juliensimon/roma-bzcat-blazars

Roma-BZCAT Multi-frequency Blazar Catalog

Credit: NASA/ESA/STScI

Part of the Astronomy Datasets collection on Hugging Face.

The Roma-BZCAT 5th edition — 3,561 confirmed blazars, the definitive multi-frequency catalog of active galactic nuclei with relativistic jets. Includes 0 BL Lac objects, 0 flat-spectrum radio quasars (FSRQs), and 0 galaxy-dominated blazars.

Dataset description

Blazars are the most extreme class of active galactic nuclei (AGN). They are powered by supermassive black holes at the centers of galaxies, but what makes them extraordinary is that one of their relativistic jets — twin beams of plasma moving at nearly the speed of light — points almost directly at Earth. This geometric alignment produces dramatic observational effects: apparent superluminal motion, extreme variability across the electromagnetic spectrum (from radio to TeV gamma-rays on timescales from minutes to years), strong and variable polarization, and Doppler-boosted luminosities that can outshine the entire host galaxy by orders of magnitude.

Blazars are divided into two main subclasses based on their optical spectra:

• BL Lac objects (BZB): named after the prototype BL Lacertae, these sources show featureless or nearly featureless optical continua with weak or absent emission lines (equivalent width < 5 angstroms). Their spectral energy distributions (SEDs) are dominated by non-thermal synchrotron and inverse-Compton emission from the jet, and they are further subdivided by the frequency of their synchrotron peak into low-, intermediate-, and high-synchrotron-peaked BL Lacs (LSP, ISP, HSP).

• Flat-spectrum radio quasars (BZQ/FSRQ): these display strong, broad optical emission lines characteristic of quasars, indicating a luminous accretion disk and broad-line region in addition to the jet. FSRQs tend to be more luminous than BL Lacs and dominate the high-redshift blazar population.

The Roma-BZCAT (Massaro et al. 2009, 2015) is the most comprehensive and widely cited catalog of confirmed blazars, compiled from multi-wavelength observations spanning radio, optical, and X-ray bands. It serves as the reference catalog for blazar identification in gamma-ray surveys (Fermi-LAT), neutrino follow-up programs (IceCube), and multi-messenger astrophysics. Every source in Roma-BZCAT has been spectroscopically confirmed or classified through its multi-frequency properties, making it the gold standard for blazar demographics and population studies.

Schema

Column	Type	Description
seq	int64	Seq
name	string	Source name / BZCAT designation
ra_deg	float64	Right ascension J2000 (degrees)
dec_deg	float64	Declination J2000 (degrees)
glon	float64	Glon
glat	float64	Glat
redshift	float64	Spectroscopic redshift
u_z	string	U z
r_mag	float64	R-band magnitude
blazar_class	string	Blazar classification (BZB=BL Lac, BZQ=FSRQ, BZG=galaxy-dominated, BZU=uncertain)
fr	float64	Fr
f143	float64	F143
fx	float64	Fx
ff	float64	Ff
aro	float64	Aro

Quick stats

• 3,561 confirmed blazars
• 0 BL Lac objects (BZB), 0 FSRQs (BZQ), 0 galaxy-dominated (BZG), 0 uncertain (BZU)
• 3,561 with measured redshift (median z = 0.636, max z = 6.802)
• 0 with radio flux, 0 with X-ray flux
• Classes: QSO RLoud flat radio sp. (1,909), BL Lac (1,059), BL Lac-galaxy dominated (274), Blazar Uncertain type (227), BL Lac Candidate (92)

Usage

from datasets import load_dataset

ds = load_dataset("juliensimon/roma-bzcat-blazars", split="train")
df = ds.to_pandas()

# BL Lac objects vs FSRQs
bl_lacs = df[df["blazar_class"].str.startswith("BZB", na=False)]
fsrqs = df[df["blazar_class"].str.startswith("BZQ", na=False)]
print(f"{len(bl_lacs):,} BL Lacs, {len(fsrqs):,} FSRQs")

# Redshift distribution by class
import matplotlib.pyplot as plt
for cls, label in [("BZB", "BL Lac"), ("BZQ", "FSRQ")]:
    subset = df[df["blazar_class"].str.startswith(cls, na=False)]
    subset["redshift"].dropna().hist(bins=50, alpha=0.6, label=label)
plt.xlabel("Redshift")
plt.ylabel("Count")
plt.legend()
plt.title("Roma-BZCAT Redshift Distribution by Blazar Class")

# Radio-loud blazars
radio_bright = df[df["radio_flux_mjy"] > 1000].sort_values("radio_flux_mjy", ascending=False)
print(f"{len(radio_bright):,} blazars with radio flux > 1 Jy")

Data source

Massaro, E., Maselli, A., Leto, C., Marchegiani, P., Perri, M., Giommi, P., Piranomonte, S. (2015), "The 5th edition of the Roma-BZCAT. A short presentation", Astrophysics and Space Science, 357, 75. Accessed via VizieR catalog VII/274, CDS Strasbourg.

Update schedule

Static dataset — rebuilt manually when a new edition is published.

Related datasets

• quasar-catalog — SIMBAD Quasar & AGN Catalog
• milliquas — Million Quasars Catalog v8
• fermi-4lac-agn-catalog — Fermi 4LAC AGN Catalog
• fermi-4fgl-dr4 — Fermi 4FGL-DR4 Source Catalog

Pipeline

Source code: juliensimon/space-datasets

Support

If you find this dataset useful, please give it a ❤️ on the dataset page and share feedback in the Community tab! Also consider giving a ⭐️ to the space-datasets repo.

Citation

@dataset{roma_bzcat_blazars,
  author = {Simon, Julien},
  title = {Roma-BZCAT Multi-frequency Blazar Catalog},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/juliensimon/roma-bzcat-blazars},
  note = {Based on Roma-BZCAT 5th edition (Massaro et al. 2015) via VizieR CDS Strasbourg}
}

License

VizieR Scientific-Use Terms