juliensimon/roma-bzcat-blazars

---
license: cc-by-4.0
pretty_name: "Roma-BZCAT Blazar Catalog"
language:
- en
description: "The definitive catalog of confirmed blazars from the Roma-BZCAT 5th edition — ~3,500 AGN with relativistic jets, including BL Lacs and FSRQs, with multi-frequency data."
task_categories:
- tabular-classification
tags:
- space
- open-data
- tabular-data
- parquet
- blazar
- agn
- roma-bzcat
- astronomy
- radio
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: data/roma_bzcat_blazars.parquet
default: true
---

# Roma-BZCAT Multi-frequency Blazar Catalog

<div align="center">
<img src="banner.jpg" alt="Hubble Deep Field revealing myriad galaxies across cosmic time" width="400">
<p><em>Credit: NASA/ESA/STScI</em></p>
</div>

*Part of the [Astronomy Datasets](https://huggingface.co/collections/juliensimon/astronomy-datasets-69c24caf2f17e36128946743) collection on Hugging Face.*

![Updated](https://img.shields.io/badge/dynamic/json?url=https://raw.githubusercontent.com/juliensimon/space-datasets/main/status.json&query=$["roma-bzcat"]&label=updated&color=brightgreen)

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

```python
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](https://vizier.cds.unistra.fr/) catalog VII/274, CDS Strasbourg.

## Update schedule

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

## Related datasets

- [quasar-catalog](https://huggingface.co/datasets/juliensimon/quasar-catalog) — SIMBAD Quasar & AGN Catalog
- [milliquas](https://huggingface.co/datasets/juliensimon/milliquas) — Million Quasars Catalog v8
- [fermi-4lac-agn-catalog](https://huggingface.co/datasets/juliensimon/fermi-4lac-agn-catalog) — Fermi 4LAC AGN Catalog
- [fermi-4fgl-dr4](https://huggingface.co/datasets/juliensimon/fermi-4fgl-dr4) — Fermi 4FGL-DR4 Source Catalog

## Pipeline

Source code: [juliensimon/space-datasets](https://github.com/juliensimon/space-datasets)

## Support

If you find this dataset useful, please give it a ❤️ on the [dataset page](https://huggingface.co/datasets/juliensimon/roma-bzcat-blazars) and share feedback in the Community tab! Also consider giving a ⭐️ to the [space-datasets](https://github.com/juliensimon/space-datasets) repo.

## Citation

```bibtex
@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

[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)