background estimation in searches for binary inspiral
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Background estimation in searches for binary inspiral Patrick Brady - PowerPoint PPT Presentation

Background estimation in searches for binary inspiral Patrick Brady Inspiral Working Group LIGO Scientific Collaboration G030637-00-Z Inspiral search pipeline Data Quality cuts applied up front Analyze only science mode data


  1. Background estimation in searches for binary inspiral Patrick Brady Inspiral Working Group LIGO Scientific Collaboration G030637-00-Z

  2. Inspiral search pipeline • Data Quality cuts applied up front » Analyze only science mode data • Multi-interferometer follow up on coincident triggers. » ( Talk by Bose ) • Single interferometer vetoes applied to triggers from each interferometer » ( Talk by Christensen and Shawhan ) • Background Estimation » Time slide Hanford data relative to Livingston data G030637-00-Z 11/10/2003 GWDAW -- 1 2

  3. Coincidence criteria • Triggers from Livingston are used to search the corresponding Hanford data • Check for coincidence between the Livingston and Hanford triggers. • The coincidence algorithm was: » 1. Triggers must be coincident in time to within 11 ms. » 2. Each mass parameter in the template must be the same to within 0.03 solar masses. » 3. Compare distances measured at Livingston (D L ) and Hanford (D H ) G030637-00-Z 11/10/2003 GWDAW -- 3

  4. Tuning the amplitude cut • Errors in distance estimates expected to decrease with Missed injections in coincidence increasing SNR |D L - D H |/D L < ε / ρ H + κ ε and κ tunable constants • Relax amplitude cut to allow detection of these Milky Way events D H /D L G030637-00-Z 11/10/2003 GWDAW -- 4

  5. Time-lag results: preliminary results using small bank LLO triggers in coincidence with LHO Take a closer look at these candidates Livingston SNR LHO triggers in coincidence with LLO G030637-00-Z 11/10/2003 GWDAW -- 5 Hanford SNR

  6. Time-lag analysis: SNR in each detector Coherent two detector SNR=10 Hanford SNR Large SNR in Livingston coincident with low SNR at Hanford Livingston SNR G030637-00-Z 11/10/2003 GWDAW -- 6

  7. Time-lag analysis: triggers versus injections Simulated injections of binary inspirals in Andromeda Raise SNR threshold in Hanford to 6 Hanford SNR Livingston SNR G030637-00-Z 11/10/2003 GWDAW -- 7

  8. Time-lag analysis: full bank & adjusted thresholds No. of distinct candidates after 1 second clustering Two out of 18 time-lags have coincidence in templates of same mass G030637-00-Z 11/10/2003 GWDAW -- 8

  9. Time-lag analysis: full bank & adjusted thresholds G030637-00-Z 11/10/2003 GWDAW -- 9

  10. Concluding remarks • Where to next: » Complete ~100 time-shifts on playground data » Check for problems with background estimation using time-shifts » Run time-shift analysis on all data to be used in search – determine network SNR threshold – compare to extrapolation from playground • Search for binary inspiral » Use background estimate from time-shifts on full data set » Search for candidate events » Determine rate limit based on efficiency, background, and number of detections G030637-00-Z 11/10/2003 GWDAW -- 10

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