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Search for continuous gravitational waves: improving robustness versus instrumental artifacts

MPG-Autoren
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Keitel,  D.
Laser Interferometry & Gravitational Wave Astronomy, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Prix,  R.
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Papa,  M. A.
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Leaci,  P.
Laser Interferometry & Gravitational Wave Astronomy, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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1311.5738v1.pdf
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PhysRevD.89_064023.pdf
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Zitation

Keitel, D., Prix, R., Papa, M. A., Leaci, P., & Siddiqi, M. (2014). Search for continuous gravitational waves: improving robustness versus instrumental artifacts. Physical Review D, 89: 064023. doi:10.1103/PhysRevD.89.064023.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0014-A921-F
Zusammenfassung
The standard multi-detector F-statistic for continuous gravitational waves is susceptible to false alarms from instrumental artifacts, for example monochromatic sinusoidal disturbances (lines). This vulnerability to line artifacts arises because the F-statistic compares the signal hypothesis to a Gaussian-noise hypothesis, and hence is triggered by anything that resembles the signal hypothesis more than Gaussian noise. Various ad-hoc veto methods to deal with such line artifacts have been proposed and used in the past. Here we develop a Bayesian framework that includes an explicit alternative hypothesis to model disturbed data. We introduce a simple line model that defines lines as signal candidates appearing only in one detector. This allows us to explicitly compute the odds between the signal hypothesis and an extended noise hypothesis, resulting in a new detection statistic that is more robust to instrumental artifacts. We present and discuss results from Monte-Carlo tests on both simulated data and on detector data from the fifth LIGO science run. We find that the line-robust detection statistic retains the detection power of the standard F-statistic in Gaussian noise, while it can be substantially more sensitive in the presence of line artifacts. This new statistic also equals or surpasses the performance of the popular F-statistic consistency veto.