相关论文: Properties of Gamma-Ray Burst Classes

A multivariate analysis of gamma-ray burst (GRB) bulk properties is presented to discriminate between distinct classes of GRBs. Several variables representing burst duration, fluence and spectral hardness are considered. Two multivariate…

Two different multivariate clustering techniques, the K-means partitioning method and the Dirichlet process of mixture modeling, have been applied to the BATSE Gamma-ray burst (GRB) catalog, to obtain the optimum number of coherent groups.…

Two classes of Gamma-ray bursts (GRBs), corresponding to the short/hard and the long/soft events, with a putative intermediate class, are typically considered in the observer frame. However, when considering GRB characteristics in the…

Clustering is an important tool to describe gamma-ray bursts (GRBs). We analyzed the Final BATSE Catalog using Gaussian-mixture-models-based clustering methods for six variables (durations, peak flux, total fluence and spectral hardness…

We have applied two different automatic classifier algorithms to the BATSE Current GRB Catalog data and we obtain three different classes of GRBs. Our results confirm the existence of a third, intermediate class of GRBs, with mean duration…

Gamma-ray bursts (GRBs) are commonly attributed to the demise of massive stars or the merger of binary compact objects. However, their varied emission characteristics strongly imply the existence of multiple GRB classes based on progenitor…

Unsupervised pattern recognition algorithms support the existence of three gamma-ray burst classes; Class I (long, large fluence bursts of intermediate spectral hardness), Class II (short, small fluence, hard bursts), and Class III (soft…

Clustering methods are an important tool to enumerate and describe the different coherent kinds of Gamma Ray Bursts (GRBs). But their performance can be affected by a number of factors such as the choice of clustering algorithm and inherent…

Gamma-ray bursts (GRBs) are usually classified into long/short categories according to their durations, but controversy still exists in this aspect. Here we re-examine the long/short classification of GRBs and further compare the…

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…

Gamma-ray bursts can be divided into three groups ("short", "intermediate", "long") with respect to their durations. The third type of gamma-ray bursts - as known - has the intermediate duration. We show that the intermediate group is the…

Two classes of gamma-ray bursts have been identified in the BATSE catalogs characterized by durations shorter and longer than about 2 seconds. There are, however, some indications for the existence of a third one. Swift satellite detectors…

Gamma-Ray Bursts (GRBs) have been traditionally divided into two categories: "short" and "long" with durations less than and greater than two seconds, respectively. However, there is a lot of literature (with conflicting results) regarding…

Two classes of Gamma Ray Bursts have been identified so far, characterized by T_90 durations shorter and longer than approximately 2 seconds. We show here that the BATSE 3B data allow a good fit with three Gaussian distributions in log…

Aims. An attempt to classify gamma-ray bursts (GRBs) with a low level of supervision using the state-of-the-start approaches stemming from graph theory was undertaken. Methods. Graph-based classification methods, relying on different…

While Gamma-Ray Burst (GRBs) are clear and distinct observed events, every individual GRB is unique. In fact, GRBs are known for their variable behaviour, and BATSE was already able to discover two categories of GRB from the T90…

The division of Gamma-ray bursts (GRBs) into different classes, other than the "short" and "long", has been an active field of research. We investigate whether GRBs can be classified based on a broader set of parameters, including prompt…

We use ESX, a product of Information Acumen Corporation, to perform unsupervised learning on a data set containing 797 gamma-ray bursts taken from the BATSE 3B catalog. Assuming all attributes to be distributed logNormally, Mukherjee et al.…

Gamma-ray bursts (GRBs) can be divided into three subclasses: X-ray flash (XRF), X-ray rich (XRR), and classical GRB (C-GRB). An X-ray flare is the rebrightening emission shown in the early X-ray afterglow of some GRBs. In this paper, we…

The Fermi GBM catalog provides a large database with many measured variables that can be used to explore and verify gamma-ray burst classification results. We have used Principal Component Analysis and statistical clustering techniques to…