Scale-invariant statistics of period in directed earthquake network

TL;DR

This paper discovers a scale-invariant power-law distribution in the period statistics of a directed earthquake network, revealing fundamental challenges in predicting earthquake recurrence based on network analysis.

Contribution

It introduces a novel analysis of earthquake networks showing that the period distribution follows a power law, highlighting scale invariance in seismic activity.

Findings

Period distribution obeys a power law

Scale invariance observed in earthquake network statistics

Highlights difficulty in statistical estimation of earthquake recurrence

Abstract

A new law regarding structure of the earthquake networks is found. The seismic data taken in California is mapped to a growing directed network. Then, statistics of period in the network, which implies that after how many earthquakes an earthquake returns to the initial location, is studied. It is found that the period distribution obeys a power law, showing the fundamental difficulty of statistical estimate of period.