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Unsupervised pattern recognition algorithms support the existence of three gamma-ray burst classes; Class I (long, large fluence bursts of intermediate spectral hardness), Class II (short, small fluence, hard bursts), and Class III (soft bursts of intermediate durations and fluences). The algorithms surprisingly assign larger membership to Class III than to either of the other two classes. A known systematic bias has been previously used to explain the existence of Class III in terms of Class I; this bias allows the fluences and durations of some bursts to be underestimated (Hakkila et al., ApJ 538, 165, 2000). We show that this bias primarily affects only the longest bursts and cannot explain the bulk of the Class III properties. We resolve the question of Class III existence by demonstrating how samples obtained using standard trigger mechanisms fail to preserve the duration characteristics of small peak flux bursts. Sample incompleteness is thus primarily responsible for the existence of Class III. In order to avoid this incompleteness, we show how a new dual timescale peak flux can be defined in terms of peak flux and fluence. The dual timescale peak flux preserves the duration distribution of faint bursts and correlates better with spectral hardness (and presumably redshift) than either peak flux or fluence. The techniques presented here are generic and have applicability to the studies of other transient events. The results also indicate that pattern recognition algorithms are sensitive to sample completeness; this can influence the study of large astronomical databases such as those found in a Virtual Observatory.
We use ESX, a product of Information Acumen Corporation, to perform unsupervised learning on a data set containing 797 gamma-ray bursts taken from the BATSE 3B catalog. Assuming all attributes to be distributed logNormally, Mukherjee et al. (1998) an
We systematically analyze three GRB samples named as radio-loud, radio-quiet and radio-none afterglows, respectively. It is shown that dichotomy of the radio-loud afterglows is not necessary. Interestingly, we find that the intrinsic durations ($T_{i
We present a catalog of radio afterglow observations of gamma-ray bursts (GRBs) over a 14 year period from 1997 to 2011. Our sample of 304 afterglows consists of 2995 flux density measurements (including upper limits) at frequencies between 0.6 GHz a
A sample of 427 gamma-ray bursts (GRBs), measured by the RHESSI satellite, is studied statistically to determine the number of GRB groups. Previous studies based on the BATSE Catalog and recently on the Swift data claim the existence of an intermedia
Gamma-ray bursts (GRBs) are the most energetic phenomena in the Universe; believed to result from the collapse and subsequent explosion of massive stars. Even though it has profound consequences for our understanding of their nature and selection bia