Rochester Institute of Technology

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Parameter estimation for black hole echo signals and their statistical significance
by Alex B. Nielsen, Collin D. Capano, Ofek Birnholtz, Julian Westerweck
(Tuesday, November 20, 2018)

Abstract

Searching for black hole echo signals with gravitational waves provides a means of probing the near-horizon regime of these objects. We demonstrate a pipeline to efficiently search for these signals in gravitational wave data and calculate model selection probabilities between signal and no-signal hypotheses. As an example of its use we calculate Bayes factors for the Abedi-Dykaar-Afshordi (ADA) model on events in LIGO's first observing run and compare to existing results in the literature. We discuss the benefits of using a full likelihood exploration over existing search methods that used template banks and calculated p-values. We use the waveforms of ADA, although the method is easily extendable to other waveforms. With these waveforms we are able to demonstrate a range of echo amplitudes that is already is ruled out by the data.

CCRG Authors

Birnholtz, Ofek