Network of Earthquakes and Recurrences Therein

TL;DR

This paper constructs a network of earthquakes based on a correlation metric to analyze their complex dynamics, revealing typical rupture lengths, hub structures, and recurrence time distributions consistent with known seismic laws.

Contribution

It introduces a modified correlation metric to build earthquake networks and analyzes recurrence lengths and times, providing new insights into earthquake dynamics and clustering.

Findings

Recurrence lengths are unimodal and relate to rupture sizes.

Large earthquakes act as hubs in the network.

Recurrence times follow a power law consistent with Omori law.

Abstract

We quantify the correlation between earthquakes and use the same to distinguish between relevant causally connected earthquakes. Our correlation metric is a variation on the one introduced by Baiesi and Paczuski (2004). A network of earthquakes is constructed, which is time ordered and with links between the more correlated ones. Data pertaining to the California region has been used in the study. Recurrences to earthquakes are identified employing correlation thresholds to demarcate the most meaningful ones in each cluster. The distribution of recurrence lengths and recurrence times are analyzed subsequently to extract information about the complex dynamics. We find that the unimodal feature of recurrence lengths helps to associate typical rupture lengths with different magnitude earthquakes. The out-degree of the network shows a hub structure rooted on the large magnitude earthquakes. In-degree distribution is seen to be dependent on the density of events in the neighborhood. Power laws are also obtained with recurrence time distribution agreeing with the Omori law.