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The Q Pipeline search for gravitational-wave bursts with LIGO

This presentation provides an overview of the problem of detecting gravitational wave bursts with limited computational resources. It discusses the parameterization of unmodeled bursts, signal space and template placement, the Q transform, white noise statistics, and preliminary results from LIGO's 5th science run. The significance distribution of Hanford triggers and follow-up of candidate events are also discussed. The outlook includes information on LIGO's sensitivity, ongoing improvements, real-time search algorithms, and development of follow-up tests.

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The Q Pipeline search for gravitational-wave bursts with LIGO

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  1. The Q Pipeline search for gravitational-wave bursts with LIGO Shourov K. Chatterji California Institute of Technology APS Meeting Dallas, Texas April 25, 2006

  2. Overview of the problem • For many potential sources of gravitational-waves (core collapse supernovae, binary black hole mergers, etc.), the waveform is not sufficiently well known to permit matched filtering • Signals are expected to be near the noise floor of the LIGO detectors, which are subject to occasional transient non-stationarities • Searches must be able to keep up with the LIGO data stream using limited computational resources • Simple parameterization to describe unmodeled busts • Efficient algorithm to search data from multiple detectors for statistically significant signal energy that is consistent with the expected properties of gravitational radiation

  3. Parameterization of unmodeled bursts • Characteristic amplitude: • Normalized waveform: • Central time, central frequency, bandwidth and duration: • Time-frequency uncertainty: • Quality factor (aspect ratio):

  4. Signal space and template placement • Multiresolution basis of minimum uncertainty waveforms • Overcomplete basis is desirable for detection • Use matched filtering template placement formalism • Tile the targeted signal space with the minimum number of tiles necessary to ensure agiven worst case energy lossdue to mismatch • Naturally yields multiresolutionbasis that generalizes discretewavelet tiling • Logarithmic in frequency andQ, linear in time

  5. The Q transform • Project onto basis of minimum uncertainty waveforms • Alternative frequency domain formalism (heterodyne detector) allows efficient computation using the fast Fourier transform • Frequency domain bi-square window has near minimum uncertainty with finite frequency domain support

  6. White noise statistics • Whitening the data prior to Q transform analysis greatly simplifies the resulting statistics • The result is equivalent to a matched filter search for minimum uncertainty waveforms in the whitened data • The squared magnitude of Q transform coefficients are chi-squared distributed with 2 degrees of freedom • Define the normalized tile energy • For white noise, Z is just exponentially distributed • Z also corresponds to a matched filter SNR for minimum uncertainty bursts of

  7. Example Q transforms 20% loss, Q of 4 1% loss, Q of 4 20% loss, Q of 8 1% loss, Q of 8

  8. Preliminary look at LIGOs 5th science run • Hanford 2km and 4 km • Analyzed 44.4 days of good quality data • Hanford 2km, 4km, and Livingston 4km • Analyzed 27.9 days of good quality data • Searched in frequency from 90 Hz to 1024 Hz • Searched in Q from 4 to 64 • Thresholds • Single detector normalized energy: 19 (SNR of 6) • Joint normalized energy: 25 (RMS SNR of 7) • No consistency tests applied to candidate events

  9. Preliminary look at LIGOs 5th science run • Background rate estimated by non-physical time shifts • 100 time shift experiments from -50 to +50 seconds • Hanford 2km, 4km, and Livingston 4km • 6 events in time shifted background • ~0 events expected in coincidence • 0 events observed in coincidence • Hanford 2km and 4km • 1231 events in time shifted background • ~12 events expected in coincidence • 78 event observed in coincidence • Due to common environmental disturbances • Consistency tests not yet applied • N events are not seen in the Livingston 4km detector

  10. Significance distribution of Hanford triggers

  11. Follow up of candidate events • This slide will present a QScan of a sample H1H2 event • These QScans are currently running • Based on the QScans, this slide will state “none of them are of likely gravitational-wave origin”

  12. Outlook • LIGO has reached its design sensitivity of an RMS strain of 10-21 integrated over a 100 Hz band and is now collecting one year of triple coincident science data • The LIGO detectors continue to undergo improvements in sensitivity • Search algorithms for unmodeled gravitational-wave bursts are now running in real time on current data • Many of these same tools are also being applied to identify and exclude anomalous detector behavior • Follow-up tests of interesting events, simulated signals, and detector anomalies are currently under development • Tests for consistency of candidate events in multiple detectors are currently under development

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