{
  "id": "1811.04904",
  "version": "v1",
  "published": "2018-11-12T18:44:05.000Z",
  "updated": "2018-11-12T18:44:05.000Z",
  "title": "Parameter estimation for black hole echo signals and their statistical significance",
  "authors": [
    "Alex B. Nielsen",
    "Collin D. Capano",
    "Julian Westerweck"
  ],
  "comment": "7 pages, 5 figures",
  "categories": [
    "gr-qc"
  ],
  "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.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2018-11-12T18:44:05.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "black hole echo signals",
      "parameter estimation",
      "statistical significance",
      "model selection probabilities",
      "gravitational wave data"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 7,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}