Gamma-ray burst class properties

被引:97
作者
Hakkila, J [1 ]
Haglin, DJ
Pendleton, GN
Mallozzi, RS
Meegan, CA
Roiger, RJ
机构
[1] Univ Alabama, Dept Phys & Astron, Huntsville, AL 35812 USA
[2] Coll Charleston, Dept Phys & Astron, Charleston, SC 29424 USA
[3] Minnesota State Univ, Dept Phys & Astron, Mankato, MN 56001 USA
[4] Minnesota State Univ, Dept Comp & Informat Sci, Mankato, MN 56001 USA
[5] NASA, George C Marshall Space Flight Ctr, Space Sci Lab, Huntsville, AL 35812 USA
关键词
gamma rays : bursts; methods : analytical; methods : data analysis;
D O I
10.1086/309107
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Guided by the supervised pattern recognition algorithm C4.5 developed by Quinlan in 1986, we examine the three gamma-ray burst classes identified by Mukherjee et al. in 1998. 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 1 thigh 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 1 or class 2 (low fluence, short, hard). We find that the two classes are relatively distinct on the basis of Band's work in 1993 on spectral parameters alpha, beta, and E-peak alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exist for class 1 and class 2 bursts. In the process of studying burst class characteristics, we identify a new bias affecting burst fluence and duration measurements. Using a simple model of how burst duration can be underestimated, we show how this fluence duration bias can affect BATSE measurements and demonstrate the type of effect it can have on the BATSE fluence versus peak flux diagram.
引用
收藏
页码:165 / 180
页数:16
相关论文
共 27 条
[21]  
Pendleton GN, 1998, AIP CONF PROC, P899
[22]  
PENDLETON GN, 2000, UNPUB
[23]  
Quinlan J. R., 1986, Machine Learning, V1, P81, DOI 10.1023/A:1022643204877
[24]  
ROIGER RJ, 2000, IN PRESS P 5 HUNTSV
[25]  
WANG VC, 1997, AIP C P, V384, P106
[26]  
Weinberg S., 1972, Gravitation and cosmology: principles and applications of the general theory of relativity
[27]   AUTOMATED STAR GALAXY CLASSIFICATION FOR DIGITIZED POSS-II [J].
WEIR, N ;
FAYYAD, UM ;
DJORGOVSKI, S .
ASTRONOMICAL JOURNAL, 1995, 109 (06) :2401-2414