MONTE CARLO METHODS FOR GENERATION OF RANDOM GRAPHS

B. Waclaw*, L. Bogacz, Z. Burda, W. Janke

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Random graphs are widely used for modeling complex networks. Instead of considering many different models, to study dynamical phenomena on networks, it is desirable to design a general algorithm which produces random graphs with a variety of properties. Here we present a Monte Carlo method based on a random walk in the space of graphs. By ascribing to each graph a statistical weight we can generate networks of different types by tuning the weight function. The algorithm allows in particular to perform multicanonical simulations known, e.g., from spin models.

Original languageEnglish
Title of host publicationPATH INTEGRALS: NEW TRENDS AND PERSPECTIVES, PROCEEDINGS
EditorsW Janke, A Pelster
Place of PublicationSINGAPORE
PublisherWORLD SCIENTIFIC PUBL CO PTE LTD
Pages342-345
Number of pages4
ISBN (Print)978-981-283-726-4
Publication statusPublished - 2008
Event9th International Conference on Path Integrals - Dresden, Germany
Duration: 23 Sep 200728 Sep 2007

Conference

Conference9th International Conference on Path Integrals
Country/TerritoryGermany
Period23/09/0728/09/07

Keywords

  • Complex networks
  • Random graphs
  • Monte Carlo methods
  • Multicanonical simulations
  • STATISTICAL-MECHANICS
  • COMPLEX NETWORKS

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