Random field Ising model and community structure in complex networks

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dc.creatorSon, Seung-Woo
dc.creatorJeong, Hawoong
dc.creatorNoh, Jae Dong
dc.date2005-02-28
dc.date.accessioned2026-07-07T06:28:55Z
dc.date.available2026-07-07T06:28:55Z
dc.descriptionWe propose a method to find out the community structure of a complex network. In this method the ground state problem of a ferromagnetic random field Ising model is considered on the network with the magnetic field $B_s = +\infty$, $B_{t} = -\infty$, and $B_{i\neq s,t}=0$ for a node pair $s$ and $t$. The ground state problem is equivalent to the so-called maximum flow problem, which can be solved exactly numerically with the help of a combinatorial optimization algorithm. The community structure is then identified from the ground state Ising spin domains for all pairs of $s$ and $t$. Our method provides a criterion for the existence of the community structure, and is applicable to unweighted and weighted networks equally well. We demonstrate the performance of the method by applying it to the Barabási-Albert network, Zachary karate club network, the scientific collaboration network, and the stock price correlation network.
dc.description7 pages, 4 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0502672
dc.identifierhttp://arxiv.org/abs/cond-mat/0502672
dc.identifierEur. Phys. J. B 50, 431 (2006)
dc.identifierdoi:10.1140/epjb/e2006-00155-4
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/97861
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.titleRandom field Ising model and community structure in complex networks
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