Constrained spin dynamics description of random walks on hierarchical scale-free networks

dc.creatorNoh, Jae Dong
dc.creatorRieger, Heiko
dc.date2003-10-15
dc.date2004-04-10
dc.date.accessioned2026-07-07T02:54:12Z
dc.date.available2026-07-07T02:54:12Z
dc.descriptionWe study a random walk problem on the hierarchical network which is a scale-free network grown deterministically. The random walk problem is mapped onto a dynamical Ising spin chain system in one dimension with a nonlocal spin update rule, which allows an analytic approach. We show analytically that the characteristic relaxation time scale grows algebraically with the total number of nodes $N$ as $T \sim N^z$. From a scaling argument, we also show the power-law decay of the autocorrelation function $C_{\bfsigma}(t)\sim t^{-α}$, which is the probability to find the Ising spins in the initial state ${\bfsigma}$ after $t$ time steps, with the state-dependent non-universal exponent $α$. It turns out that the power-law scaling behavior has its origin in an quasi-ultrametric structure of the configuration space.
dc.description9 pages, 6 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0310344
dc.identifierhttp://arxiv.org/abs/cond-mat/0310344
dc.identifierPhys. Rev. E 69, 036111 (2004)
dc.identifierdoi:10.1103/PhysRevE.69.036111
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/22450
dc.subjectStatistical Mechanics
dc.titleConstrained spin dynamics description of random walks on hierarchical scale-free networks
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