Template-based gravitational-wave echoes search using Bayesian model selection

• Published in: Physical review. D 2019-04, Vol.99 (8), p.1, Article 084052
• Main Authors: Lo, Rico K. L., Li, Tjonnie G. F., Weinstein, Alan J.
• Format: Article
• Language: English
• Subjects: Bayesian analysis; Computer simulation; Echoes; Gravitation; Gravitational waves; Random noise; Searching
• ISSN: 2470-0010; 2470-0029
• DOI: 10.1103/PhysRevD.99.084052

The ringdown of the gravitational-wave signal from a merger of two black holes has been suggested as a probe of the structure of the remnant compact object, which may be more exotic than a black hole. It has been pointed out that there will be a train of echoes in the late-time ringdown stage for different types of exotic compact objects. In this paper, we present a template-based search methodology using Bayesian statistics to search for echoes of gravitational waves. Evidence for the presence or absence of echoes in gravitational-wave events can be established by performing Bayesian model selection. The Occam factor in Bayesian model selection will automatically penalize the more complicated model that echoes are present in gravitational-wave strain data because of its higher degree of freedom to fit the data. We find that the search methodology was able to identify gravitational-wave echoes with Abedi et al.'s echoes waveform model about 82.3% of the time in simulated Gaussian noise in the Advanced LIGO and Virgo network and about 61.1% of the time in real noise in the first observing run of Advanced LIGO with ≥5σ significance. Analyses using this method are performed on the data of Advanced LIGO's first observing run, and we find no statistical significant evidence for the detection of gravitational-wave echoes. In particular, we find