shift in perspective from node- to edgecentric quantities enables ...
  • Cellai, Davide; Lawlor, Aonghus; Dawson, Kenneth A; Gleeson, James P. (American Physical Society, 2013)
    k-core percolation is a percolation model which gives a notion of network functionality and has many applications in network science. In analyzing the resilience of a network under random damage, an extension of this model ...
  • 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 ...
  • O'Sullivan, David J.P. (University of Limerick, 2017)
    Networks are ubiquitous in the world around us. Any system of interacting objects can be conveniently represented as a network, allowing for mathematical interrogation of its properties. These systems range from news ...
  • 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.; O'Sullivan, Kevin P.; Banos, Ranquel, A.; Moreno, Yamir (American Physical Society, 2016)
    Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we ...
  • Faqeeh, Ali; Melnik, Sergey; Colomer-deSimón, Pol; Gleeson, James P. (American Physical Society, 2016)
    It is commonly assumed in percolation theories that at most one percolating cluster can exist in a network. We show that several coexisting percolating clusters (CPCs) can emerge in networks due to limited mixing, i.e., a ...

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