Network of recurrent events for the Olami-Feder-Christensen model

TL;DR

This study uses network analysis to evaluate how well the OFC earthquake model reproduces real seismic clustering, revealing both similarities and limitations in its ability to mimic observed earthquake patterns.

Contribution

It applies a network-based method to analyze the OFC model's synthetic seismic catalogs, highlighting its statistical properties and differences from real earthquake data.

Findings

OFC model networks show degree distributions similar to real seismicity.

Significant differences exist between OFC model and actual earthquake clustering.

The OFC model is insufficient to fully replicate seismic spatiotemporal patterns.

Abstract

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder and Christensen (OFC) to mimic earthquakes and investigate to which extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicty. Following a recently proposed method to characterize such clustering by networks of recurrent events [Geophys. Res. Lett. {\bf 33}, L1304, 2006], we find that for synthetic catalogs generated by the OFC model these networks have many non-trivial statistical properties. This includes characteristic degree distributions -- very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.