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arXiv · 1910.09138

Multi-waveform inference of gravitational waves

Gregory Ashton·Sebastian Khan
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Abstract

Bayesian inference of gravitational wave signals is subject to systematic error due to modelling uncertainty in waveform signal models, coined approximants. A growing collection of approximants are available which use different approaches and make different assumptions to ease the process of model development. We provide a method to marginalize over the uncertainty in a set of waveform approximants by constructing a mixture-model multi-waveform likelihood. This method fits into existing workflows by determining the mixture parameters from the per-waveform evidences, enabling the production of marginalized combined sample sets from independent runs.

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BibTeXRIS

Gregory Ashton, Sebastian Khan. 2020-02-27. Multi-waveform inference of gravitational waves. https://doi.org/10.1103/physrevd.101.064037

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