juliensimon/gamma-ray-bursts

Fermi GBM Gamma-Ray Burst Catalog

Complete catalog of gamma-ray bursts detected by the Fermi Gamma-ray Burst Monitor (GBM), sourced from NASA HEASARC. Currently 4,241 GRBs (707 short, 3,531 long).

Dataset description

Gamma-ray bursts (GRBs) are the most energetic explosions in the universe. They come in two classes based on duration: short GRBs (T90 < 2 s, from neutron star mergers) and **long** GRBs (T90 >= 2 s, from massive star collapse). The Fermi GBM has been detecting GRBs across the full unocculted sky since 2008.

This dataset includes duration measurements (T90, T50), fluence, peak flux, and Band function spectral parameters for each burst.

Schema

Column	Type	Description
name	string	GRB trigger name (e.g. "GRB230101123")
trigger_time	datetime	Trigger time (UTC)
ra	float	Right ascension (degrees)
dec	float	Declination (degrees)
t90	float	T90 duration in seconds (time containing 90% of fluence)
t90_error	float	T90 uncertainty
t50	float	T50 duration in seconds (time containing 50% of fluence)
t50_error	float	T50 uncertainty
fluence	float	Total fluence (erg/cm^2)
fluence_error	float	Fluence uncertainty
flux_256	float	Peak flux on 256 ms timescale (ph/cm^2/s)
pflx_best_fitting_model	string	Best-fit spectral model for peak flux
flnc_band_ampl	float	Band function amplitude
flnc_band_epeak	float	Band function peak energy (keV)
flnc_band_alpha	float	Band function low-energy index
flnc_band_beta	float	Band function high-energy index
duration_class	string	"short" (T90 < 2 s) or "long" (T90 >= 2 s)

Quick stats

• 4,241 gamma-ray bursts
• 707 short GRBs, 3,531 long GRBs
• Date range: 2008-07-14 to 2026-03-18
• Brightest burst: GRB221009553 (fluence 3.88e-02 erg/cm^2)

Usage

from datasets import load_dataset

ds = load_dataset("juliensimon/gamma-ray-bursts", split="train")
df = ds.to_pandas()

# Short vs long GRBs
short = df[df["duration_class"] == "short"]
long = df[df["duration_class"] == "long"]
print(f"{len(short):,} short, {len(long):,} long GRBs")

# Brightest bursts
top = df.nlargest(10, "fluence")[["name", "trigger_time", "fluence", "t90"]]

# T90 distribution
import matplotlib.pyplot as plt
df["t90"].dropna().apply(lambda x: max(x, 1e-3)).hist(bins=50, log=True)
plt.xlabel("T90 (s)")
plt.title("GRB Duration Distribution")

Data source

All data comes from the Fermi GBM Burst Catalog hosted by NASA's High Energy Astrophysics Science Archive Research Center (HEASARC), accessed via the TAP protocol.

Update schedule

Weekly on Monday at 17:00 UTC via GitHub Actions.

Related datasets

• space-track-satcat — NORAD Satellite Catalog
• solar-flare-index — Solar flare observations
• near-earth-objects — NEO close approaches

Pipeline

Source code: juliensimon/space-datasets

Citation

@dataset{gamma_ray_bursts,
  author = {Simon, Julien},
  title = {Fermi GBM Gamma-Ray Burst Catalog},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/juliensimon/gamma-ray-bursts},
  note = {Based on NASA HEASARC Fermi GBM Burst Catalog data}
}

License

CC-BY-4.0