English

Trapping in complex networks

Disordered Systems and Neural Networks 2008-11-17 v2 Statistical Mechanics

Abstract

We investigate the trapping problem in Erdos-Renyi (ER) and Scale-Free (SF) networks. We calculate the evolution of the particle density ρ(t)\rho(t) of random walkers in the presence of one or multiple traps with concentration cc. We show using theory and simulations that in ER networks, while for short times ρ(t)exp(Act)\rho(t) \propto \exp(-Act), for longer times ρ(t)\rho(t) exhibits a more complex behavior, with explicit dependence on both the number of traps and the size of the network. In SF networks we reveal the significant impact of the trap's location: ρ(t)\rho(t) is drastically different when a trap is placed on a random node compared to the case of the trap being on the node with the maximum connectivity. For the latter case we find ρ(t)exp[At/Nγ2γ1\avk]\rho(t)\propto\exp\left[-At/N^\frac{\gamma-2}{\gamma-1}\av{k}\right] for all γ>2\gamma>2, where γ\gamma is the exponent of the degree distribution P(k)kγP(k)\propto k^{-\gamma}.

Keywords

Cite

@article{arxiv.0808.1736,
  title  = {Trapping in complex networks},
  author = {Aristotelis Kittas and Shai Carmi and Shlomo Havlin and Panos Argyrakis},
  journal= {arXiv preprint arXiv:0808.1736},
  year   = {2008}
}

Comments

Appendix added

R2 v1 2026-06-21T11:09:49.090Z