In simulated GRB detection, quantum fingerprinting encoding consistently outperforms data reuploading, confirming that data encoding choice dominates QML performance.
The Fermi GBM Gamma-Ray Burst Spectral Catalog: 10 Years of Data
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We present the systematic spectral analyses of gamma-ray bursts (GRBs) detected by the Fermi Gamma-Ray Burst Monitor (GBM) during its first ten years of operation. This catalog contains two types of spectra; time-integrated spectral fits and spectral fits at the brightest time bin, from 2297 GRBs, resulting in a compendium of over 18000 spectra. The four different spectral models used for fitting the spectra were selected based on their empirical importance to the shape of many GRBs. We describe in detail our procedure and criteria for the analyses, and present the bulk results in the form of parameter distributions both in the observer frame and in the GRB rest frame. 941 GRBs from the first four years have been re-fitted using the same methodology as that of the 1356 GRBs in years five through ten. The data files containing the complete results are available from the High-Energy Astrophysics Science Archive Research Center (HEASARC).
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Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection
In simulated GRB detection, quantum fingerprinting encoding consistently outperforms data reuploading, confirming that data encoding choice dominates QML performance.