📝 SummarXiv

Abstract

Active galactic nuclei (AGNs) exhibit stochastic optical variability, commonly characterized by a damped random walk. The damping timescale 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 timescales 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 timescale on AGN properties. In contrast, we introduce a novel forward modeling approach, Baseline-Aware Dependence fitting for DAmping Timescales (BADDAT), which explicitly accounts for these biases and leverages the information contained in underestimated timescale measurements. Rather than attempting to correct individual timescale measurements, BADDAT robustly constrains the population-level dependence of damping timescale 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.