AGN-DB：一个统一的多波段活动星系核数据库
AGN-DB: A Unified Multi-Wavelength Database of Active Galactic Nuclei
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中文总结 AI 辅助
该研究推出AGN-DB多波段活动星系核数据库，整合100余个公开星表，经Lyra框架匹配后含约680万AGN，支持多类分析且可定期更新。
中文摘要 AI 辅助
我们推出活动星系核数据库（AGN-DB），这是一个综合多波段星表，汇编自截至2025年底发布的100多个公开AGN星表和样本，覆盖从射电到γ射线的全波段。该数据库包含约810万个独特源，标记恒星污染物后剩余约780万个，其中约680万个被归类为AGN。跨星表的源匹配采用Lyra框架完成，这是一种贝叶斯似然比框架，联合考虑位置不确定性、源密度和测光信息来计算后验匹配概率。生成的星表为每个独特源提供天体测量坐标、红移、测光数据和分类结果，保留了所有多星表来源信息。对于每个属性，我们存储完整的数值数组及其来源星表标识符，支持多历元和多巡天分析。本文描述了AGN-DB的处理流程，包括匹配方法，并展示了v1.0星表的统计特性。AGN-DB旨在以前所未有的规模开展种群研究、光谱能量分布建模、AGN分类和变异性分析，其处理流程设计便于整合新的星表，使AGN-DB能够定期更新，计划至少每年发布一次版本。
英文摘要
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.
发表机构
- Eureka Scientific（尤里卡科学）
- Yale University（耶鲁大学）
- University of Miami（迈阿密大学）
- Universidad Diego Portales（迭戈帕托莱斯大学）
- Technische Universität Wien (TU Wien)（维也纳工业大学）
- California Institute of Technology（加州理工学院）
机构由 AI 辅助整理，请以论文原文为准。
