On multiple classes of gamma-ray bursts, as deduced from autocorrelation functions or bivariate duration/hardness ratio distributions

Details On multiple classes of gamma-ray bursts, as deduced from autocorrelation functions or bivariate duration/hardness ratio distributions On multiple classes of gamma-ray bursts, as deduced from autocorrelation functions or bivariate duration/hardness ratio distributions

Feb 2012

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012mnras.420..405k&link_type=abstract

Monthly Notices of the Royal Astronomical Society, Volume 420, Issue 1, pp. 405-415.

Astronomy and Astrophysics

Astronomy

Methods: Statistical, Gamma-Ray Burst: General

Scientific paper

Autocorrelation functions (ACFs) of 119 gamma-ray bursts (GRBs) monitored by the Burst Alert Telescope (BAT) on Swift are calculated. Contrasting with previous results for smaller numbers of bursts from other missions, the widths of the ACFs are not bimodally distributed. Although the distribution appears slightly asymmetrical, underlying mixtures of distributions can also probably be ruled out. Factors contributing to differences between the results presented here, and those in the literature, may include the differences in energy passbands used, and the superior sensitivity of the BAT instrument (which affects e.g. the redshift distribution of the detected GRB). The second part of the paper is concerned with the fitting of mixtures of bivariate Gaussians to the joint duration/hardness ratio data of 325 GRBs. A careful analysis confirms that a three-component mixture is the statistically most acceptable, but it is shown that the implied marginal distribution of the hardness ratios does not fit the data very well. It is also stressed that mixture components cannot automatically be assumed to represent different classes of GRBs. The point is illustrated by showing two substantially different, but statistically almost equivalent, mixture models for the distribution of 571 BAT-determined GRB durations.

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