1. Burst Figure of Merit Julien Sylvestre LSC Meeting, March 2004
LIGO Laboratory

2. Requirements Real time One number Orthogonal to other FOMs Accurate
lag data acquisition by less then 5 minutes
One number
Orthogonal to other FOMs
Accurate
Correlates well with our efficiency and background
LIGO Laboratory

3. Proposals:
Floating SNR cut
End-to-end analysis
LIGO Laboratory

4. Floating SNR cut Process data segments with an ETG every T seconds
For each segment, apply a SNR cut so that only N events survive
FOM = SNR cut
Large glitches affect the FOM
Small glitches don’t affect the FOM much
For a given signal model, and a calibrated spectrum, get hrss, range, etc.
Ran for a month during S3
LIGO Laboratory

5. End-to-End analysis Inject a (few) waveform(s), process with ETG
Do coincidence between all IFOs (optional)
Measure background
FOM = sqrt(background) / efficiency
Requires real-time calibration information
Model dependent: short/long bursts, frequency range, etc.
Real-time inter-site coincidences demonstrated during S2
LIGO Laboratory

6. Orthogonality L1, S2 playground 130-400 Hz 300s segment
100 injections per
amplitude
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7. Correlation between burst rate and inspiral FOM
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8. Correlations Inspiral range hrss SG153 hrss SG235 hrss SG361
hrss G0.001
Burst rate
-0.64
0.52
0.59
0.56
0.60
-0.80
-0.86
-0.78
-0.75
0.41
0.85 1
0.64
Sqrt(bac. rate) / (hrss SG361)
0.68
-0.53
-0.63
(decorrelated)
0.02
-0.07
-0.14
-0.16
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9. Conclusion Reasonably easy to define and implement a burst FOM
Key question #1: what new information is this FOM generating?
Key question #2: how good is this FOM at predicting the quality of the burst analysis?
LIGO Laboratory