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With the advanced LIGO and Virgo detectors taking observations the detection of gravitational waves is expected within the next few years. Extracting astrophysical information from gravitational wave detections is a well-posed problem and thoroughly studied when detailed models for the waveforms are available. However, one motivation for the field of gravitational wave astronomy is the potential for new discoveries. Recognizing and characterizing unanticipated signals requires data analysis techniques which do not depend on theoretical predictions for the gravitational waveform. Past searches for short-duration un-modeled gravitational wave signals have been hampered by transient noise artifacts, or glitches, in the detectors. In some cases, even high signal-to-noise simulated astrophysical signals have proven difficult to distinguish from glitches, so that essentially any plausible signal could be detected with at most 2-3 $sigma$ level confidence. We have put forth the BayesWave algorithm to differentiate between generic gravitational wave transients and glitches, and to provide robust waveform reconstruction and characterization of the astrophysical signals. Here we study BayesWaves capabilities for rejecting glitches while assigning high confidence to detection candidates through analytic approximations to the Bayesian evidence. Analytic results are tested with numerical experiments by adding simulated gravitational wave transient signals to LIGO data collected between 2009 and 2010 and found to be in good agreement.
We present a method for assigning a statistical significance to detection candidates in targeted searches for continuous gravitational waves from known pulsars, without assuming the detector noise is Gaussian and stationary. We take advantage of the
We show that for detections of gravitational-wave transients, constraints can be given on physical parameters of the source without using any specific astrophysical models. Relying only on fundamental principles of general relativity, we can set uppe
The observed distributions of the source properties from gravitational-wave detections are biased due to the selection effects and detection criteria in the detections, analogous to the Malmquist bias. In this work, this observation bias is investiga
A central challenge in Gravitational Wave Astronomy is identifying weak signals in the presence of non-stationary and non-Gaussian noise. The separation of gravitational wave signals from noise requires good models for both. When accurate signal mode
Gravitational wave astronomy has established its role in measuring the equation of state governing cold supranuclear matter. To date and in the near future, gravitational wave measurements from neutron star binaries are likely to be restricted to the