9,260 research outputs found
Statistical Evidence for Three classes of Gamma-ray Bursts
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. In the standard paradigm, GRB are classified in only two groups, the
long and short bursts. However, for both the clustering techniques, the optimal
number of classes was found to be three, a result which is consistent with
previous statistical analysis. In this classification, the long bursts are
further divided into two groups which are primarily differentiated by their
total fluence and duration and hence are named low and high fluence GRB.
Analysis of GRB with known red-shifts and spectral parameters suggests that low
fluence GRB have nearly constant isotropic energy output of 10^{52} ergs while
for the high fluence ones, the energy output ranges from 10^{52} to 10^{54}
ergs. It is speculated that the three kinds of GRBs reflect three different
origins: mergers of neutron star systems, mergers between white dwarfs and
neutron stars, and collapse of massive stars.Comment: 7 pages, accepted for publication in the Astrophysical Journal. Minor
editorial change
A six-parameter space to describe galaxy diversification
Galaxy diversification proceeds by transforming events like accretion,
interaction or mergers. These explain the formation and evolution of galaxies
that can now be described with many observables. Multivariate analyses are the
obvious tools to tackle the datasets and understand the differences between
different kinds of objects. However, depending on the method used,
redundancies, incompatibilities or subjective choices of the parameters can
void the usefulness of such analyses. The behaviour of the available parameters
should be analysed before an objective reduction of dimensionality and
subsequent clustering analyses can be undertaken, especially in an evolutionary
context. We study a sample of 424 early-type galaxies described by 25
parameters, ten of which are Lick indices, to identify the most structuring
parameters and determine an evolutionary classification of these objects. Four
independent statistical methods are used to investigate the discriminant
properties of the observables and the partitioning of the 424 galaxies:
Principal Component Analysis, K-means cluster analysis, Minimum Contradiction
Analysis and Cladistics. (abridged)Comment: Accepted for publicationin A\&
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