Effective non-universality of the quorum percolation model on directed graphs with Gaussian in-degree

Renaud Renault, Pascal Monceau, Samuel Bottani and Stéphane Métens

Physica A: Statistical Mechanics and its Applications, 2014, vol. 414, issue C, 352-359

Abstract: We investigate a model derived from bootstrap percolation on a directed random graph with Gaussian in-degree useful in describing the collective behavior of dissociated neuronal networks. By developing a continuous version of the model, we were able to provide accurate values of the critical thresholds and exponents associated with the occurrence of a giant cluster. As a main result, it turns out that the values of the exponents calculated over a numerical accessible range covering more than two orders of magnitude below the critical point exhibit a slight dependence upon the connectivity of the graph.

Keywords: Phase transitions general studies; Neural networks; Percolation; Complex networks (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:414:y:2014:i:c:p:352-359

DOI: 10.1016/j.physa.2014.07.028

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