Geographical Coarsegraining of Complex Networks

Simple item page
dc.creatorKim, Beom Jun
dc.date2004-09-04
dc.date.accessioned2026-07-07T03:00:18Z
dc.date.available2026-07-07T03:00:18Z
dc.descriptionWe perform the renormalization-group-like numerical analysis of geographically embedded complex networks on the two-dimensional square lattice. At each step of coarsegraining procedure, the four vertices on each $2 \times 2$ square box are merged to a single vertex, resulting in the coarsegrained system of the smaller sizes. Repetition of the process leads to the observation that the coarsegraining procedure does not alter the qualitative characteristics of the original scale-free network, which opens the possibility of subtracting a smaller network from the original network without destroying the important structural properties. The implication of the result is also suggested in the context of the recent study of the human brain functional network.
dc.descriptionTo appear in Phys. Rev. Lett
dc.identifierhttps://arxiv.org/abs/cond-mat/0409095
dc.identifierhttp://arxiv.org/abs/cond-mat/0409095
dc.identifierPhys.Rev.Lett. 93 (2004) 168701
dc.identifierdoi:10.1103/PhysRevLett.93.168701
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/24786
dc.subjectDisordered Systems and Neural Networks
dc.subjectAstrophysics
dc.subjectStatistical Mechanics
dc.subjectNeurons and Cognition
dc.titleGeographical Coarsegraining of Complex Networks
dc.typetext

Files

Collections

arXiv