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Continuous gravitational waves (CW) are expected from spinning neutron starswith non-axisymmetric deformations. A network of interferometric detectors(LIGO, Virgo and GEO600) is looking for these signals. They are predicted to bevery weak and retrievable only by integration over long observation times. Oneof 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 keptfor further analysis. However, this detection statistic is susceptible to aclass of noise artifacts, strong monochromatic lines in a single detector. Byassuming an extended noise model - standard Gaussian noise plus single-detectorlines - we can use a Bayesian odds ratio to derive a generalized detectionstatistic, the line veto (LV-) statistic. In the absence of lines, it behavessimilarly to the F-statistic, but it is more robust against line artifacts. Inthe past, ad-hoc post-processing vetoes have been implemented in searches toremove these artifacts. Here we provide a systematic framework to develop andbenchmark this class of vetoes. We present our results from testing thisLV-statistic on simulated data.

An F-statistic based multi-detector veto for detector artifacts in continuous-wave gravitational wave data