Presentation is loading. Please wait.

Presentation is loading. Please wait.

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

Similar presentations


Presentation on theme: "TAMA binary inspiral event search Hideyuki Tagoshi (Osaka Univ., Japan) 3rd TAMA symposium, ICRR, 2/6/2003."— Presentation transcript:

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 1.Neutron star binary search 2.TAMA-LISM coincident event search for mass range (onestep search) 3.Lower mass 4.Higher mass

4 Matched filter 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 Post-Newtonian approximation

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

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 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 Mass : distribute uniformly between

11 Galactic event detection efficiency

12 Upper limit to the event rate: Poisson statistics Threshold ( ) Expected number of fake events over threshold : N bg =0.1 Observed number of events over threshold: N obs =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 TAMA DT7: 2002.8.31 ~ 2002.9.2 Best Sensitivity: DT7 analysis

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

16

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

18 [1.09minutes] TAMA DT6 all 8/1 ~ 9/20/2001 Variation of Noise power (1 minute average)

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

20 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)) TAMA data analysis activity


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

Similar presentations


Ads by Google