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.
Gamma-Ray Burst Spectrum with Decaying Magnetic Field
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abstract
In the internal shock model for gamma-ray bursts (GRBs), the synchrotron spectrum from the fast cooling electrons in a homogeneous downstream magnetic field (MF) is too soft to produce the low-energy slope of GRB spectra. However the magnetic field may decay downstream with distance from the shock front. Here we show that the synchrotron spectrum becomes harder if electrons undergo synchrotron and inverse-Compton cooling in a decaying MF. To reconcile this with the typical GRB spectrum with low energy slope $\nu F_\nu\propto\nu$, it is required that the postshock MF decay time is comparable to the cooling time of the bulk electrons (corresponding to a MF decaying length typically of $\sim10^5$ skin depths); that the inverse-Compton cooling should dominate synchrotron cooling after the MF decay time; and/or that the MF decays with comoving time roughly as $B\propto t^{-1.5}$. An internal shock synchrotron model with a decaying MF can account for the majority of GRBs with low energy slopes not harder than $\nu^{4/3}$.
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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.