Computer Science
Scientific paper
Sep 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005cqgra..22s1303a&link_type=abstract
Classical and Quantum Gravity, Volume 22, Issue 18, pp. S1303-S1309 (2005).
Computer Science
2
Scientific paper
We present the current status of the TAMA300 data analysis using the alternative linear fit (ALF) filter, which is one of the burst filters used to extract burst gravitational wave (GW) signals. Although burst GW analyses of the TAMA300 data have already made progress using an excess-power filter, it is important to use various methods in order to avoid missing burst GW signals, because the precise waveforms are unknown. In the present work, we set the parameters of the ALF filter and then calculated the detection efficiency for GW burst events in our galaxy. We obtained a comparable efficiency to that of the excess-power filter. In addition, we calculated the trigger rate of the TAMA300 data. The result shows that there were so many trigger events which could not be identified as being GW signals or fake events that methods to reduce fake events are required.
Akutsu Tatsuya
Ando Matthew
Hayakawa Hisao
Kanda Nobuyuki
Kuroda Kazuaki
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