1 / 27

Title

Title. 1 kHz Glitches in S4. Max-Planck-Institut für Gravitationsphysik (Albert-Einstein-Institut). GEO‘s sensitivity for last 20 days of S4. Peak sensitivity ‚drifted‘ during S4 (much more than at other frequencies). BLRMS of H(t) vs glitch rate. Glitchrate 700-2000 Hz.

yon
Download Presentation

Title

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Title 1 kHz Glitches in S4 Max-Planck-Institut für Gravitationsphysik(Albert-Einstein-Institut)

  2. GEO‘s sensitivity for last 20 days of S4 Peak sensitivity ‚drifted‘ during S4 (much more than at other frequencies)

  3. BLRMS of H(t) vs glitch rate Glitchrate 700-2000 Hz H(t) BLRMS 990-1000 Hz Found relation between glitchrate and peak sensitivity.

  4. Spectra for good and bad time Glitches cause additional noise between 400 Hz and 1.3 kHz • Example times: • high glitch rate • 2005-03-22 06:10:00 • low glitch rate • 2005-03-22 13:00:00

  5. Spectrograms of differential EP-P High glitchrate Low glitchrate Glitches present in MI_diff_EP  not an artifact from calibration process

  6. Timeseries of 1kHz Glitches Filtered with bandpass, 950 to 1050 Hz, 6th Order

  7. Noise projections 1 kHz glitches can‘t be explained by our current set of noiseprojections

  8. Gliches vs BLRMS @ 1 kHz

  9. Timedomain distribution

  10. SNR distribution

  11. Number of pixels

  12. Duration of bursts

  13. Bandwidth of burst Probably maximal bandwidth is limited to 400 Hz (strong lines 822 and 1266 Hz)

  14. Time-delay between glitches

  15. Periodicity of the glitches Periodicity of 1.45 mHz Sometimes one can see a periodicity (5-10 times per hour) of the glitchrate

  16. 1.45 mHz in autoalignment signals 1.45 mHz 2*1.45 mHz

  17. 1.45 mHz in MC_AA rotation 2*1.45 mHz 1.45 mHz

  18. Temperatures in the central building 1.45 mHz 2*1.45 mHz 2.3 mHz

  19. 2.3 mHz from air conditioning system AC system usually dominates vertical seismic rms at the central building 2.3 mHz is produced by the outdoor unit of central building‘s airconditioning system

  20. 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. Periodicity of the glitches Periodicity of 2.5 mHz Sometimes one can see a periodicity (5-10 times per hour) of the glitchrate

  22. 2.5 mHz in MPR alignment 2*2.5 mHz 2.5 mHz 3*2.5 mHz 1.45 mHz 2.9 mHz

  23. 2.5 mHz in MC2-AA 2*2.5 mHz 2.5 mHz 3*2.5 mHz

  24. 2.5 mHz in central building‘s temperatures 2.5 mHz 2.3 mHz

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

  26. 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. 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 Index i = subsegment Index k = frequency bin Spectrogram (2-dim set of numbers / pixels) = mean Clustering = standard deviation = high threshold = 25 = low threshold = 5 Triggers

More Related