Gamma-ray burst class properties

Guided by the supervised pattern recognition algorithm C4.5 developed by Qu inlan in 1986, we examine the three gamma-ray burst classes identified by M ukherjee et al. in 1998. C4.5 provides strong statistical support for this classification. However, with C4.5 and our knowledge of the BATSE instrumen t? we demonstrate that class 3 (intermediate fluence, intermediate duration , soft) does not have to be a distinct source population: statistical/syste matic errors in measuring burst attributes combined with the well-known har dness/intensity correlation can cause low peak flux class 1 thigh fluence, long, intermediate hardness) bursts to take on class 3 characteristics natu rally. 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 1 or c lass 2 (low fluence, short, hard). We find that the two classes are relativ ely distinct on the basis of Band's work in 1993 on spectral parameters alp ha, beta, and E-peak alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exis t for class 1 and class 2 bursts. In the process of studying burst class ch aracteristics, we identify a new bias affecting burst fluence and duration measurements. Using a simple model of how burst duration can be underestima ted, we show how this fluence duration bias can affect BATSE measurements a nd demonstrate the type of effect it can have on the BATSE fluence versus p eak flux diagram.