Earthquake Correlations and Networks- A Comparative Study
T. R. Krishna Mohan P. G., Revathi

TL;DR
This study constructs earthquake networks based on correlation metrics across different regions, revealing universal recurrence length features and power-law recurrence time distributions that extend aftershock laws.
Contribution
It introduces a correlation-based network model for earthquakes and compares seismic regions to identify universal and region-specific features.
Findings
Recurrence length distribution is unimodal and consistent across regions.
Large earthquakes act as hubs in the network with high out-degree.
Recurrence time distribution follows a two-regime power law, extending Omori's 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. Recurrences to earthquakes are identified employing correlation thresholds to demarcate the most meaningful ones in each cluster. Data pertaining to three different seismic regions, viz. California, Japan and Himalayas, are comparatively analyzed using such a network model. The distribution of recurrence lengths and recurrence times are two of the key features analyzed to draw conclusions about the universal aspects of such a network model. We find that the unimodal feature of recurrence length distribution, which helps to associate typical rupture lengths with…
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Taxonomy
Topicsearthquake and tectonic studies · Earthquake Detection and Analysis · Complex Systems and Time Series Analysis
