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.
Non-Thermal emission from the photospheres of Gamma-Ray Burst outflows. I: High frequency tails
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abstract
We study the spectrum of high frequency radiation emerging from mildly dissipative photospheres of long-duration gamma-ray burst outflows. Building on the results of recent numerical investigations, we assume that electrons are heated impulsively to mildly relativistic energies by either shocks or magnetic dissipation at Thomson optical depths of several and subsequently cool by inverse Compton, scattering off the thermal photons of the photosphere. We show that even in the absence of magnetic field and non-thermal leptons, inverse Compton scattering produces power-law tails that extend from the peak of the thermal radiation, at several hundred keV, to several tens of MeV, and possibly up to GeV energies. The slope of the high-frequency power-law is predicted to vary substantially during a single burst, and the model can easily account for the diversity of high-frequency spectra observed by BATSE. Our model works in baryonic as well as in magnetically dominated outflows, as long as the magnetic field component is not overwhelmingly dominant.
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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.