Baseline-Aware Dependence fitting for DAmping Timescales (BADDAT): a nearly unbiased approach to constraining optical variability dependence on physical properties of active galactic nuclei

作者：Ruisong Xia, Zhen-Yi Cai, Yongquan Xue, Lu Xianliang, Guowei Ren, Shuying Zhou, Mouyuan Sun, Shifu Zhu, Zhen-Bo Su, Hao Liu · 发表于：Monthly Notices of the Royal Astronomical Society Letters · 年份：2025 · DOI：10.1093/mnrasl/slaf102 · 被引用次数：1 · 研究领域：Stellar, planetary, and galactic studies、Astronomy and Astrophysical Research、Astro and Planetary Science

ABSTRACT Active galactic nuclei (AGNs) exhibit stochastic optical variability, commonly characterized by a damped random walk. The damping time-scale is of particular interest because it is related to fundamental properties of the central black hole, such as its mass and accretion rate. However, the systematic underestimation of damping time-scales caused by limited observational baselines makes it difficult to exhaustively utilize all available data. Many previous efforts have relied on strict selection criteria to avoid biased measurements, and such criteria inevitably constrain the range of AGN physical parameter space and therefore hinder robust inference of the underlying dependencies of damping time-scale on AGN properties. In contrast, we introduce a novel forward modelling approach, Baseline-Aware Dependence fitting for DAmping Timescales (BADDAT), which explicitly accounts for these biases and leverages the information contained in underestimated time-scale measurements. Rather than attempting to correct individual time-scale measurements, BADDAT robustly constrains the population-level dependence of damping time-scale on AGN physical properties. We demonstrate its effectiveness using mock light curves and show that it successfully reconciles previous inconsistent results based on two independent AGN samples. Our BADDAT method will have broad applications in AGN variability studies during the era of time-domain astronomy.