The Bayesian Earthquake Analysis Tool

Hannes Vasyura-Bathke, Jan Dettmer, Andreas Steinberg, Sebastian Heimann, Marius Paul Isken, Olaf Zielke, Paul Martin Mai, Henriette Sudhaus, Sigurjon Jonsson

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Abstract : The Bayesian earthquake analysis tool (BEAT) is an open-source Python software to conduct source-parameter estimation studies for crustal deformation events, such as earthquakes and magma intrusions, by employing a Bayesian framework with a flexible problem definition. The software features functionality to calculate Green’s functions for a homogeneous or a layered elastic half-space. Furthermore, algorithm(s) that explore the solution space may be selected from a suite of implemented samplers. If desired, BEAT’s modular architecture allows for easy implementation of additional features, for example, alternative sampling algorithms. We demonstrate the functionality and performance of the package using five earthquake source estimation examples: a full moment-tensor estimation; a double-couple moment-tensor estimation; an estimation for a rectangular finite source; a static finite-fault estimation with variable slip; and a full kinematic finite-fault estimation with variable hypocenter location, rupture velocity, and rupture duration. This software integrates many aspects of source studies and provides an extensive framework for joint use of geodetic and seismic data for nonlinear source- and noise-covariance estimation within layered elastic half-spaces. Furthermore, the software also provides an open platform for further methodological development and for reproducible source studies in the geophysical community.
Original languageEnglish (US)
JournalSeismological Research Letters
DOIs
StatePublished - Jan 22 2020

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