Classification Problem and Parameter Estimating of Gamma-Ray Bursts

P. 134–147.

Minaev P., Pozanenko A. S.

There are at least two distinct classes of Gamma-Ray Bursts
(GRB) according to their progenitors: short duration and long duration
bursts. It was shown that short bursts result from compact binary
merging, while long bursts are associated with core collapse supernova.
However, one could suspect the existence of more classes and subclasses.
For example, compact binary can be double neutron stars, or neutron
star and black hole, which might generate gamma-ray bursts with different
properties. From another hand, gamma-ray transients are known
to be produced by magnetars in Galaxy, named Soft Gamma-Repeaters
(SGR). A Giant Flare from SGR can be detected from a nearby galaxy,
and it can mimic for a short GRB. So the classification problem is
very important for correct investigation of different transient progenitors.
Gamma-ray transients are characterized by a number of parameters and
known phenomenology correlations between them, obtained for well classified
ones. Using these correlations, which could be unique for different
classes of gamma-ray transients, we can classify an event and determine
the type of its progenitor, using only temporal and spectral characteristics.
We suggest the statistical classification method, based on the cluster
analysis of the trained dataset of 323 events. Using the known dependencies,
one can not only classify the types of gamma-ray bursts, but also
discriminate events that are not associated with gamma-ray bursts, but
have a different physical nature. We show that GRB 200415A, originally
classified as a short GRB, probably does not belong to the class of short
GRBs, but it is most likely associated with the giant flare of SGR. On
the other hand, we can estimate one of the unknown parameters if we
assume the certain classification of the event. As an example, an estimate
the redshift of the GRB 200422A source is given. We also discuss
that in some cases it is possible to give a probabilistic estimate of the
unknown parameters of the source. The method could be applied to any
other analogous classification problems.

Keywords: классификация, cluster analysis, кластерный анализ, classifications, гамма-всплески, gamma-ray bursts, Soft gamma repeater, Redshift, источники повторного гамма-излучения, красное смещение

In book

Data Analytics and Management in Data Intensive Domains: 22nd International Conference, DAMDID/RCDL 2020, Voronezh, Russia, October 13–16, 2020, Selected Proceedings

Springer, 2021.