An analysis of the durations of Swift gamma-ray bursts

Zhang, Zhibin; Choi, Chul-Sung

doi:10.1051/0004-6361:20079210

Cited by 65 publications

(69 citation statements)

References 48 publications

(74 reference statements)

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“…3 connection between the third component and the XRFs might be true.Based on the above analysis in the two dimensional case, one can conclude that the Swift bursts with measured redshift are still better to be classified into two groups, which is in good agreement with some previous works (e.g. Zhang & Choi 2008;Qin & Chen 2013;Tarnopolski 2015;Yang et al 2016) The results of this work can be summarized as.…”

Section: Resultssupporting

confidence: 91%

Two dimensional classification of the Swift/BAT GRBs

Yang¹,

Zhang²,

Jiang³

2016

Astrophys Space Sci

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Using Gaussian Mixture Model and Expectation Maximization algorithm, we have performed a density estimation in the framework of T 90 versus hardness ratio for 296 Swift/BAT GRBs with known redshift. Here, Bayesian Information Criterion has been taken to compare different models. Our investigations show that two instead of three or more Gaussian components are favoured in both the observer and rest frames. Our key findings are consistent with some previous results.

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Section: Resultssupporting

confidence: 91%

Two dimensional classification of the Swift/BAT GRBs

Yang¹,

Zhang²,

Jiang³

2016

Astrophys Space Sci

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“…It was supported (Horváth 2002) with the use of the complete BATSE dataset. Evidence for a third normal component was also found in Swift data Zhang and Choi 2008;Huja et al 2009). BeppoSAX dataset was shown to be in agreement with earlier results regarding the bimodal distribution, and the detection of an intermediate-duration component was established on a lower, compared to BATSE and Swift, significance level due to a less populate sample (Horváth 2009).…”

Section: Introductionsupporting

confidence: 89%

On the limit between short and long GRBs

Tarnopolski

2015

Astrophys Space Sci

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Two classes of GRBs have been identified thus far without doubt and are prescribed to different physical scenarios-NS-NS or NS-BH mergers, and collapse of massive stars, for short and long GRBs, respectively. The existence of two distinct populations was inferred through a bimodal distribution of the observed durations T 90 , and the commonly applied 2 s limit between short and long GRBs was obtained by fitting a parabola between the two peaks in binned data from BATSE 1B. Herein, by means of a maximum likelihood (ML) method a mixture of two Gaussians is fitted to the datasets from BATSE, Swift, BeppoSAX, and Fermi in search for a local minimum that might serve as a new, more proper, limit for the two GRB classes. It is found that Swift and BeppoSAX distributions are unimodal, hence no local minimum is present, Fermi is consistent with the conventional limit, whereas BATSE gives the limit significantly longer (equal to 3.38 ± 0.27 s) than 2 s. These new values change the fractions of short and long GRBs in the samples examined, and imply that the observed T 90 durations are detector dependent, hence no universal limiting value may be applied to all satellites due to their different instrument specifications. Because of this, and due to the strong overlap of the two-Gaussian components, the straightforward association of short GRBs to mergers and long ones to collapsars is ambiguous.

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“…Horváth (1998) and Mukherjee et al (1998) independently discovered a third peak in the duration distribution in the BATSE 3B catalog (Meegan et al 1996), located between the short and long peaks, and the statistical existence of this intermediate class was supported (Horváth 2002) with the use of BATSE 4B data. Evidence for a third component in log T 90 was also found in the Swift data (Horváth et al 2008a,b;Zhang & Choi 2008;Huja et al 2009;Horváth et al 2010). Other datasets, i.e., RHESSI (Řípa et al 2009) and BeppoSAX (Horváth 2009), are both in agreement with earlier results regarding the bimodal distribution, and the detection of a third component was established on a lower significance level (compared to BATSE and Swift) owing to less populated samples.…”

Section: Introductionsupporting

confidence: 83%

Analysis ofFermigamma-ray burst duration distribution

Tarnopolski

2015

A&A

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Context. Two classes of gamma-ray bursts (GRBs), short and long, have been determined without any doubts, and are usually prescribed to different physical scenarios. A third class, intermediate in T 90 durations has been reported in the datasets of BATSE, Swift, RHESSI, and possibly BeppoSAX. The latest release of >1500 GRBs observed by Fermi gives an opportunity to further investigate the duration distribution. Aims. The aim of this paper is to investigate whether a third class is present in the log T 90 distribution, or whether it is described by a bimodal distribution. Methods. A standard χ 2 fitting of a mixture of Gaussians was applied to 25 histograms with different binnings. Results. Different binnings give various values of the fitting parameters, as well as the shape of the fitted curve. Among five statistically significant fits, none is trimodal. Conclusions. Locations of the Gaussian components are in agreement with previous works. However, a trimodal distribution, understood in the sense of having three distinct peaks, is not found for any binning. It is concluded that the duration distribution in the Fermi data is well described by a mixture of three log-normal distributions, but it is intrinsically bimodal, hence no third class is present in the T 90 data of Fermi. It is suggested that the log-normal fit may not be an adequate model.

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An analysis of the durations of Swift gamma-ray bursts

Cited by 65 publications

References 48 publications

Two dimensional classification of the Swift/BAT GRBs

Two dimensional classification of the Swift/BAT GRBs

On the limit between short and long GRBs

Analysis ofFermigamma-ray burst duration distribution

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