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juliensimon/fermi-4lac-agn-catalog

Fermi LAT Fourth AGN Catalog (4LAC) Credit: NASA/JPL-Caltech/STScI/CXC/SAO Part of a dataset collection on Hugging Face. Dataset description Active galactic nuclei (AGN) detected by the Fermi Large Area Telescope, the largest gamma-ray AGN catalog with source classifications, spectral parameters, and redshifts. Active galactic nuclei are supermassive black holes at the centers of galaxies that produce powerful jets of relativistic particles. When one of… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/fermi-4lac-agn-catalog.

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Dataset Card

Fermi LAT Fourth AGN Catalog (4LAC)

<div align="center"> <img src="banner.jpg" alt="Cassiopeia A supernova remnant in X-ray, optical, and infrared light" width="400"> <p><em>Credit: NASA/JPL-Caltech/STScI/CXC/SAO</em></p> </div>

Part of a [dataset collection](https://huggingface.co/collections/juliensimon/physics-datasets-69c2d4682d37dfdb77447bd7) on Hugging Face.

Dataset description

Active galactic nuclei (AGN) detected by the Fermi Large Area Telescope, the largest gamma-ray AGN catalog with source classifications, spectral parameters, and redshifts.

Active galactic nuclei are supermassive black holes at the centers of galaxies that produce powerful jets of relativistic particles. When one of these jets points toward Earth, the AGN appears as a blazar -- the most common type of gamma-ray source in the sky.

The Fourth LAT AGN Catalog (4LAC) is based on Fermi LAT observations and represents the most comprehensive census of gamma-ray AGN. It includes BL Lac objects, flat-spectrum radio quasars (FSRQs), and other AGN types, with spectral parameters, variability indices, and multiwavelength counterpart associations.

The two dominant blazar subclasses -- BL Lac objects and FSRQs -- represent fundamentally different accretion regimes onto supermassive black holes. FSRQs are high-luminosity sources with strong broad emission lines, radiatively efficient accretion disks, and gamma-ray spectra that tend to be soft due to dominant external Compton scattering. BL Lac objects have weak or absent emission lines, radiatively inefficient accretion flows, and harder gamma-ray spectra produced primarily by synchrotron self-Compton emission within the jet.

The gamma-ray properties in 4LAC, combined with radio, optical, and X-ray data, enable construction of broadband spectral energy distributions (SEDs) spanning over 15 decades in frequency, constraining physical jet models and distinguishing between leptonic and hadronic emission scenarios.

This dataset is suitable for tabular classification tasks.

Schema

ColumnTypeDescriptionSampleNull %
namestrIAU source name (4FGL designation)4FGL J2109.8-86180.0%
rafloat64Right ascension (J2000, degrees, 0-360)317.46190.0%
decfloat64Declination (J2000, degrees, -90 to +90)-86.30780.0%
liifloat64Galactic longitude (degrees, 0-360)306.41255490.0%
biifloat64Galactic latitude (degrees, -90 to +90)-29.181885240.0%
energy_fluxfloat64Energy flux in erg/cm2/s integrated over 100 MeV-100 GeV3.1895e-120.0%
pivot_energyfloat64Decorrelation (pivot) energy in MeV at which the flux uncertainty is minimized; minimizes spectral index / normalization degeneracy6264.750.0%
lp_indexfloat64Log-parabola spectral index at the pivot energy1.76070.0%
lp_betafloat64Log-parabola curvature parameter; >0 indicates spectral softening at higher energies0.03660.0%
assoc_namestrCounterpart name at other wavelengths (radio, optical, or X-ray); null if no confident association2MASS J21101113-86184730.0%
redshiftfloat64Spectroscopic redshift; null for ~40% of BL Lac objects that lack optical emission lines1.03247.0%
sed_classstrSynchrotron peak classification: LSP (low-synchrotron-peaked), ISP (intermediate), HSP (high)HSP22.8%
variability_indexfloat64Flux variability chi-squared statistic over the 4-year baseline; >18.48 indicates significant variability at 99% confidence10.41920.0%
frac_variabilityfloat64Fractional variability amplitude F_var; null if source is not significantly variable0.00.0%

Quick stats

  • —3,407 active galactic nuclei
  • —1,806 sources with measured redshift
  • —Median redshift: 0.560

Usage

python
from datasets import load_dataset

ds = load_dataset("juliensimon/fermi-4lac-agn-catalog", split="train")
df = ds.to_pandas()
python
from datasets import load_dataset

ds = load_dataset("juliensimon/fermi-4lac-agn-catalog", split="train")
df = ds.to_pandas()

# Brightest AGN by flux
top = df.nlargest(10, "flux")[["name", "flux", "spectral_index", "redshift"]]
print(top)

# Redshift distribution
import matplotlib.pyplot as plt
df["redshift"].dropna().hist(bins=50)
plt.xlabel("Redshift")
plt.title("4LAC AGN Redshift Distribution")
plt.show()

Data source

https://heasarc.gsfc.nasa.gov/W3Browse/fermi/fermilac.html

Related datasets

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About the author

Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.

Citation

bibtex
@dataset{fermi_4lac_agn_catalog,
  title = {Fermi LAT Fourth AGN Catalog (4LAC)},
  author = {Simon, Julien},
  year = {2026},
  url = {https://huggingface.co/datasets/juliensimon/fermi-4lac-agn-catalog},
  publisher = {Hugging Face},
  note = {Derived from NASA HEASARC (High Energy Astrophysics Science Archive Research Center), https://heasarc.gsfc.nasa.gov/W3Browse/fermi/fermilac.html}
}

License

CC-BY-4.0