THE GAMMA-RAY BURST CATALOG OBTAINED WITH THE GAMMA-RAY BURST MONITOR ABOARD
                    <i>BeppoSAX</i>

Frontera, F.; Guidorzi, C.; Montanari, E.; Rossi, Fabrice; Costa, E.; Feroci, M.; Calura, F.; Rapisarda, M.; Amati, L.; Carturan, D.; Cinti, M. R.; Fiume, D. Dal; Nicastro, L.; Orlandini, M.

doi:10.1088/0067-0049/180/1/192

Cited by 76 publications

(78 citation statements)

References 27 publications

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“…23 Similarly, the start and end time of T 50 is defined as the times when the accumulated light curve reaches 25% and 75%. These definitions for T 90 and T 50 are commonly adopted for quantifying burst durations by other teams, including BATSE, BeppoSAX, and Fermi (Koshut et al 1996;Paciesas et al 1999;Frontera et al 2009;von Kienlin et al 2014). In this paper, we follow the convention and use the T 90 =2 s as the separation between the long and short GRBs categories (Kouveliotou et al 1993).…”

Section: Standard Analysismentioning

confidence: 99%

The Third Swift Burst Alert Telescope Gamma-Ray Burst Catalog

Lien

Sakamoto

Barthelmy

et al. 2016

ApJ

289

320

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To date, the Burst Alert Telescope (BAT) onboard Swift has detected ∼1000 gamma-ray bursts (GRBs), of which ∼360 GRBs have redshift measurements, ranging from z=0.03 to z=9.38. We present the analyses of the BATdetected GRBs for the past ∼11 years up through GRB151027B. We report summaries of both the temporal and spectral analyses of the GRB characteristics using event data (i.e., data for each photon within approximately 250 s before and 950 s after the BAT trigger time), and discuss the instrumental sensitivity and selection effects of GRB detections. We also explore the GRB properties with redshift when possible. The result summaries and data products are available at http://swift.gsfc.nasa.gov/results/batgrbcat/index.html. In addition, we perform searches for GRB emissions before or after the event data using the BAT survey data. We estimate the false detection rate to be only one false detection in this sample. There are 15 ultra-long GRBs (∼2% of the BAT GRBs) in this search with confirmed emission beyond ∼1000 s of event data, and only two GRBs (GRB100316D and GRB101024A) with detections in the survey data prior to the starting of event data.

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Section: Standard Analysismentioning

confidence: 99%

The Third Swift Burst Alert Telescope Gamma-Ray Burst Catalog

Lien

Sakamoto

Barthelmy

et al. 2016

ApJ

289

320

View full text Add to dashboard Cite

show abstract

“…Herein, we consider the GRB datasets available from BATSE 1 4B catalog (Paciesas et al 1999), Swift 2 (Lien et al 2016), Fermi-GBM 3 (Narayana Bhat et al 2016 and BeppoSAX 4 (Frontera et al 2009). The number of GRBs analyzed for the model comparison are 2036 from BATSE, 927 from Swift, 1901 from Fermi, and 1003 from BeppoSAX.…”

Section: Datasetsmentioning

confidence: 99%

“…The BeppoSAX catalogue (Frontera et al 2009) has a total of 1003 GRBs detected between 1996 and 2001. Table 2.…”

Section: Bepposaxmentioning

confidence: 99%

Classification of gamma-ray burst durations using robust model-comparison techniques

Kulkarni

Desai

2017

Astrophys Space Sci

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Gamma-Ray Bursts (GRBs) have been conventionally bifurcated into two distinct categories dubbed "short" and "long", depending on whether their durations are less than or greater than two seconds respectively. However, many authors have pointed to the existence of a third class of GRBs with mean durations intermediate between the short and long GRBs. Here, we apply multiple model comparison techniques to verify these claims. For each category, we obtain the best-fit parameters by maximizing a likelihood function based on a weighted superposition of two (or three) lognormal distributions. We then do model-comparison between each of these hypotheses by comparing the chi-square probabilities, Akaike Information criterion (AIC), and Bayesian Information criterion (BIC). We uniformly apply these techniques to GRBs from Swift (both observer and intrinsic frame), BATSE, BeppoSAX, and Fermi-GBM. We find that the Swift GRB distributions (in the observer frame) for the entire dataset favor three categories at about 2.4σ from difference in chi-squares, and show decisive evidence in favor of three components using both AIC and BIC. However, when the same analysis is done for the subset of Swift GRBs with measured redshifts, two components are favored with marginal significance. For all the other datasets, evidence for three components is either very marginal or disfavored.

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“…Likewise, for the BeppoSAX/GRBM sample we started from the GRB catalogue (Frontera et al 2009) by selecting the GRBs covered with 7.8 ms resolution, available in the 40-700 keV energy band only for those that triggered the GRBM on-board logic. In one case (010222) the time profile was not entirely covered with high resolution; by comparing the high-resolution PDS with the one extracted over the full profile at lower (1 s) resolution, no remarkable difference was noted in the common frequency range, so we used the high-resolution PDS because of the better sampled high-frequency tail.…”

Section: Data From Past Experimentsmentioning

confidence: 99%

Correlation between peak energy and Fourier power density spectrum slope in gamma-ray bursts

Dichiara

Guidorzi

Amati

et al. 2016

A&A

Self Cite

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Context. The origin of the gamma-ray burst (GRB) prompt emission still defies explanation, in spite of recent progress made, for example, on the occasional presence of a thermal component in the spectrum along with the ubiquitous non-thermal component that is modelled with a Band function. The combination of finite duration and aperiodic modulations make GRBs hard to characterise temporally. Although correlations between GRB luminosity and spectral hardness on one side and time variability on the other side have long been known, the loose and often arbitrary definition of the latter makes the interpretation uncertain. Aims. We characterise the temporal variability in an objective way and search for a connection with rest-frame spectral properties for a number of well-observed GRBs. Methods. We studied the individual power density spectra (PDS) of 123 long GRBs with measured redshift, rest-frame peak energy E p,i of the time-averaged ν F ν spectrum, and well-constrained PDS slope α detected with Swift, Fermi and past spacecraft. The PDS were modelled with a power law either with or without a break adopting a Bayesian Markov chain Monte Carlo technique. Results. We find a highly significant E p,i -α anti-correlation. The null hypothesis probability is ∼10 −9 . Conclusions. In the framework of the internal shock synchrotron model, the E p,i -α anti-correlation can hardly be reconciled with the predicted E p,i ∝ Γ −2 , unless either variable microphysical parameters of the shocks or continual electron acceleration are assumed. Alternatively, in the context of models based on magnetic reconnection, the PDS slope and E p,i are linked to the ejecta magnetisation at the dissipation site, so that more magnetised outflows would produce more variable GRB light curves at short timescales ( 1 s), shallower PDS, and higher values of E p,i .

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THE GAMMA-RAY BURST CATALOG OBTAINED WITH THE GAMMA-RAY BURST MONITOR ABOARD BeppoSAX

Cited by 76 publications

References 27 publications

The Third Swift Burst Alert Telescope Gamma-Ray Burst Catalog

The Third Swift Burst Alert Telescope Gamma-Ray Burst Catalog

Classification of gamma-ray burst durations using robust model-comparison techniques

Correlation between peak energy and Fourier power density spectrum slope in gamma-ray bursts

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