1. T.Akutsu, M.Ando, N.Kanda, D.Tatsumi, S.Telada, S.Miyoki, M.Ohashi and TAMA collaboration GWDAW10 UTB Texas 2005 Dec. 13

2. GWDAW10@UTB, Texas 2005 Dec. 13 I. Target Source II. ALF filter III. Flow of analysis IV. Summery  Trigger rate  Detection efficiency  Result

3. GWDAW10@UTB, Texas 2005 Dec. 13 Burst GW signal from Supernovae Explosion  Time duration ~100msec  Spike-like waveform GW root sum square (RSS) amplitude A&A 393 523 (2002) GW RSS amplitude of sources located at 100pc GW RSS amplitude and Detector noise level Simulation signals GW RSS amplitude of sources located at the Galactic center

4. GWDAW10@UTB, Texas 2005 Dec. 13 A slope value of a raw of data (N samples) is used to trigger an event. In this work, window size N = (0.4, 0.6, 0.9) [msec] C.Q.G. 22 (2005) S1303

5. GWDAW10@UTB, Texas 2005 Dec. 13 ALF filter Time scale veto Monitor Veto RAWDATA Filter Output Trigger List Event List window C.Q.G. 20 (2003) S697-S709 Conditioning AC line Violin mode Calibration peak This test is based on  distribution of the filer output.

6. GWDAW10@UTB, Texas 2005 Dec. 13 Trigger rate of DT9 Total 182.9 hours Rejected time by veto 4.4 hours Analysis time 187.3 hours Analysis data DataTaking9 of TAMA300 (Nov.2003-Jan.2004)

7. GWDAW10@UTB, Texas 2005 Dec. 13 Injected signals 26 kinds of signals A&A 393 523 (2002)  Monte Carlo simulation of 26signals We set threshold to be, which corresponds at the level of 0.51 events/day with 90% confidence level. Result of simulation Preliminary

8. GWDAW10@UTB, Texas 2005 Dec. 13 Type I Regular collapse Type II Multiple bounce collapse Type III Rapid collapse Waveform depends on the type of signal.  Simulation result of Each type signal Preliminary

9. GWDAW10@UTB, Texas 2005 Dec. 13  Rate [events/day] with confidence level 90% 0.62 events/day Preliminary Rate

10. GWDAW10@UTB, Texas 2005 Dec. 13 Improvement of data conditioning Adjustment of filter parameters Coincidence analysis for reduction of fake events We implemented the time scale veto and the monitor veto in order to remove fake events Detection efficiency was evaluated by Monte Carlo simulation. As a result, we obtained 0.62 events/day at

11. GWDAW10@UTB, Texas 2005 Dec. 13 Astron.Journal 125 1958 (2003) sky-survey observation Source-distribution model Preliminary antenna pattern sensitivity an event location polarization of a source

12. GWDAW10@UTB, Texas 2005 Dec. 13 C.Q.G. 20 (2003) S697-S709 This test is based on  distribution of the filer output. Stability of the noise level Gaussianity ♣ ♣

13. GWDAW10@UTB, Texas 2005 Dec. 13 small Time scale example small Time scale Amplitude long

14. GWDAW10@UTB, Texas 2005 Dec. 13 Longest time scale signal

15. GWDAW10@UTB, Texas 2005 Dec. 13 Injected signals A&A 393 523 (2002) 26 signals

16. GWDAW10@UTB, Texas 2005 Dec. 13  Rate [events/day] with confidence level 90% 0.62 events/day Preliminary 0.53 events/day 0.73 events/day type1 Type2,3

17. GWDAW10@UTB, Texas 2005 Dec. 13 Astron.Journal 125 1958 (2003) sky-survey observation Source-distribution model Preliminary

18. GWDAW10@UTB, Texas 2005 Dec. 13

19. Reduction ratio by veto

20. GWDAW10@UTB, Texas 2005 Dec. 13 Injected signals 26 kinds signals A&A 393 523 (2002)  Monte Carlo simulation of 26signals Type I Regular collapse Type II Multiple bounce collapse Type III Rapid collapse