Are blips and koi fish related?
There is some debate on whether Koi fish and blip glitches are part of the same morphology distinguished mainly by loudness or amplitude of the signal. Andy Lundgren has shown that removing calibration lines as part of “data cleaning” makes them look much more similar. A possible explanation of this is that for loud enough glitches, the calibration lines may be causing the Q-transform’s whitening filter to ring at those frequencies, creating the fins on the koi fish. Whitening is a process that removes stationary differences in the loudness of Individual frequencies in the signal.
Fig 1 – Q-transform of typical Koi fish glitch
Fig 2 – Q-transform plot of the same data as above, but with calibration lines removed prior to calculating the Q-transform.
Beverly Berger has suggested that the amplitude of the glitches may be an effective way of discriminating between Koi fish and blips, with Koi fish being louder. To dig into that a little further we plotted the frequency and amplitude of the two glitch types during the 02 run.
Fig 3 – Frequency distribution of blip glitches during 02
Fig 4 – Frequency distribution of Koi fish glitches during 02
The plots of frequency distributions show significant overlap between the two glitch types. Koi fish have a lower peak frequency due to the shape but not enough of a difference to help in classification.
Fig 5 – Amplitude distribution of blip glitches during 02
Fig 6 – Amplitude distribution of Koi fish blitzes during 02
When we look at the amplitude differences between Koi fish and blips we see a pretty sharp dividing line around 10-21, especially during the first 21 weeks. The gap starting at week 23 is a time when there was significant commissioning. There was also a significant increase in range at Livingston around this time.
It is still unclear whether Koi fish are the same as blip glitches, only louder. We also have not been able to identify what exactly causes either glitch. This is just an interesting observation that we thought we would share with our colleagues at Gravity Spy.
Thank you Professor Areeda for sharing this very interesting information with us!
I am a bit confused. The Q value looks the same on the spectrograms and it is marked on all the 4 spectrograms that Q of 5.7
The glitch shape is slightly changing by removal of calibration lines: the “fins” of koi fishes are disappearing after the removal. From this I would assume that the fins are spectrogram interferences (maybe not physical wave interference but spectrogram artifacts).
I would classify both as koi fish. The one which is more similar to a blip is a “baby koi fish”. Unchanged morphology features:
– the shape of the peak. It is very well conserved on many examples.
– the “eyes” of the koi fish, which is happen to be not inside but on the edge of the glitches.
These conserved motives are good discriminating factors between blips and the “baby” koi fishes.
May I ask what were the frequencies of the removed calibration lines?
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Sorry for the delay in getting back to you I’ve been kind of swamped.
The calibration lines move around a bit between runs but for the latest observing and they were at 37.3, 36.7, 331.9, and 1083.7 Hz. The difference in those images are probably the ones below 40 Hz.
I’m not sure what your question about the Q value is? The fact that it is the same in these images makes them easier to compare. Here is a good introduction to these images http://www.ligo.org/scientists/GRB051103/omegagrams.php The other thing about them is that the normalized energy saturates at 25 (arbitrary units) so on extremely loud glitches we look deeper into the background noise.
I would agree with your classifications and think the point of the post is that blips and koi fish may be a continuum of the same phenomenon rather than two distinct types of events.
The gravity spy results that are coming through allow us to study one glitch type over a long period of time. Goal being to understand what is causing the problem and make it go away.
For the record, I am not a professor I am researcher with a computer background working in data visualization and data analysis. Please call me Joe.