NASA NTRS1999
Guided by the Supervised pattern recognition algorithm C4.5, we examine the three gamma-ray burst classes identified by Mukherjee et al. C4.5 provides strong statistical support for this classification. However, with C4.5 and our knowledge of the BATSE instrument, we demonstrate that Class 3 (intermediate fluence, intermediate duration, soft) does not have to be a distinct source population: statistical/systematic errors in measuring burst attributes combined with the well-known hardness/intensity correlation can cause low peak flux Class I (high fluence, long, intermediate hardness) bursts to take on Class 3 characteristics naturally. Based on our hypothesis that the third class is not a distinct one, we provide rules so that future events can be placed in either Class I or Class 2 (low fluence, short, hard). Using classified bursts from the BATSE 4B Catalog, we plot log(N>P) vs. log(P) curves and study spectral features of each class. We find that the two classes are relatively distinct on the basis of spectral parameters, alpha, Beta, and E(sub peak) alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exist for Class I and Class 2 bursts. In the process of studying burst class characteristics, we identify a new bias that affects measurement of burst fluences and durations. Using a simple model of how burst duration can be underestimated, we generally characterize how this fluence duration bias affects BATSE measurements, and demonstrate the type of effect it can have on the BATSE fluence vs. peak flux diagram.