LECTURERS

  • Corina Tarnita - Princeton University
  • Fernando Albuquerque de Oliveira - UNB
  • Francisco Aparecido Rodrigues - USP
  • Francisco Castilho Alcaraz - USP
  • Gabriel Teixeira Landi - USP
  • Irene Giardina - INFN (Roma1)
  • Marjolein Dijkstra - Utrecht University
  • Marta Gonzalez - UC Berkeley
  • Romualdo Pastor Satorras - UPC
  • Satya Majumdar - CNRS
  • Ying Wai Li - LANL
  • ROUND TABLES

  • Ivon Fittipaldi - the birth of ENFMC
  • COVID 19 Pandemic
  • Diversity in Physics
  • TUTORIALS

  • Machine Learning - Ying Wai Li - LANL

  • Active Matter - Francesco Ginelli - UNINSUBRIA

  • Compartmental models for epidemic processes on complex networks - Silvio C. Ferreira - UFV

    Spreading processes are extremely relevant in several contexts, from contagious diseases to the dissemination of information on social networks. The spreading almost universally happens by means of contacts among elements which can be properly represented with the theoretical framework of complex networks. A key aspect of networked structures is their high level of heterogeneity that leads to the dynamical behaviors much more complex than in standard lattice models or homogeneous mixing approaches. In this tutorial, a short introduction of spreading processes on the top of complex networks will be addressed using fundamental models such as SIS and SIR. The main theoretical and numerical approaches and a revision of network theory with the properties important for understanding the spreading processes will be presented. Finally, some advanced topics, such as localization phenomena and applications to COVID19 pandemics, will be presented as illustrations of the power of the theoretical tools presented in the tutorial.

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    Desenho do logo: Saulo Reis