Onset of anomalous diffusion from local motion rules

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Abstract

Anomalous diffusion processes, in particular superdiffusive ones, are known to be efficient strategies for searching and navigation in animals and also in human mobility. One way to create such regimes are Lévy flights, where the walkers are allowed to perform jumps, the "flights," that can eventually be very long as their length distribution is asymptotically power-law distributed. In our work, we present a model in which walkers are allowed to perform, on a one-dimensional lattice, "cascades" of n unitary steps instead of one jump of a randomly generated length, as in the Lévy case, where n is drawn from a cascade distribution pn. We show that this local mechanism may give rise to superdiffusion or normal diffusion when pn is distributed as a power law. We also introduce waiting times that are power-law distributed as well and therefore the probability distribution scaling is steered by the two local distributions power-law exponents. As a perspective, our approach may engender a possible generalization of anomalous diffusion in context where distances are difficult to define, as in the case of complex networks, and also provide an interesting model for diffusion in temporal networks.

Original languageEnglish
Article number022113
Number of pages8
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume95
Issue number2
DOIs
Publication statusPublished - 13 Feb 2017

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Anomalous Diffusion
Power Law
Cascade
Motion
Jump
Superdiffusion
cascades
Power-law Distribution
flight
Waiting Time
Complex Networks
Diffusion Process
Navigation
Animals
Probability Distribution
navigation
Exponent
Scaling
animals
exponents

Keywords

  • random walks
  • anomalous diffusion
  • levy flight
  • microscopic model

Cite this

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Onset of anomalous diffusion from local motion rules. / De Nigris, Sarah; Carletti, Timoteo; Lambiotte, Renaud.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 95, No. 2, 022113, 13.02.2017.

Research output: Contribution to journalArticle

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