- Letter
Motif-based mean-field approximation of interacting particles on clustered networks
Phys. Rev. E 105, L042301 – Published 28 April, 2022
DOI: https://doi.org/10.1103/PhysRevE.105.L042301
Abstract
Interacting particles on graphs are routinely used to study magnetic behavior in physics, disease spread in epidemiology, and opinion dynamics in social sciences. The literature on mean-field approximations of such systems for large graphs typically remains limited to specific dynamics, or assumes cluster-free graphs for which standard approximations based on degrees and pairs are often reasonably accurate. Here, we propose a motif-based mean-field approximation that considers higher-order subgraph structures in large clustered graphs. Numerically, our equations agree with stochastic simulations where existing methods fail.
