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Search for inspiraling neutron star binaries using TAMA300 data

Search for inspiraling neutron star binaries using TAMA300 data. Hideyuki Tagoshi on behalf of the TAMA collaboration. Outline. I will describe the revised analysis of the binary neutron star search using TAMA300 data. The data we use is TAMA DT6, DT8, and DT9 data.

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Search for inspiraling neutron star binaries using TAMA300 data

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  1. Search for inspiraling neutron star binaries using TAMA300 data Hideyuki Tagoshi on behalf of the TAMA collaboration GWDAW10, UTB, Dec. 14 - 17, 2005

  2. Outline • I will describe the revised analysis of the binary neutron star search using TAMA300 data. • The data we use is TAMA DT6, DT8, and DT9 data. • Mass range: 1-3M_solar (for each member star) GWDAW10, UTB, Dec. 14 - 17, 2005

  3. Data taking run (1)- Observation runs - • TAMA observation runs This presentation GWDAW10, UTB, Dec. 14 - 17, 2005

  4. Data taking run (2)- Observable range - Observable distance for inspiraling binaries (SNR=10, optimal direction and polarization) 1.4 Mo binary inspirals DT6: 33kpc DT8: 42kpc DT9: 72kpc (～30kpc on average) DT6 DT9 DT8 Now, TAMA300 covers most part of our Galaxy GWDAW10, UTB, Dec. 14 - 17, 2005

  5. Revised analysis • Difference from the analysis so far • DT6: mass range 1-2M_solar (PRD70,042003(‘04)) • => 1-3M_solar • DT8: In the previous analysis, calibration data was not taken into account properly, due to the error of file format. We have redone the analysis. • (This was applied to LIGO-TAMA S2-DT8 inspiral analysis too.) • DT9: new results (initial results were reported at Amaldi6) • Systematic error is estimated. GWDAW10, UTB, Dec. 14 - 17, 2005

  6. Matched filtering • Detector outputs: h(t) ：　known gravitational waveform (template) n(t) ： noise • Matched filter : : one sided noise power spectrum density Parameters (mass, coalescence time, …) are not known a priori. We search the parameter space. We need to introduce fake event reduction method because of non-Gaussian noise • Fake event reduction by a measure of the deviation of events from real signal. B. Allen, PRD 71, 062001 (2005) GWDAW10, UTB, Dec. 14 - 17, 2005

  7. Chi square cut- statistic - We use as the statistic to discriminate fake events from true signals. We set a threshold of as where is determined by the false alarm rate. The chi square cut is automatically introduced by these procedures. This statistic can accommodate large signals which could occur due to mismatch between signals and templates. GWDAW10, UTB, Dec. 14 - 17, 2005

  8. Comparison of DT6, DT8 and DT9 efficiency GWDAW10, UTB, Dec. 14 - 17, 2005

  9. DT6, DT8, DT9 trigger lists GWDAW10, UTB, Dec. 14 - 17, 2005

  10. Decision of threshold In the case of Gaussian noise, the square of , or , obeys the F distribution with the degree of freedom (2,2p-2). (p: the number of division of a template in the definition of chi^2. In our case, p=15. ) The probability density function g(z) of z is given by and Thus, in Gaussian case, if we make a log(N(z))-log(z+p-1) plot of the triggers, it becomes linear with slope=-p+1. This suggest that z+p-1 is a more natural variable for the estimation of the false alarm rate than . GWDAW10, UTB, Dec. 14 - 17, 2005

  11. DT9 threshold (1) Looks like linear, although the slope is Different from Gaussian case GWDAW10, UTB, Dec. 14 - 17, 2005

  12. DT9 threshold (2) Threshold = 2.24 for the false alarm rate = 1/yr GWDAW10, UTB, Dec. 14 - 17, 2005

  13. DT8 threshold Threshold = 2.04 for the false alarm rate = 1/yr GWDAW10, UTB, Dec. 14 - 17, 2005

  14. DT6 threshold Threshold = 2.40 for the false alarm rate = 1/yr Unfortunately, the DT6 distribution does not look like linear even in this log-log plot. It is not easy to have accurate estimate of the false alarm rate. Thus, we take a very large value of the threshold to have a conservative upper limit. GWDAW10, UTB, Dec. 14 - 17, 2005

  15. Systematic errors (1) 1. Uncertainty of Galactic simulation Uncertainty of mass distribution Uncertainty of the position of solar system in our Galaxy Error due to finite number of simulation 2. Uncertainty of ρ due to uncertainty of theoretical wave form -10% at most. 3. Calibration error It is not know exactly (although it is expected to be less than 5%). We take a conservative value (+-10%) 4. Uncertainty of threshold (for a given false alarm rate) GWDAW10, UTB, Dec. 14 - 17, 2005

  16. Systematic errors (2) summary preliminary GWDAW10, UTB, Dec. 14 - 17, 2005

  17. Upper limit to the Galactic events • DT8 gives the most stringent upper limitbecause of • Largest length of data • Rather high sensitivity to the Galactic events • Very stable operation (low threshold) • (DT9’s detection probability would have been much larger. However, the first half of DT9 was not very stable. Fake events with large ζ were produced during that period. They degrade the detection probability of DT9.) GWDAW10, UTB, Dec. 14 - 17, 2005

  18. Summary Reanalysis of DT6 and DT8, and the analysis of DT9 to search for the neutron star binaries were done. We will perform the search for • the low mass binary black hole • higher mass bh-bh and/or bh-ns binaries with spin in the near future GWDAW10, UTB, Dec. 14 - 17, 2005

  19. GWDAW10, UTB, Dec. 14 - 17, 2005

  20. DT8 threshold (1) GWDAW10, UTB, Dec. 14 - 17, 2005

  21. DT6 threshold (1) GWDAW10, UTB, Dec. 14 - 17, 2005

  22. DT6, DT8, DT9 trigger lists plot GWDAW10, UTB, Dec. 14 - 17, 2005

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