Citation

Shcherbakov R, Davidsen J, Tiampo KF. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 2013; 87(5-1): 052811.

Affiliation

Department of Earth Sciences, University of Western Ontario, London, Ontario, Canada N6A 5B7 and Department of Physics and Astronomy, University of Western Ontario, London, Ontario, Canada N6A 5B7.

Copyright

(Copyright © 2013, American Physical Society, Publisher American Institute of Physics)

DOI

unavailable

PMID

23767588

Abstract

Record-breaking avalanches generated by the dynamics of several driven nonlinear threshold models are studied. Such systems are characterized by intermittent behavior, where a slow buildup of energy is punctuated by an abrupt release of energy through avalanche events, which usually follow scale-invariant statistics. From the simulations of these systems it is possible to extract sequences of record-breaking avalanches, where each subsequent record-breaking event is larger in magnitude than all previous events. In the present work, several cellular automata are analyzed, among them the sandpile model, the Manna model, the Olami-Feder-Christensen (OFC) model, and the forest-fire model to investigate the record-breaking statistics of model avalanches that exhibit temporal and spatial correlations. Several statistical measures of record-breaking events are derived analytically and confirmed through numerical simulations. The statistics of record-breaking avalanches for the four models are compared to those of record-breaking events extracted from the sequences of independent and identically distributed (i.i.d.) random variables. It is found that the statistics of record-breaking avalanches for the above cellular automata exhibit behavior different from that observed for i.i.d. random variables, which in turn can be used to characterize complex spatiotemporal dynamics. The most pronounced deviations are observed in the case of the OFC model with a strong dependence on the conservation parameter of the model. This indicates that avalanches in the OFC model are not independent and exhibit spatiotemporal correlations.

Language: en