Method for estimation of gravitational-wave transient model parameters in frequency–time maps
A common technique for detection of gravitational-wave (GW) signals is searching for excess power in frequency–time (ft)-maps of GW detector data. In the event of a detection, model selection and parameter estimation will be performed in order to explore the properties of the source. In this paper, we develop a Bayesian statistical method for extracting model-dependent parameters from observed GW signals in ft-maps. We demonstrate the method by recovering the parameters of model GW signals added to simulated advanced LIGO noise. We also characterize the performance of the method and discuss prospects for future work.
© 2014 IOP Publishing Ltd. Received 17 April 2014, revised 25 June 2014; Accepted for publication 7 July 2014; Published 5 August 2014. The authors would like to thank Matthew Pitkin for help running the likelihood sampler. MC was supported by the National Science Foundation Graduate Research Fellowship Program, under NSF grant number DGE 1144152. ET is a member of the LIGO Laboratory, supported by funding from United States National Science Foundation. NCʼs work was supported by NSF grant PHY-1204371. JGʼs work is supported by the Royal Society. LIGO was constructed by the California Institute of Technology and Massachusetts Institute of Technology with funding from the National Science Foundation and operates under cooperative agreement PHY-0757058. The authors thank the LIGO and Virgo Collaborations for providing the data plotted in figure 4. This paper has been assigned LIGO document number LIGO-P1400043.
Submitted - 1404.4642v1.pdf