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arXiv · 1901.11346

Markov chain approach to anomalous diffusion on Newman-Watts networks

Alfonso Allen-Perkins·Alfredo Blanco Serrano·Thiago Albuquerque de Assis·Juan Manuel Pastor·Roberto F. S. Andrade
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Abstract

A Markov chain (MC) formalism is used to investigate the mean-square displacement (MSD) of a random walker on Newman-Watts (NW) networks. It leads to a precise analysis of the conditions for the emergence of anomalous sub- or super-diffusive regimes in such random media. Whereas results provided by most numerical approaches used so far base their results on the computation of a large number of independent runs over many equivalent substrates, the MC framework is applied only once to each equivalent sample. Starting from the simple cycle graph with $2k$ nearest neighbor connections, for which exact MSD expressions within the MC formalism can be derived, the randomness and complexity of the substrate is easily controlled by the number $x$ of added links. Results for different values of $k$, $x$, and the number $N$ of nodes make it possible to distinguish actual anomalous regimes from transient behavior and finite size effects. Albeit the high computing cost restricts the size of our networks to $N\leq1500$ nodes, our very precise results justify a new and more comprehensive scaling ansatz for walker dynamics, from which the behavior for very large networks can be derived.

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Alfonso Allen-Perkins, Alfredo Blanco Serrano, Thiago Albuquerque de Assis, Juan Manuel Pastor, Roberto F. S. Andrade. 2019-02-26. Markov chain approach to anomalous diffusion on Newman-Watts networks. https://doi.org/10.1088/1742-5468%2Fab14dc

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