Stochastic Dynamics on Hypergraphs and the Spatial Majority Rule Model

Nicolas Lanchier, J. Neufer

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


This article starts by introducing a new theoretical framework to model spatial systems which is obtained from the framework of interacting particle systems by replacing the traditional graphical structure that defines the network of interactions with a structure of hypergraph. This new perspective is more appropriate to define stochastic spatial processes in which large blocks of vertices may flip simultaneously, which is then applied to define a spatial version of the Galam's majority rule model. In our spatial model, each vertex of the lattice has one of two possible competing opinions, say opinion 0 and opinion 1, as in the popular voter model. Hyperedges are updated at rate one, which results in all the vertices in the hyperedge changing simultaneously their opinion to the majority opinion of the hyperedge. In the case of a tie in hyperedges with even size, a bias is introduced in favor of type 1, which is motivated by the principle of social inertia. Our analytical results along with simulations and heuristic arguments suggest that, in any spatial dimensions and when the set of hyperedges consists of the collection of all n×⋯×n blocks of the lattice, opinion 1 wins when n is even while the system clusters when n is odd, which contrasts with results about the voter model in high dimensions for which opinions coexist. This is fully proved in one dimension while the rest of our analysis focuses on the cases when n=2 and n=3 in two dimensions.

Original languageEnglish (US)
Pages (from-to)21-45
Number of pages25
JournalJournal of Statistical Physics
Issue number1-2
StatePublished - Apr 2013


  • Hypergraph
  • Interacting particle systems
  • Majority rule
  • Social group
  • Voter model

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics


Dive into the research topics of 'Stochastic Dynamics on Hypergraphs and the Spatial Majority Rule Model'. Together they form a unique fingerprint.

Cite this