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Dataset . 2023
License: CC BY
Data sources: Datacite
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Gamma-ray burst detection with Poisson-FOCuS and other trigger algorithms

Authors: Giuseppe Dilillo;

Gamma-ray burst detection with Poisson-FOCuS and other trigger algorithms

Abstract

Datasets for the paper "Detecting GRBs with Poisson-FOCuS and other trigger algorithms". The repository contains the following datasets: simulated_dataset_grb120707800.fits: This dataset comprises a FITS table containing data for 30,000 simulated Gamma-Ray Burst (GRB) lightcurves. These lightcurves simulate different intensities and are modeled after the short burst GRB120707800. The data are binned at a 16 ms resolution and stored as images. This file includes both control and testing datasets. simulated_dataset_grb180703949.fits: Similar to the previous dataset, this one contains data for 30,000 simulated GRB lightcurves. However, these lightcurves are modeled after long burst GRB180703949. The data is also binned at a 16 ms resolution and stored as images. Like the previous dataset, it includes both control and testing datasets. gbm_dataset_50to300keV_binned016ms_20171002_201710.zip: This dataset consists of a zipped CSV file containing count data observed by the 12 NaI detectors of Fermi-GBM during the period from October 2, 2017, to October 10, 2017. The data are binned at a 16 ms resolution and covers the energy band 50-300 keV. simulated_dataset_compeff: This dataset includes a collection of 1000 randomly generated, Poisson-distributed count time series with varying lengths and means, stored as text files. Rather dull but provided for completeness.

Keywords

gamma-ray burst, time series, trigger algorithms

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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