AGN-DB: A Unified Multi-Wavelength Database of Active Galactic Nuclei
Abstract
We present the Active Galactic Nuclei Database (AGN-DB), a comprehensive, multi-wavelength catalog compiled from more than 100 publicly available AGN catalogs and samples released by the end of 2025, spanning radio to γ-ray wavelengths. The database contains approximately 8.1 million unique sources, approximately 7.8 million of which remain after flagging stellar contaminants, and approximately 6.8 million of these are classified as AGN. Source cross-matching across catalogs is performed using Lyra, a Bayesian likelihood-ratio framework that jointly considers positional uncertainties, source densities, and photometric information to compute posterior match probabilities. The resulting catalog provides astrometric coordinates, redshifts, photometry, and classifications for each unique source. All multi-catalog provenance is preserved. For every property, we store the full array of values and originating catalog identifiers, enabling multi-epoch and multi-survey analyses. In this paper, we describe the AGN-DB pipeline, including the cross-matching methodology, and present the statistical properties of the v1.0 catalog. AGN-DB is designed to enable population studies, spectral energy distribution modeling, AGN classification, and variability analyses at an unprecedented scale. Its pipeline is designed to facilitate the integration of new catalogs, allowing AGN-DB to be updated regularly, with releases planned at least annually.
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BibTeX
@misc{peca2026agndb,
title = {{AGN-DB: A Unified Multi-Wavelength Database of Active Galactic Nuclei}},
author = {Alessandro Peca and Nico Cappelluti and C. Megan Urry and Zhongtian Hu and Jerry R. Bonnell and Jack McKeown and Giulia Cerini and Xulei Sun and Fabio Pacucci and Tracey Jane Turner and Peter G. Boorman and Aritra Ghosh and Connor Auge and Rebeka L. Böttger and Adi Foord and Massimiliano Galeazzi and Jeyhan S. Kartaltepe and Iver Warburton Kilmarrin and Allison Kirkpatrick and Michael J. Koss and Stephanie LaMassa and Md Mahmudunnobe and Stefano Marchesi and Lea Marcotulli and Isaac Moskowitz and Priyamvada Natarajan and Mitsunori Ogihara and Meredith Powell and David Sanders and Dominic Sicilian and Chuan Tian and Ezequiel Treister},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.04322},
eprint = {2609.04322},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.04322},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - AGN-DB: A Unified Multi-Wavelength Database of Active Galactic Nuclei
AU - Alessandro Peca
AU - Nico Cappelluti
AU - C. Megan Urry
AU - Zhongtian Hu
AU - Jerry R. Bonnell
AU - Jack McKeown
AU - Giulia Cerini
AU - Xulei Sun
AU - Fabio Pacucci
AU - Tracey Jane Turner
AU - Peter G. Boorman
AU - Aritra Ghosh
AU - Connor Auge
AU - Rebeka L. Böttger
AU - Adi Foord
AU - Massimiliano Galeazzi
AU - Jeyhan S. Kartaltepe
AU - Iver Warburton Kilmarrin
AU - Allison Kirkpatrick
AU - Michael J. Koss
AU - Stephanie LaMassa
AU - Md Mahmudunnobe
AU - Stefano Marchesi
AU - Lea Marcotulli
AU - Isaac Moskowitz
AU - Priyamvada Natarajan
AU - Mitsunori Ogihara
AU - Meredith Powell
AU - David Sanders
AU - Dominic Sicilian
AU - Chuan Tian
AU - Ezequiel Treister
PY - 2026
DA - 2026/09/03
PB - arXiv
DO - 10.48550/arxiv.2609.04322
UR - https://arxiv.org/abs/2609.04322
AB - We present the Active Galactic Nuclei Database (AGN-DB), a comprehensive, multi-wavelength catalog compiled from more than 100 publicly available AGN catalogs and samples released by the end of 2025, spanning radio to γ-ray wavelengths. The database contains approximately 8.1 million unique sources, approximately 7.8 million of which remain after flagging stellar contaminants, and approximately 6.8 million of these are classified as AGN. Source cross-matching across catalogs is performed using Lyra, a Bayesian likelihood-ratio framework that jointly considers positional uncertainties, source densities, and photometric information to compute posterior match probabilities. The resulting catalog provides astrometric coordinates, redshifts, photometry, and classifications for each unique source. All multi-catalog provenance is preserved. For every property, we store the full array of values and originating catalog identifiers, enabling multi-epoch and multi-survey analyses. In this paper, we describe the AGN-DB pipeline, including the cross-matching methodology, and present the statistical properties of the v1.0 catalog. AGN-DB is designed to enable population studies, spectral energy distribution modeling, AGN classification, and variability analyses at an unprecedented scale. Its pipeline is designed to facilitate the integration of new catalogs, allowing AGN-DB to be updated regularly, with releases planned at least annually.
ER -