Nicola Perra, Ph.D.
  • Home
  • About Me
  • Research
    • Dynamical Processes on Time-Varying Networks
    • Contagion Models and Adaptive Behavior
    • Epidemics in Structured Populations
    • Global Epidemic and Mobility Model: GLEaM
    • Modeling and Studying Online Social Networks
    • Resilience of Coevolving and Interdependent Networks
    • Centrality Measures on Complex Networks
  • Publications
  • In the Press
  • Softwares and Online Projects
  • Talks
  • Contacts
  • Home
  • About Me
  • Research
    • Dynamical Processes on Time-Varying Networks
    • Contagion Models and Adaptive Behavior
    • Epidemics in Structured Populations
    • Global Epidemic and Mobility Model: GLEaM
    • Modeling and Studying Online Social Networks
    • Resilience of Coevolving and Interdependent Networks
    • Centrality Measures on Complex Networks
  • Publications
  • In the Press
  • Softwares and Online Projects
  • Talks
  • Contacts

Dynamical Processes on Time-Varying Networks

The study of dynamical processes on complex networks has  been focused mostly in two limits: the timescale describing the evolution of the process is usually considered either much slower or much faster than the timescale describing the change of the network. In the first case the graph is considered as static. In the second case instead the graph is considered as annealed.
However, in many cases the two timescales are comparable and cannot be decoupled. The time duration and the co-occurrence of links is crucial.  The understanding and characterization of this limit of timescale mixing is still partial, limited, and a very popular topic in networks science. 
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