--- license: other license_name: vizier-scientific-use license_link: https://cds.unistra.fr/vizier-org/licences_vizier.html pretty_name: "Veron-Cetty AGN/Quasar Catalog (13th edition)" language: - en description: "The Veron-Cetty & Veron Quasars and Active Nuclei catalog, 13th edition (VizieR VII/258) — the canonical reference compilation of 168,940 quasars and active galactic nuclei published through 2010, cov" task_categories: - tabular-classification tags: - space - astronomy - agn - quasars - active-galactic-nuclei - seyfert - blazars - bl-lac - vizier - open-data - tabular-data - parquet size_categories: - 100K Artist concept of a supermassive black hole with a relativistic jet — AGN engine

Credit: NASA/JPL-Caltech

*Part of a [dataset collection](https://huggingface.co/collections/juliensimon/galaxies-and-cosmology-69c792b117242a3b236df55d) on Hugging Face.* ## Dataset description The Veron-Cetty & Veron Quasars and Active Nuclei catalog, 13th edition (VizieR VII/258) — the canonical reference compilation of 168,940 quasars and active galactic nuclei published through 2010, covering optical/UV-selected quasars, X-ray-selected AGN, radio galaxies, and BL Lac objects. The catalog merges every published QSO and AGN identification with a homogeneous position, spectroscopic redshift, optical photometry, B-V and U-B colors, absolute magnitude, and (where available) radio fluxes at 6 cm and 20 cm. It remains the standard look-up source for cross-matching unidentified sources against the established AGN population, for selecting training/test samples by spectral subclass (Seyfert 1, Seyfert 2, LINER, BL Lac), and for population statistics in redshift, luminosity, and color spaces. Object class column conventions: 'Q' marks quasars (M_V <= -23, brighter than the historical QSO/AGN boundary), 'A' marks lower-luminosity AGN (M_V > -23), and 'B' marks BL Lac objects. The spectral classification column captures Seyfert sub-type and special spectral phenomena. Use this dataset alongside juliensimon/milliquas (the more recent Million Quasars Catalog that supersedes Veron for survey-era discoveries), juliensimon/gaia-dr3-qso-candidates (Gaia-selected QSOs), juliensimon/black-hole-catalog, juliensimon/4xmm-dr14-xray-sources, and juliensimon/icrf3-reference-frame for AGN cross-mission analysis. This dataset is suitable for **tabular classification** tasks. ## Schema | Column | Type | Description | Sample | Null % | |--------|------|-------------|--------|--------| | `object_class` | str | Object classification: 'Q' = quasar (M_abs <= -23, brighter than -23), 'A' = AGN (M_abs > -23, fainter), 'B' = BL Lac object | Q | 0.0% | | `radio_flag` | str | Radio-detection flag: '*' = detected at radio frequencies, blank = not detected (or no radio coverage) | * | 11.3% | | `name` | str | Primary designation (catalog and survey ID), typically 'SDSS Jhhmm+ddmm', '4C+nn.nn', 'PG hhmm+ddd', etc. | SDSS J03003+0009 | 0.0% | | `position_origin` | str | Origin code for the J2000 coordinates: 'O' = optical position, 'R' = radio position, 'X' = X-ray, etc. | O | 2.5% | | `ra` | float64 | Right ascension (degrees, J2000) | 45.07541666666666 | 0.0% | | `dec` | float64 | Declination (degrees, J2000) | 0.1524999999999999 | 0.0% | | `flux_20cm_mjy` | float64 | Radio flux density at 20 cm (1.4 GHz) in mJy where detected | 0.0 | 89.2% | | `flux_20cm_reference` | float64 | Bibliographic reference code for the 20 cm flux measurement | 2068.0 | 64.6% | | `redshift` | float64 | Spectroscopic or photometric redshift z (dimensionless); range ~0 to ~7 in this compilation | 2.23 | 0.4% | | `spectral_classification` | str | Spectral subclass code: 'S1' = Seyfert 1, 'S2' = Seyfert 2, 'S1.5'/'S1.9' = intermediate types, 'NLAGN' = narrow-line AGN, 'HP' = high polarization, 'LINER' = LINER, blank = standard QSO | S2 | 82.7% | | `magnitude_band` | str | Photometric system letter for the magnitude: 'V' = Johnson V, 'B' = blue, 'R' = red, 'g' = SDSS g, etc. | * | 81.4% | | `apparent_magnitude` | float64 | Apparent magnitude in the band identified by magnitude_band; brighter sources have smaller values | 20.45 | 0.4% | | `color_bv` | float64 | Johnson B-V color index (mag); positive values indicate redder colors | 0.28 | 22.1% | | `color_ub` | float64 | Johnson U-B color index (mag); the 'UV excess' (negative U-B) is the historical AGN selection signature | -0.18 | 9.7% | | `absolute_magnitude` | float64 | Absolute V magnitude M_V (mag); the Q/A class boundary is M_V = -23. Computed assuming H_0 = 71, Omega_M = 0.27, Omega_lambda = 0.73 | -24.4 | 0.7% | | `finding_chart_reference` | float64 | Bibliographic reference code for a published finding chart of the source | 529.0 | 93.5% | | `magnitude_reference` | float64 | Bibliographic reference code for the magnitude measurement | 2068.0 | 9.1% | | `redshift_reference` | float64 | Bibliographic reference code for the redshift | 2068.0 | 0.0% | ## Quick stats - **168,940** quasars + AGN + BL Lac objects in the canonical compilation - **133,335** quasars (M_V <= -23) + **34,231** lower-luminosity AGN + **1,374** BL Lac objects - **149,874** sources with detected radio counterparts (6cm or 20cm) - Redshift range: **0.00** to **6.43** (median 1.35) - Absolute magnitude (M_V): **-31.5** (most luminous) to **-7.8** (faintest) ## Usage ```python from datasets import load_dataset ds = load_dataset("juliensimon/veron-agn-quasar-catalog", split="train") df = ds.to_pandas() ``` ```python from datasets import load_dataset import matplotlib.pyplot as plt import numpy as np df = load_dataset("juliensimon/veron-agn-quasar-catalog", split="train").to_pandas() # Hubble diagram: absolute magnitude vs redshift, colored by class mask = df["redshift"].notna() & df["absolute_magnitude"].notna() fig, ax = plt.subplots(figsize=(10, 6)) for cls, color in zip(["Q", "A", "B"], ["blue", "orange", "red"]): sub = df[mask & (df["object_class"] == cls)] ax.scatter(sub["redshift"], sub["absolute_magnitude"], s=2, alpha=0.3, color=color, label=cls) ax.axhline(-23, color="grey", linestyle="--", label="QSO/AGN boundary") ax.invert_yaxis() # brighter = up ax.set_xscale("log") ax.set_xlabel("Redshift z") ax.set_ylabel("Absolute V magnitude") ax.legend() plt.tight_layout() plt.show() # Seyfert sub-type breakdown print(df["spectral_classification"].value_counts().head(15)) ``` ## Data source https://cdsarc.cds.unistra.fr/viz-bin/cat/VII/258 ## Related datasets - [juliensimon/milliquas](https://huggingface.co/datasets/juliensimon/milliquas) - [juliensimon/gaia-dr3-qso-candidates](https://huggingface.co/datasets/juliensimon/gaia-dr3-qso-candidates) - [juliensimon/black-hole-catalog](https://huggingface.co/datasets/juliensimon/black-hole-catalog) - [juliensimon/4xmm-dr14-xray-sources](https://huggingface.co/datasets/juliensimon/4xmm-dr14-xray-sources) - [juliensimon/icrf3-reference-frame](https://huggingface.co/datasets/juliensimon/icrf3-reference-frame) - [juliensimon/roma-bzcat-blazars](https://huggingface.co/datasets/juliensimon/roma-bzcat-blazars) > If you find this dataset useful, please consider [giving it a like](https://huggingface.co/datasets/juliensimon/veron-agn-quasar-catalog) on Hugging Face. It helps others discover it. ## About the author Created by [Julien Simon](https://julien.org) — AI Operating Partner at Fortino Capital. Part of the [Space Datasets](https://julien.org/datasets) collection. ## Citation ```bibtex @dataset{veron_agn_quasar_catalog, title = {Veron-Cetty AGN/Quasar Catalog (13th edition)}, author = {juliensimon}, year = {2026}, url = {https://huggingface.co/datasets/juliensimon/veron-agn-quasar-catalog}, publisher = {Hugging Face} } ``` ## License [VizieR Scientific-Use Terms](https://cds.unistra.fr/vizier-org/licences_vizier.html)