Publication
The Bayesian Earthquake Analysis Tool
Publisher:
Seismological Society of America (SSA)
Date:
22-01-2020
DOI:
10.1785/0220190075
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 s lers. If desired, BEAT’s modular architecture allows for easy implementation of additional features, for ex le, alternative s ling algorithms. We demonstrate the functionality and performance of the package using five earthquake source estimation ex les: 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.