Multi-waveform inference of gravitational waves
arXiv:1910.09138 · doi:10.1103/PhysRevD.101.064037
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.
arXiv comment6 pages, 5 figures, 3 tables, accepted in Phys. Rev. D
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