Deep Modeling of Quasar Variability
Deep Modeling of Quasar Variability
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DOI：
10.3847/1538-4357/abb9a9
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发表时间：
2020-03
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通讯作者：
Yutaro 朗橘 Tachibana 優太;M. Graham;N. Kawai;S. Djorgovski;A. Drake;A. Mahabal;D. Stern
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作者：
Yutaro 朗橘 Tachibana 優太;M. Graham;N. Kawai;S. Djorgovski;A. Drake;A. Mahabal;D. Stern
类星体长期以来一直被认为是内变源，但时间光学/紫外光变率的物理机制仍然没有得到很好的理解。我们提出了一种新的非参数方法建模和预测的光学变化的类星体利用AE神经网络洞察到的基本过程。AE是用卡塔利纳实时瞬态巡天获得的15,000个十年长的类星体光变曲线训练的，这些光变曲线是在宿主星系的通量污染可以忽略不计的情况下选择的。AE对类星体流量随时间变化的预测性能上级阻尼随机游走过程。我们发现一个时间上的不对称性的光学可变性和一个新的关系的振幅的可变性不对称性的亮度和/或黑洞质量的增加而减少建议与自动编码功能的帮助。的变化不对称的特性是一致的，从自组织磁盘不稳定性模型，它预测的变化不对称的幅度减小的吸积盘中的扩散质量流入质量的比例增加。
Quasars have long been known as intrinsically variable sources, but the physical mechanism underlying the temporal optical/UV variability is still not well understood. We propose a novel nonparametric method for modeling and forecasting the optical variability of quasars utilizing an AE neural network to gain insight into the underlying processes. The AE is trained with ∼15,000 decade-long quasar light curves obtained by the Catalina Real-time Transient Survey selected with negligible flux contamination from the host galaxy. The AE’s performance in forecasting the temporal flux variation of quasars is superior to that of the damped random walk process. We find a temporal asymmetry in the optical variability and a novel relation—the amplitude of the variability asymmetry decreases as luminosity and/or black hole mass increases—is suggested with the help of autoencoded features. The characteristics of the variability asymmetry are in agreement with those from the self-organized disk instability model, which predicts that the magnitude of the variability asymmetry decreases as the ratio of the diffusion mass to inflow mass in the accretion disk increases.