CNN emulator for decaying magnetic field fast-cooling synchrotron spectra is trained on synthetic data and used in Bayesian fits to GRB 231020A, favoring the decaying-field model over the standard version.
The Fermi GBM Gamma-Ray Burst Spectral Catalog: Four Years Of Data
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abstract
In this catalog we present the updated set of spectral analyses of GRBs detected by the Fermi Gamma-Ray Burst Monitor (GBM) during its first four years of operation. It contains two types of spectra, time-integrated spectral fits and spectral fits at the brightest time bin, from 943 triggered GRBs. Four different spectral models were fitted to the data, resulting in a compendium of more than 7500 spectra. The analysis was performed similarly, but not identically to Goldstein et al. 2012. All 487 GRBs from the first two years have been re-fitted using the same methodology as that of the 456 GRBs in years three and four. We describe, in detail, our procedure and criteria for the analysis, and present the results in the form of parameter distributions both for the observer-frame and rest-frame quantities. The data files containing the complete results are available from the High-Energy Astrophysics Science Archive Research Center (HEASARC).
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Modeling Gamma-Ray Burst Spectra with Convolutional Neural Networks: Fast-Cooling Synchrotron Emission in a Decaying Magnetic Field
CNN emulator for decaying magnetic field fast-cooling synchrotron spectra is trained on synthetic data and used in Bayesian fits to GRB 231020A, favoring the decaying-field model over the standard version.