David Keitel, Reinhard Prix, Maria Alessandra Papa, Maham Siddiqi
Continuous gravitational waves (CW) are expected from spinning neutron stars
with non-axisymmetric deformations. A network of interferometric detectors
(LIGO, Virgo and GEO600) is looking for these signals. They are predicted to be
very weak and retrievable only by integration over long observation times. One
of the standard methods of CW data analysis is the multi-detector F-statistic.
In a typical search, the F-statistic is computed over a range in frequency,
spin-down and sky position, and the candidates with highest F values are kept
for further analysis. However, this detection statistic is susceptible to a
class of noise artifacts, strong monochromatic lines in a single detector. By
assuming an extended noise model - standard Gaussian noise plus single-detector
lines - we can use a Bayesian odds ratio to derive a generalized detection
statistic, the line veto (LV-) statistic. In the absence of lines, it behaves
similarly to the F-statistic, but it is more robust against line artifacts. In
the past, ad-hoc post-processing vetoes have been implemented in searches to
remove these artifacts. Here we provide a systematic framework to develop and
benchmark this class of vetoes. We present our results from testing this
LV-statistic on simulated data.
View original:
http://arxiv.org/abs/1201.5244
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