2008/03/10 by Tiago P. Peixoto, Joern Davidsen, Jörn Davidsen · 1 citation
Earth and Planetary Sciences · Economics, Econometrics and Finance · Physics and Astronomy · #Artificial intelligence #Cluster analysis #Complex Systems and Time Series Analysis #Computer science #Geology #Induced seismicity #Physics #Seismology #Simple (philosophy) #Statistical physics #Theoretical and Computational Physics #cond-mat.dis-nn #earthquake and tectonic studies
paper · pdf · doi:10.1103/physreve.77.066107
11 pages, 16 figures
arxiv created 2008/03/10 · openalex publication_date 2008/06/10 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial 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.