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| Paper: |
Automatic Spectral Classification of High Energy Transients Based on the Global Fit Approach |
| Volume: |
376, Astronomical Data Analysis Software and Systems XVI |
| Page: |
441 |
| Authors: |
Chernenko, A. |
| Abstract: |
With the launch of highly sensitive gamma-ray experiments, thousands of highly variable and transient sources, such as Gamma-ray bursts, have been recorded. For a number of reasons, such as very broad source brightness distribution, strong and fast spectral variability, tremendous diversity of light curves, and frequently involved cosmological red-shift, it has been very difficult to establish robust, unbiased, cosmologically invariant parameters that characterize the spectral variability of a source regardless of its light curve and brightness. As a solution, we proposed a general method for the analysis of time-resolved gamma-ray spectra of astrophysical transients: the Global Fit Analysis (GFA). Instead of parameterizing individual spectra and analyzing the spectral evolution of a given transient in terms of numerous individual spectral fit parameters, we define a spectral evolution model with a set of a very few (3–5) constant Global parameters and just a few (1–2) time dependent variables. Since each Global fit is in fact based on the entire source fluence, it is very robust and therefore batch Global fits are quite feasible. Thus, the parameters could be estimated without any human intervention for a large number of sources, such as entire set of sources studied by a given experiment. Further analysis of estimated Global spectral parameters allows one to identify spectral classes of sources using principal component or cluster analysis. Then further sources can be automatically related to their classes based on the scores with respect to the principal components or distance to the respective clusters. In this paper we present such analyses for Gamma-ray bursts that were recorded in the BATSE experiment. |
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