1. All-sky search with VSR1 data
F. Antonucci, P. Astone, S. d’Antonio, S. Frasca, C. Palomba
calibrated data
Data quality
SFDB
Average spect rum estimation
Data quality
SFDB
Average spect rum estimation
peak map
peak map
hough transf.
hough transf.
candidates
coincidences
candidates
coherent step
events

2. Three main categories of disturbances:
persistency
Three main categories of disturbances:
- ‘known’ Virgo lines (i.e present in the list);
- lines of likely instrumental origin (mainly harmonics of a set of frequencies);
- lines of unknown origin.

3. Low amplitude lines can be very persistent

4. .585Hz Hz Hz
.2Hz
1.0Hz
Small disturbances ‘accumulates’ in time and clearly emerges in the total peak frequency distribution

5. Harmonics of
0.333Hz: up to ~60 Hz
1.0Hz: up to ~200 Hz
2.6314Hz: mainly in Hz, Hz, Hz, Hz
2.6316Hz: mainly in Hz
10Hz: nearly everywhere in 0-2kHz Hz
Hz: 55 harmonics spread over the whole band
38.728Hz Hz Hz

6. Even after removing lines from the Virgo known line list, there are residual disturbances
This happens because lines with rather small amplitude are not detected by the line monitor tool, but if they are persistent enough we anyway find them in the peak frequency distribution.

7. Then, a further cut has been applied at the level of each peakmap, but still there are small but clear residuals in the total peak map, which produce candidate excess.

9. Even a small peaks excess can produce a big excess in the number of candidates. This is due to the fact that each disturbed frequency bin affects all the search frequency within a Doppler band range around it.

10. Searching for non-zero spin-down candidates slightly reduces the effect of narrow disturbances
Next steps
Better (i.e more rough) cleaning by cutting bands around violin modes and calibration lines
Repeat the analysis on the first part of VSR1
Extend the analysis to the second part of VSR1