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• GlitchPlot

GlitchPlot

This project is for glitch and lock loss study. Also applicable to event validation of GW candidate. You can see the result here.

Original developer: Chihiro Kozakai (production of plots), Hirotaka Yuzurihara (web page).

The latest trigger channel list

4/7~4/20 O3GK

Overview

The main purpose is to study glitches and lock loss by visual inspection. Also, collecting information for glitch database is done through voting form for each glitch event. Using the result, we aim to do noise hunting, glitch characterization, and labeling for machine learning application. Here is slides describing how to use: slides

GlitchPlot uses trigger information provided by Omicron. GlitchPlot does clustering of the triggers and summarize the trigger information for each events based on the Omicron output.

• clustering: If windows of triggers have overlap or no margin, they are regarded as 1 event.

Also, GlitchPlot uses lock loss information based on lock state information of guardian.

For each events, plots for triggered channel and relevant channels are provided on Yuzu Summary. The relevant channels are basically chosen from

• Trigger channel
• Unsafe channels
• Important upstream channels
• Relevant VIS channels
• PEM near the trigger channel sensor

Using Kozapy batch codes, following plots are provided:

• Time series
• Spectrum before trigger and after trigger
• Spectrogram
• Coherencegram with trigger channel
• Q-transform (Under testing)

The parameter for plots are determined based on trigger information. Also, lock state summary around the trigger time is provided.

Specification detail

Trigger clustering

For the trigger clustering method, please refer p3 of slides.

Plot channel list

For the exact channel list for each trigger, please refer $channelname.dat in GlitchPlot github.

Plot parameter

For the exact method for plot parameter determination, please refer plotter.py and condor_jobfile_plotter.sh in GlitchPlot github. The intent and the variable name in the shell script is as follows.

• Time series
  • GPS start time ($gpsstart), end time ($gpsend)
    • The center is the trigger time.
    • Time span is roughly larger one of [4sec, trigger duration * 10]. (Adjusted to fit the spectrogram requirement)
  • Output directory ($outdir)
  • Channel ($chlist[@])
  • Lock state segment bar: flag($lock), guardian channel($lchannel), guardian value($lnumber), segment bar title($llabel)
  • Data file type ($data)
    • Full data is used.
  • If time span is too long, down sample is applied.
• Spectrum
  • List of GPS start time ($gpsstarts30[@]), end time ($gpsend30[@])
    • Trigger time and 2sec before and after the trigger is avoided.
    • About 30 sec is used each before trigger and after trigger spectrum.
    • The length is adusted to the multiple of the FFT length.
  • Output directory ($outdir)
  • Channel ($chlist[@])
  • FFT length ($fft30)
    • 1/band width (Adjusted to the nearest 2^n sec.)
• Spectrogram, coherencegram
  • GPS start time ($gpsstart), end time ($gpsend)
    • The center is the trigger time.
    • Time span is roughly larger one of [4sec, trigger duration * 10].
    • The length is adjusted to be Stride * n
  • Output directory ($outdir)
  • Channel ($chlist[@])
  • Lock state segment bar: flag($lock), guardian channel($lchannel), guardian value($lnumber), segment bar title($llabel)
  • Stride ($stride)
    • To have enough time resolution to see the glitch.
  • FFT length ($fft)
    • stride = FFT length * n
  • With and without whitening (Spectrogram)
• Q-transform (Under testing. GWpy default parameter is used.)
  • GPS start time ($gpsstart), end time ($gpsend)
  • Output directory ($outdir)
  • Channel ($chlist[@])
  • Lock state segment bar: flag($lock), guardian channel($lchannel), guardian value($lnumber), segment bar title($llabel)
• Lock segment summary
  • GPS start time ($gpsstart), end time ($gpsend)
    • Same as time series
  • Output directory ($outdir)
  • Channel ($channel)
  • Trigger time ($gpstime) and duration ($max_duration)
    • Taken from Omicron information

Source code

GlitchPlot github.

Master branch: On Kamioka server, plotter.sh runs by crontab every 15 min. plotter.py is called. it gives clustered Omicron trigger information as a text file. The text files are sent to Kashiwa server by rsync.

kashiwa branch: On Kashiwa sercer, GlitchPlot.sh runs by crontab every 15 min. Using text file sent from Kamioka, condor_jobfile_plotter.sh runs to throw jobs into condor to make plots.

Note for developer

* It is better to use low-latency pipeline result for RRT. CBC and burst pipeline configuration is under constructing. * Top page maybe better to start from the latest date.

Info log

Trigger channel list log

8/15~ (X-arm nightly, only time with K1:MIF-WE_ARE_DOING_NOTHING == 1)

8/10~ (X-arm nightly, only time with K1:MIF-WE_ARE_DOING_NOTHING == 1)

7/25~ (only 0:00~8:00)

7/19~ (only 0:00~8:00)

7/13 (MICH ER)

7/12~ and 7/13 11:30~24:00

7/10~

7/5~7/9 (buggy setting)

6/8 during ER

6/12~7/5

6/7~6/12

Update log

• 8/20 Test version for data analysis pipeline result CBC Burst

• 8/14 Only main channel trigger is used.
• 8/10 For daily run, both glitch and lockloss are monitored during nightly data taking. Trigger list is updated to adapt X-arm configuration.
• 7/24 For daily run, only lock loss events will be monitored.

• 7/19 Glitch events in ER on 7/13 are reprocessed. Yuzu summary

• 7/13 SNR thresholds are optimized ER trigger rate.
• 7/12 Trigger channel is changed for MICH optimized set.
• 7/10 Changed SNR threshold.
• 7/9 Bug fix for SNR threshold lowering.
• 7/5 SNR threshold is lowered during 0am-8am. Instead, daytime events are all rejected.
• 7/5 Missing plot for PEM trigger channel is fixed.
• 7/4 ER events are reprocessed.
• 7/4 Started this wiki.