Scaling and precursor motifs in earthquake networks

TL;DR

This paper introduces a network-based method to analyze earthquake correlations, revealing that specific motifs involving distant aftershocks often precede major earthquakes, suggesting potential for early warning indicators.

Contribution

The study demonstrates that earthquake networks with particular motifs can identify patterns that occur before large seismic events, offering new insights into earthquake prediction.

Findings

Motifs involving far aftershocks are frequent before major earthquakes.

Network analysis can potentially serve as an early warning tool.

Major earthquakes are preceded by identifiable network patterns.

Abstract

A measure of the correlation between two earthquakes is used to link events to their aftershocks, generating a growing network structure. In this framework one can quantify whether an aftershock is close or far, from main shocks of all magnitudes. We find that simple network motifs involving links to far aftershocks appear frequently before the three biggest earthquakes of the last 16 years in Southern California. Hence, networks could be useful to detect symptoms typically preceding major events.