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TAMA binary inspiral event search

TAMA binary inspiral event search. Hideyuki Tagoshi (Osaka Univ., Japan). 3rd TAMA symposium, ICRR, 2/6/2003. Coalescing compact binaries. Neutron stars Black holes. Inspiral phase of coalescing compact binaries are main target because

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TAMA binary inspiral event search

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  1. TAMA binary inspiral event search Hideyuki Tagoshi (Osaka Univ., Japan) 3rd TAMA symposium, ICRR, 2/6/2003

  2. Coalescing compact binaries Neutron stars Black holes Inspiral phase of coalescing compact binaries are main target because Expected event rate of NS-NS merger: a few within 200Mpc /year Well known waveform, etc. Possibility of MACHO black holes

  3. TAMA Binary inspiral search • Neutron star binary search • TAMA-LISM coincident event search for mass range (onestep search) • Lower mass • Higher mass

  4. Matched filter Post-Newtonian approximation • Detector outputs: ：　known gravitational waveform (template) ： noise. • Outputs of matched filter: • noise spectrum density • signal to noise ratio • Matched filtering is the process to find optimal parameters which realize

  5. Event list 52 sec Matched filtering analysis t Read data FFT of data Apply transfer function Conversion to stain equivalent data Evaluate noise spectrum near the data

  6. TAMA events and Galactic event Test signals selection will produce loss of strong S/N events TAMA events

  7. Search Result TAMA DT6

  8. Log10[Number of events]

  9. Upper limit to the Galactic event rate • Ｎ：　Upper limit to the average number of events • over certain threshold • Ｔ：　Length of data [hours] • :Detection efficiency

  10. Galactic event simulation We perform Galactic event simulation to estimate detection efficiency Assume binary neutron stars distribution in our Galaxy Mass : distribute uniformly between • Give a time during DT6 • Determine mass, position, inclination angle, phase by random numbers • Give a test signal into real data • Search • Make event lists and estimate detection efficiency

  11. Galactic event detection efficiency

  12. Upper limit to the event rate: Poisson statistics • Threshold ( ) • Expected number of fake events over threshold：Nbg=0.1 • Observed number of events over threshold: Nobs=0 • Assuming Poisson distribution for the number of real/fake events • over the threshold, • we obtain upper limit to the expected number of real events from N=2.3(C.L.=90%)

  13. Upper limit to the Galactic event rate • threshold=16 (～S/N=11) • (fake event rate=0.8/year) • Efficiency • We also obtain upper limit to the average number of events over threshold by standard Poisson statistics analysis • N=2.3(C.L.=90%) • Observation time T＝1039 hours c.f.Caltech 40m : 0.5/hour(C.L.=90%) Allen et al. Phys. Rev. Lett. 83, 1498 (1999).

  14. DT7 analysis TAMA DT7: 2002.8.31 ～ 2002.9.2 Best Sensitivity:

  15. DT7 event lists 23.7 hours data These results will be used for TAMA-LIGO coincidence analysis.

  16. chi square Divide frequency region into bins. Test whether the contribution to from each bins agree with that expected from chirp signal

  17. Variation of Noise power (1 minute average) TAMA DT6 all 8/1～9/20/2001 [1.09minutes]

  18. Variation of Noise power (1 minute average) LISM DT6 9/3 ～9/17/2001 [1.09minutes]

  19. TAMA data analysis activity • Binary inspiral search : one step search (Tagoshi, Tatsumi,Takahashi) • TAMA-LISM coincidence • (Takahashi,Tagoshi,Tatsumi) • two step search (Tagoshi, Tanaka) • Binary inspiral search using Wavelet: (Kanda) • Continuous wave from known pulsar:(Soida, Ando) • Burst wave search: (Ando) • Noise veto analysis:(Kanda) • Calibration: (Tatsumi, Telada,…) • Interferometer online diagnostic: (Ando,…) • BH ringdown search, Stochastic background search, etc. will be done. • Two new post-docs (Tsunesasa(NAOJ),Nakano(Osaka))

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