1. LIGO-G070411-00-Z Searching for gravitational wave bursts with the new global detector network Shourov K. Chatterji INFN Sezioni di Roma / Caltech LIGO Laboratory for the LIGO Scientific and Virgo Collaborations 7 th Eduardo Amaldi Conference on Gravitational Waves 2007 July 8-14 Sydney, Australia

2. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-142 Abstract

3. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-143 Overview Benefits of joint data analysis Agreement on joint data analysis Previous studies based on coincidence methods Investigations with simulated data Current investigations with real data Coherent methods for joint data analysis Special case of collocated detectors General case of multiple non-aligned detectors Maximum likelihood statistics Null stream consistency tests Source reconstruction Hierarchical search approach Conclusions

4. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-144 Benefits of a global network Improved sky coverage Less likely that event occurs in null of detector network Improved duty cycle More likely that at least one detector observes an event

5. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-145 Benefits of a global network Increased signal to noise ratio Coherently sum signals from multiple detectors Improved detection confidence Multi-detector coincidence greatly reduces false rate Coherent consistency tests can differentiate between gravitational-wave signals and instrumental glitches Improved source reconstruction “Inverse problem” requires three non-aligned detectors Provides sky position and both polarizations of waveform Permits comparison with theory This is where the science is! Shared best practices Learn from each other’s approaches

6. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-146 Agreement on joint data analysis Recognizing the benefits of joint data analysis, the LIGO Scientific and Virgo collaborations have entered into an agreement to jointly analyze data from the GEO, LIGO, and Virgo detectors Sharing of data started in May 2007 when Virgo commenced its first long science run in coordination with LIGO’s fifth science run A joint run plan committee is coordinating detector operation and commissioning schedules to improve the prospects for detection Joint data analysis meetings are already taking place Joint data analysis exercises with simulated and small amounts of real data have already been performed for the inspiral, burst, and stochastic analysis

7. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-147 Project 2b ~72 hours of coincident data from the G1, H1, H2, L1, and V1 detectors from September 2006 (LIGO’s fifth science run and Virgo’s first weekly science run) Data shifted in time by a secret amount Perform “end to end” analysis using one of the methods Produce upper limits for a variety of simulated burst signals Study coherent methods Identify options and issues for the upcoming joint analysis 1.2 days 1.4 days 1.89 days 2.1 days 2.2 days 1.4 days 1.8 days H1 V1 L1

8. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-148 Coincident analysis Applied the excess power search algorithm Searches for statistically significant signals using a time- frequency decomposition of the data Tests for coincident events between multiple detectors Searched from 800 to 2000 Hz

9. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-149 Pairwise coincident sensitivity Based on previous investigations, we study the union of all pairwise coincident triggers The detection threshold in each detector was set to maximize detection efficiency for all simulated waveforms at a false event rate of 1 uHz. The resulting efficiencies are compared with the efficiency of using only the two 4km LIGO detectors. Preliminary results

10. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1410 Preliminary sensitivities

11. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1411 Coherent analysis coherent sum N-2 dimensional null space detector data coherent null 2 dimensional signal space Coherent sum: Find linear combinations of detector data that maximize signal to noise ratio Null sum: Linear combinations of detector data that cancel the signal provide useful consistency tests. data = response x signal + noise X = F h + n Naturally handles arbitrary networks of detectors

12. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1412 Coherent consistency tests  2 / DOF consistency with a GWB as a function of direction for a simulated supernova (~1 kpc) Interference fringes from combining signal in two detectors. True source location:  intersection of fringes  2 / DOF ~ 1 GWB: Dimmelmeier et al. A1B3G3 waveform, Astron. Astrophys. 393 523 (2002), SNR = 20 Network: H1-L1-Virgo, design sensitivity Coherent methods also off the possibility of consistency tests Test null stream for consistency with noise over sky

13. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1413 Example consistency sky maps Simulated gravitational-wave burst Simulated coincident glitch

14. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1414 Source position recovery Given a statistically significant and consistent signal What direction on the sky maximizes the coherent sum? What direction on the sky minimizes the null stream? Sky position estimates typically fall along rings of constant time delay between sites, leading to poor direction. Other statistics or image processing techniques may be needed source location Null energy E null varies slowly along rings of constant time delay with respect to any detector pair. Noise fluctuations often move minimum away from source location (pointing error)

15. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1415 Coherent sky position recovery example Comparison of sky position recovery by Coherent WaveBurst algorithm for LIGO only and LIGO/GEO/Virgo networks. H1xL1 L1xH1xH2xV1xG1 WILL BE REPLACED WITH SIMULATED DATA SKY POSITION RECOVERY EXAMPLE USING XPIPELINE APPROACH

16. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1416 Timing based recovery of sky position 1 ms Gaussian signals recovered within ~1 degree of true position using Gaussian matched filter and timing based recovery of position Rings of constant time of arrival delay between detectors Plane of detectors Source location Mirror image source location

17. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1417 Waveform recovery Given a statistically significant and consistent signal and a best guess sky position Solve the matrix equation x = Fh + n for the waveforms h Find the psuedo-inverse R such that RF = I Network: H1-L1-GEO GWB: Zwerger-Muller A4B1G4, SNR=40 [Astron. Astrophys. 320 209 (1997)] Recovered signal (blue) is a noisy, band-passed version of simulated GWB signal (red) Injected GWB signal has h x = 0. Recovered h x (green) is just noise.

18. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1418 Summary Coincident and coherent analysis tools are now available to take advantage of data from networks of detectors The union of pairwise coincident triggers from the LIGO/Virgo network provides an improvement in detection efficiency and coverage over the LIGO only network Coherent methods naturally handle arbitrary networks of detectors and provide increased detection confidence, consistency tests, and parameter estimation. Coincident and coherent analysis methods complement eachother and can be used as part of a hierarchical search We are ready to start analyzing joint GEO, LIGO, and Virgo data

19. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1419 Outlook Current sensitivity of the LIGO and Virgo detectors

20. LIGO-G070411-00-Z End

21. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1421 Initial joint working group Need to plan for joint analysis as soon as possible First meeting held in June 2004 Investigations using simulated detector noise Develop common language to describe searches Learn from and gain confidence in search algorithms Demonstrate ability to analyze each other’s data Confront different sample frequencies, file formats, etc. Quantify the benefit of the LIGO/Virgo network Investigations using real detector noise Learn to handle data quality and veto information Confront non-ideal behavior of real detectors Identify options for future joint analysis

22. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1422 Project 1A 3 hours of simulated H1 and V1 detector noise A variety of simulated waveforms: Binary neutron star inspirals Unmodeled Bursts: Core-collapse supernovae Gaussians Sinusoidal Gaussians Applied a variety of LSC and Virgo search algorithms Characterized and compared search algorithm performance Burst and inspiral results presented at GWDAW 9 and published in corresponding conference proceedings Burst: Class. Quant. Grav. 22, S1293 (2005)Class. Quant. Grav. 22, S1293 (2005) Inspiral: Class. Quant. Grav. 22, S1149 (2005)Class. Quant. Grav. 22, S1149 (2005)

23. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1423 Project 1A burst results

24. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1424 Project 1B 24 hours of simulated triple coincident (H1, L1, and V1) data Injection populations of simulated waveforms Binary neutron star inspirals from M87 and NGC 6744 Supernovae in the direction of the galactic center Demonstrated benefit of union of two detector networks Demonstrated sky position reconstruction and astrophysical parameter estimation Joint burst and inspiral results presented at Amaldi 6 and published in corresponding conference proceedings J. Phys. Conf. Ser. 32, 212 (2006)

25. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1425 Project 1b results For coincident searches, union of double coincident detector networks provides improved performance Burst results for simulated supernovae in the direction of the galactic center at a 1  Hz false rate: Inspiral results for simulated signals from M87 and NGC 6744 at an SNR threshold of 6:

26. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1426 Timing based recovery of sky position 1 ms Gaussian signals recovered within ~1 degree of true position using Gaussian matched filter and timing based recovery of position Rings of constant time of arrival delay between detectors Plane of detectors Source location Mirror image source location

27. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1427 Project 1 results Comprehensive papers describing work on simulated data Expand on previous work incorporating lessons learned Burst: arXiV:gr-qc/0701026arXiV:gr-qc/0701026 Investigate robustness over large signal space Investigate intersection and union of algorithms Inspiral: arXiV:gr-qc/0701027arXiV:gr-qc/0701027 Detailed comparison of analyses pipelines Bayesian estimation of source parameters

28. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1428 Project 2a First exchange of real data occurred on 2006 June 15 ~3 hours of non-coincident G1, H1, and V1 data including: Periods of lock loss Periods of good and bad data quality Hardware injections of burst and inspiral waveforms Data quality and veto segment information also exchanged Applied LSC and Virgo search algorithms Results shared at a working group meeting on 2006 June 23-24 in Orsay, France

29. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1429 Project 2b ~72 hours of coincident data from the G1, H1, H2, L1, and V1 detectors from September 2006 (LIGO’s fifth science run and Virgo’s first weekly science run) Data shifted in time by a secret amount Perform “end to end” analysis using one of the methods Produce upper limits for a variety of simulated burst signals Study coherent methods Identify options and issues for the upcoming joint analysis Results to be presented at Amaldi7 in Sydney, Australia

30. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1430 Coincident and coherent analysis Coincident methods Test for time and/or frequency coincidence between detectors Performance constrained by least sensitive detector Difficult to select detector dependent significant thresholds for optimal performance Coherent methods Test linear combinations of detector data based on: Frequency dependent sensitivity of each detector Expected response of each detector to gravitational waves from a particular direction on the sky Naturally handles arbitrary numbers of detectors Naturally handles detectors with different sensitivities Three different applications of coherent methods: 1.Event detection 2.Consistency testing 3.Source reconstruction

31. LIGO-G070411-00-Z 7th Amaldi Conference, Sydney, Australia, 2007 July 8-1431 General case of non-aligned detectors Y. Gursel & M. Tinto PRD 40 3884 (1989) “Near Optimal Solution to the Inverse Problem for GWBs”. Full solution requires at least three non-aligned detectors First solution of the problem for the three detector case Procedure: Use a linear combination of time shifted signals from two detectors to predict the signal in the third detector For each direction on the sky, compute the prediction error Find the direction on the sky where the prediction error is minimized Yields best fit sky position Also yields both polarizations of gravitational waveforms This is equivalent to the maximum likelihood approach