1. Stefan Hild S4 Data Workshop, Hannover, May 2005 Title 1 kHz Glitches in S4 Max-Planck-Institut für Gravitationsphysik (Albert-Einstein-Institut)

2. Stefan Hild S4 Data Workshop, Hannover, May 2005 GEO‘s sensitivity for last 20 days of S4 Peak sensitivity ‚drifted‘ during S4 (much more than at other frequencies)

3. Stefan Hild S4 Data Workshop, Hannover, May 2005 BLRMS of H(t) vs glitch rate H(t) BLRMS 990-1000 Hz Glitchrate 700-2000 Hz Found relation between glitchrate and peak sensitivity.

4. Stefan Hild S4 Data Workshop, Hannover, May 2005 Spectra for good and bad time Example times: high glitch rate 2005-03-22 06:10:00 low glitch rate 2005-03-22 13:00:00 Glitches cause additional noise between 400 Hz and 1.3 kHz

5. Stefan Hild S4 Data Workshop, Hannover, May 2005 Spectrograms of differential EP-P High glitchrate Low glitchrate Glitches present in MI_diff_EP  not an artifact from calibration process

6. Stefan Hild S4 Data Workshop, Hannover, May 2005 Timeseries of 1kHz Glitches Filtered with bandpass, 950 to 1050 Hz, 6 th Order

7. Stefan Hild S4 Data Workshop, Hannover, May 2005 Noise projections 1 kHz glitches can‘t be explained by our current set of noiseprojections

8. Stefan Hild S4 Data Workshop, Hannover, May 2005 Gliches vs BLRMS @ 1 kHz

9. Stefan Hild S4 Data Workshop, Hannover, May 2005 Timedomain distribution

10. Stefan Hild S4 Data Workshop, Hannover, May 2005 SNR distribution

11. Stefan Hild S4 Data Workshop, Hannover, May 2005 Number of pixels

12. Stefan Hild S4 Data Workshop, Hannover, May 2005 Duration of bursts

13. Stefan Hild S4 Data Workshop, Hannover, May 2005 Bandwidth of burst Probably maximal bandwidth is limited to 400 Hz (strong lines 822 and 1266 Hz)

14. Stefan Hild S4 Data Workshop, Hannover, May 2005 Time-delay between glitches

15. Stefan Hild S4 Data Workshop, Hannover, May 2005 Periodicity of the glitches Sometimes one can see a periodicity (5-10 times per hour) of the glitchrate Periodicity of 1.45 mHz

16. Stefan Hild S4 Data Workshop, Hannover, May 2005 1.45 mHz in autoalignment signals 1.45 mHz 2*1.45 mHz

17. Stefan Hild S4 Data Workshop, Hannover, May 2005 1.45 mHz 1.45 mHz in MC_AA rotation 2*1.45 mHz

18. Stefan Hild S4 Data Workshop, Hannover, May 2005 Temperatures in the central building 1.45 mHz 2*1.45 mHz 2.3 mHz

19. Stefan Hild S4 Data Workshop, Hannover, May 2005 2.3 mHz from air conditioning system 2.3 mHz is produced by the outdoor unit of central building‘s airconditioning system AC system usually dominates vertical seismic rms at the central building

20. Stefan Hild S4 Data Workshop, Hannover, May 2005 Temperatures in the central building 1.45 mHz 2*1.45 mHz 2.3 mHz from AC 1.45 and 2.9 mHz appear strongly in temperature of the laser bench

21. Stefan Hild S4 Data Workshop, Hannover, May 2005 Periodicity of the glitches Sometimes one can see a periodicity (5-10 times per hour) of the glitchrate Periodicity of 2.5 mHz

22. Stefan Hild S4 Data Workshop, Hannover, May 2005 2.5 mHz in MPR alignment 2.5 mHz 2*2.5 mHz 3*2.5 mHz 1.45 mHz 2.9 mHz

23. Stefan Hild S4 Data Workshop, Hannover, May 2005 2.5 mHz in MC2-AA 2.5 mHz 2*2.5 mHz 3*2.5 mHz

24. Stefan Hild S4 Data Workshop, Hannover, May 2005 2.5 mHz in central building‘s temperatures 2.5 mHz 2.3 mHz

25. Stefan Hild S4 Data Workshop, Hannover, May 2005 How to go on ?? Is there any possibility to get vetoes for the 1 kHz Glitches ? Do we have to make vetoes for the 1 kHz Glitches ? How can we avoid such a problem in future? More time in front of a data run (???) Some further effort is needed to investigate the Glitches and find their origin. Analysis of GEO S4 data Instrumental viewpoint Future issues

26. Stefan Hild S4 Data Workshop, Hannover, May 2005 How to attack the problem „Thinking“: Which hardware of GEO600 could cause glitches with these properties ? Coupling ? What experiments do we need to check a potential hypothesis? Data analysis: Try to find a correlation between glitchrate during S4 and ??? Compare detector status for good (low glitch rate) and bad time (high glitch rate). Anything different ? Maybe the periodicity leads us to origin of the glitches ?

27. Stefan Hild S4 Data Workshop, Hannover, May 2005 HACR: Burst and glitch analysis Take in 32 seconds of data Subdevide this into subsegments of 32 ms (Overlab of 28 ms) Windowing and FFT Spectrogram (2-dim set of numbers / pixels) Clustering Triggers = mean = standard deviation = high threshold = 25 = low threshold = 5 Index i = subsegment Index k = frequency bin