Allsky search with VSR 1 data F Antonucci

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

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. 2

• Low amplitude lines can be very persistent 3

. 585 Hz. 285 -. 3 Hz 1. 745 -1. 76 -1. 8 Hz. 2 Hz 1. 0 Hz • Small disturbances ‘accumulates’ in time and clearly emerges in the total peak frequency distribution 4

Harmonics of 0. 333 Hz: up to ~60 Hz 1. 0 Hz: up to ~200 Hz 2. 6314 Hz: mainly in 315 -355 Hz, 560 -589 Hz, 602 -621 Hz, 805 -828 Hz 2. 6316 Hz: mainly in 240 -290 Hz 10 Hz: nearly everywhere in 0 -2 k. Hz 12. 2782 Hz 19. 2309 Hz: 55 harmonics spread over the whole band 38. 728 Hz 41. 6179 Hz 180. 5489 Hz 5

• 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. 6

• 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. 7

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• 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. 9

• 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 VSR 1 • Extend the analysis to the second part of VSR 1 10