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 Spectral Evolution Through Crosscorrelations of Discriminator Light Curves
2 Pith papers cite this work. Polarity classification is still indexing.
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abstract
Gamma-ray burst spectra usually show hard-to-soft evolution within intensity spikes and from spike to spike. The techniques used to study spectral evolution often lack sufficient temporal resolution to determine the nature of this evolution. By comparing the auto- and crosscorrelations between the time histories of the BATSE Large Area Detector discriminator rates I have characterized the spectral evolution of a sample of 209 bursts. I find that hard-to-soft evolution is ubiquitous, and only ~10% of the bursts show clear soft-to-hard evolution.
fields
astro-ph.HE 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Time lags between energy bands serve as proxies for spectral evolution in GRBs, with positive lags tracing prompt emission softening and negative lags indicating a new delayed high-energy component.
citing papers explorer
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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.
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Time lags as proxy of spectral evolution in gamma-ray bursts
Time lags between energy bands serve as proxies for spectral evolution in GRBs, with positive lags tracing prompt emission softening and negative lags indicating a new delayed high-energy component.