Statistics
Scientific paper
Dec 1995
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995aas...187.1001n&link_type=abstract
American Astronomical Society, 187th AAS Meeting, #10.01; Bulletin of the American Astronomical Society, Vol. 27, p.1295
Statistics
Scientific paper
We perform a search for time dilation in short (T_90 < 2 s) gamma-ray bursts using the pulse-width and auto-correlation statistics. Both measures avoid the problem of accurate estimation of burst onset and cessation in the presence of relatively large statistical fluctuations in dim bursts. We fit pulses using time-tagged event data (2 mu s resolution). The pulse-fitting algorithm is entirely automatic, employs a Poisson cost function, links information between energy channels, and utilizes the data at original resolution. The latter feature is important since pulses in short bursts can be factors of ~ 10--100 shorter than pulses in long bursts. Peak intensities, also determined in the pulse-fitting process, are converted to peak fluxes using 4-channel detector response matrices. The peak fluxes are used to rank burst brightness. Brightness selection effects are addressed by rendering signal-to-noise levels equal to that of the dimmest bursts in the sample and then exploring the thresholds at which bright and dim bursts drop from the sample. Time-dilation statistics are then generated for surviving bursts grouped by peak flux. We report latest results derived for a sample of ~ 200 short bursts detected by BATSE on the Compton Gamma Ray Observatory.
Bonnell Jerry T.
Nemiroff Robert J.
Norris Jay P.
Scargle Jeffrey D.
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