论文标题
为下一代大数据调查建模光度计映射数据。与LSST大小的类星体积聚磁盘尺寸
Modeling photometric reverberation mapping data for the next generation of big data surveys. Quasar accretion disks sizes with the LSST
论文作者
论文摘要
光度传感映射可以通过测量在不同的连续体带中观察到的光曲线之间的时间延迟来检测活性银核中积聚盘(AD)的径向范围。量化延迟测量效率和准确性的约束对于恢复AD尺寸左度关系以及可能使用类星体作为标准蜡烛很重要。我们已经探索了使用下一代大数据调查来确定类星体的AD大小的可能性。我们专注于Vera C. Rubin天文台的时空(LSST)的传统调查,该调查将在其10年的运营寿命中观察数千种类星体,并在深度钻探场中进行数千种类星体,并在六个宽带过滤器中进行主要调查。我们开发了广泛的模拟,考虑了LSST调查的特征和类星体的内在特性。这些模拟用于表征使用各种算法确定AD大小的光曲线。我们发现,对于光曲线,可以以5%的精度和15%的精度恢复时间延迟,分别抽样为2天和5天。结果在很大程度上取决于源的红移以及发射线对带通的相对贡献。假设光学厚和几何薄AD,回收的时间延迟频谱与衍生出30%不确定性的黑洞质量一致。
Photometric reverberation mapping can detect the radial extent of the accretion disc (AD) in Active Galactic Nuclei by measuring the time delays between light curves observed in different continuum bands. Quantifying the constraints on the efficiency and accuracy of the delay measurements is important for recovering the AD size-luminosity relation, and potentially using quasars as standard candles. We have explored the possibility of determining the AD size of quasars using next-generation Big Data surveys. We focus on the Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory, which will observe several thousand quasars with the Deep Drilling Fields and up to 10 million quasars for the main survey in six broadband filter during its 10-year operational lifetime. We have developed extensive simulations that take into account the characteristics of the LSST survey and the intrinsic properties of the quasars. The simulations are used to characterise the light curves from which AD sizes are determined using various algorithms. We find that the time delays can be recovered with an accuracy of 5 and 15% for light curves with a time sampling of 2 and 5 days, respectively. The results depend strongly on the redshift of the source and the relative contribution of the emission lines to the bandpasses. Assuming an optically thick and geometrically thin AD, the recovered time-delay spectrum is consistent with black hole masses derived with 30% uncertainty.