1. Results From the Low Threshold, Early S5, All-Sky Burst Search Laura Cadonati for the Burst Group LSC meeting @ MIT November 5, 2006 G060563-00-Z

2. 2 S5 All-Sky Burst Search The standard WaveBurst + CorrPower analysis New features since S4: »New wavelets (sym->Meyer) and data conditioning in WaveBurst »Notch the second harmonic of the violin mode in CorrPower pre-filter »Require a minimal correlation between H1 and L1 (significance>0.1%) »The final threshold is frequency-dependent in  Data type: h(t) frames RDS_C02_LX Analyzed period: »November 17, 2005 to April 3, 2006 (816258800-828104473) Triple-coincidence time before data quality and veto cuts (~10%): »54.4 days »4777.3 days = 13.5 years time slides for tuning »4376.5 days = 12.0 years time slides for background estimate

3. 3 H1H2L1 Simulated waveforms + ΔtΔt Coincidence (time, frequency) Waveform consistency test burst candidate events Filter ++ The Burst All-Sky Pipeline Filter, wavelet TF Filter, wavelet TF Filter, wavelet TF

4. 4 H1H2L1 Simulated waveforms + ΔtΔt Coincidence (time, frequency) Waveform consistency test burst candidate events Filter ++ The Burst All-Sky Pipeline WaveBurst Event Trigger Generator Zg threshold Filter, wavelet TF Filter, wavelet TF Filter, wavelet TF

5. 5 H1H2L1 Simulated waveforms + ΔtΔt Coincidence (time, frequency) Waveform consistency test burst candidate events Filter ++ CorrPower r-statistic test  threshold The Burst All-Sky Pipeline WaveBurst Event Trigger Generator Zg threshold Filter, wavelet TF Filter, wavelet TF Filter, wavelet TF

6. 6 H1H2L1 Simulated waveforms + ΔtΔt Coincidence (time, frequency) Waveform consistency test burst candidate events Filter ++ CorrPower r-statistic test  threshold The Burst All-Sky Pipeline WaveBurst Event Trigger Generator Zg threshold Filter, wavelet TF Filter, wavelet TF Filter, wavelet TF

7. 7 H1H2L1 Simulated waveforms + ΔtΔt Coincidence (time, frequency) Waveform consistency test burst candidate events Filter ++ CorrPower r-statistic test  threshold The Burst All-Sky Pipeline WaveBurst Event Trigger Generator Zg threshold Filter, wavelet TF Filter, wavelet TF Filter, wavelet TF

8. 8 End-Of-Pipeline Cuts H1-H2 consistency cut: »Estimated burst amplitude (h rss ) must be within a factor 2 »Calibrated H1 and H2 must be POSITIVELY correlated H1-L1 minimal correlation »Require  H1L1 > 3 (less than 0.1% probability to get the measured r from uncorrelated noise at L1 and H1) »Missed some simulations (unfavorable antenna pattern for one site or different waveforms at LLO and LHO) but 50% and 90% detection efficiency only affected by a few percents Data quality cuts Event-by-event veto using transients in auxiliary channels Fixed Zg threshold Frequency-dependent threshold on 

9. 9 Amplitude Consistency Simulations: SineGaussians Q=8.9,3 Before any cut After H1-H2 and H1-L1 cuts Accidentals from time-slides

10. 10 Data Quality: Category 1 Data quality flags used to define analysis segments. Data flagged by Category 1 is not even looked at by this analysis (we verify in other ways that they are not due to a very loud GW event) IFOFlagDescription H1,H2,L1OUT_OF_LOCK L1AS_TRIGGER H1,H2,L1INJECTION H1,H2,L1 CALIB_DROPOUT_1SAMPLE CALIB_DROPOUT_1SEC CALIB_DROPOUT_AWG_STUCK CALIB_GLITCH_ZG the calibration system injects glitches in DARM_ERR. L1CALIB_DROPOUT_BN H1,H2,L1 PD_OVERFLOW MASTER_OVERFLOW_LSC some part the length sensing and control system saturated, making it nonlinear and/or feeding back a glitch into the interferometer

11. 11 Data Quality: Category 2 “Unconditional” data quality flags, used for upper limit and detection. We know data flagged by Category 2 is not good, with loud noise transients (single-IFO or time-slide triple coincidence) Dead Time = 2.2% Veto efficiency:  > 2 : 5.6%  > 3 : 6.5%  > 4 : 7.8%  > 5 : 27.6% ASI_CORR_OVERFLOW (1.8% D.T.) MASTER_OVERFLOW_ASC MASTER_OVERFLOW_SUS_RM CALIB_BAD_COEFF OSEM_GLITCH (H2 only) MMT3_OPTLEVER (H2 only) POWMAG LHO Power glitches  = r-statistic test combined significance for the linear correlation of detector pairs  =(  H1H2 +  H1L1 +  H2L1 )/3

12. 12 Data Quality: Category 3 Data quality flags used for upper limit only. We do look for detection candidates in Category 3 data, but we need to take the DQ into account in establishing the confidence of the event  = r-statistic test combined significance for the linear correlation of detector pairs  =(  H1H2 +  H1L1 +  H2L1 )/3 seismic flags LIGHTDIP PRELOCKLOSS_60sec L1:TRAIN_LIKELY (2.4% DeadTime) H1:SEISMIC_EY_99PCTL_3_10Hz Dead Time = 6.1% Veto efficiency:  > 2 : 11%  > 3 : 13%  > 4 : 14%  > 5 : 48% vetoed by Cat2+Cat3 vetoed by Cat2+Cat3

13. 13 Event-By-Event AuxChan Veto Decided a priori, based on efficiency at vetoing loud single- interferometer triggers found by KleineWelle »LLO: 60 environmental and 45 interferometric »LHO: 29 environmental and 44 (H1) / 44 (H2) interferometric »Deadtime 1.6% We are still producing histograms of events after these vetos are applied, BUT the event at highest  after Category2+Category3 is vetoed  histogram in the tuning set After Category 2 and Category 3 data quality flags and H1-H2, H1-L1 cuts

14. 14 Frequency-Dependent Threshold After Category 2 DQ flags After Category 2 and 3 DQ flags Empirically chosen, frequency-dependent threshold ~1/(f-64Hz) in 100-300Hz, 4 at high frequency, 6 at low frequency Target rate of accidental coincidences: << 1 per analysis period Expected: 0.06 in early S5, 0.4/year

15. 15 Detection Efficiency Sine-Gaussians Q=9 S4 S5 ---------------------------------- 70Hz 48 40 100Hz 14 12 153Hz 12 6.2 235Hz 14 6.6 361Hz 22 11 554Hz 26 12 849Hz 39 19 1053Hz 55 24 h rss values with 50% detection efficiency, in units of 10 -22 /sqrt(Hz) White-Noise Bursts 10ms duration Fc [Hz] BW [Hz] S4 S5 ---------------------------------------------- 1000 1000 84 36 1000 100 47 21 100 100 11 6.1 250 100 15 7.4 Gaussians Duration S4 S5 ------------------------------ 0.05ms 54 28 0.1ms 38 20 1.0ms 18 10 4.0ms 70 71

16. Are we there yet? Time to open the box on early S5 …and explore zero-lag triggers with a different set of 100 LHO-LLO time-slides to estimate accidental rates

17. 17 Before Any Cuts

18. 18 After Analysis and DQ Cuts

19. 19 Before Any Cuts

20. 20 After Analysis and DQ Cuts

21. 21 Rate vs Time Accidental triggers rate, sum of 100 LHO-LLO time slides All WaveBurst triggers After H1H2, H1L1 cuts and Category 2+3 DQ flags

22. 22 From S1 to S5 S1 S2 S4 Early S5 Sine-Gaussian waveforms, Q=8.9

23. 23 NO Detection Candidates Look after only category 2 applied: Releasing the category 3 DQ flags does not uncover any candidate

24. 24 Summary We completed tuning and open the box on the early S5, low threshold WaveBurst+CorrPower burst analysis. »Period covered: November 17 to April 3 There are NO GW candidates The detection efficiency is ~2 times better than in S4 except at low frequencies (below 100Hz), where thresholds were cranked up to address seismic-induced outliers. Upper limit exclusion curves improved as expected with lower noise and longer lifetime than S4.