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arxiv: 1206.2495 · v3 · pith:HTXXLTZ4new · submitted 2012-06-12 · ❄️ cond-mat.stat-mech · cond-mat.mes-hall

Diffusion in sparse networks: linear to semi-linear crossover

classification ❄️ cond-mat.stat-mech cond-mat.mes-hall
keywords diffusionnetworkstransitionanalysisdescribedlinearsparsesystem
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We consider random networks whose dynamics is described by a rate equation, with transition rates $w_{nm}$ that form a symmetric matrix. The long time evolution of the system is characterized by a diffusion coefficient $D$. In one dimension it is well known that $D$ can display an abrupt percolation-like transition from diffusion ($D>0$) to sub-diffusion (D=0). A question arises whether such a transition happens in higher dimensions. Numerically $D$ can be evaluated using a resistor network calculation, or optionally it can be deduced from the spectral properties of the system. Contrary to a recent expectation that is based on a renormalization-group analysis, we deduce that $D$ is finite; suggest an "effective-range-hopping" procedure to evaluate it; and contrast the results with the linear estimate. The same approach is useful for the analysis of networks that are described by quasi-one-dimensional sparse banded matrices.

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