Distribution of the Largest Aftershocks in Branching Models of Triggered Seismicity: Theory of the Universal Bath's law

Abstract

Using the ETAS branching model of triggered seismicity, we apply the formalism of generating probability functions to calculate exactly the average difference between the magnitude of a mainshock and the magnitude of its largest aftershock over all generations. This average magnitude difference is found empirically to be independent of the mainshock magnitude and equal to 1.2, a universal behavior known as Bath's law. Our theory shows that Bath's law holds only sufficiently close to the critical regime of the ETAS branching process. Allowing for error bars +- 0.1 for Bath's constant value around 1.2, our exact analytical treatment of Bath's law provides new constraints on the productivity exponent alpha and the branching ratio n: $0.9<=alpha<=1$ and 0.8 <= n <= 1. We propose a novel method for measuring alpha based on the predicted renormalization of the Gutenberg-Richter distribution of the magnitudes of the largest aftershock. We also introduce the ``second Bath's law for foreshocks: the probability that a main earthquake turns out to be the foreshock does not depend on its magnitude.

25 pages with 8 figures

References in corpus (10)

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• Power law distribution of seismic rates: theory and data

Cited by in corpus (8)

• "Universal" Distribution of Inter-Earthquake Times Explained
• Theory of Earthquake Recurrence Times
• Constraints on the Size of the Smallest Triggering Earthquake from the ETAS Model, Baath's Law, and Observed Aftershock Sequences
• Vere-Jones' Self-Similar Branching Model
• Renormalization of the ETAS branching model of triggered seismicity from total to observable seismicity
• Statistical Physics Approaches to Seismicity
• Generating Functions and Stability Study of Multivariate Self-Excited Epidemic Processes
• Hierarchy of Temporal Responses of Multivariate Self-Excited Epidemic Processes