Testing general relativity with compact coalescing binaries: Comparing exact and predictive methods to compute the Bayes factor

Walter Del Pozzo, Katherine Grover, Ilya Mandel, Alberto Vecchio

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15 Citations (Scopus)


The second generation of gravitational-wave detectors is scheduled to start operations in 2015. Gravitational-wave signatures of compact binary coalescences could be used to accurately test the strong-field dynamical predictions of general relativity (GR). Computationally expensive data analysis pipelines, including TIGER (test infrastructure for general relativity), have been developed to carry out such tests. As a means to cheaply assess whether a particular deviation from GR can be detected, Cornish et al (2011 Phys. Rev. D 84 062003) and Vallisneri (2012 Phys. Rev. D 86 082001) recently proposed an approximate scheme to compute the Bayes factor between a GR gravitational-wave model and a model representing a class of alternative theories of gravity parametrized by one additional parameter. This approximate scheme is based on only two easy-to-compute quantities: the signal-to-noise ratio (SNR) of the signal and the fitting factor (FF) between the signal and the manifold of possible waveforms within GR. In this work, we compare the prediction from the approximate formula against an exact numerical calculation of the Bayes factor using the lalinference library. We find that, using frequency-domain waveforms, the approximate scheme predicts exact results with good accuracy, providing the correct scaling with the SNR at a FF value of 0.992 and the correct scaling with the FF at a SNR of 20, down to a FF of ∼0.9. We extend the framework for the approximate calculation of the Bayes factor, which significantly increases its range of validity, at least to FFs of ∼0.7 or higher.

Original languageEnglish
Article number205006
Pages (from-to)1-13
Number of pages13
JournalClassical and Quantum Gravity
Issue number20
Publication statusPublished - 21 Oct 2014
Externally publishedYes


  • compact binaries
  • data analysis
  • tests of general relativity

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