论文标题
类星体可变性的深层建模
Deep modeling of quasar variability
论文作者
论文摘要
长期以来，类星体一直被称为本质上可变源，但是暂时光学/紫外线变异性的物理机制仍然不太了解。我们提出了一种新型的非参数方法，用于使用自动编码器神经网络对类星体的光学变异进行建模和预测，以深入了解基础过程。自动编码器经过约15,000个十年长的类星体光曲线的训练，该曲线是由Catalina实时瞬态调查获得的，从宿主银河系中选择可忽略不计的通量污染。自动编码器在预测类星体的时间通量变化方面的性能优于阻尼随机行走过程。我们发现在光学变异性和新型关系中存在时间不对称性 - 借助自动编码的特征，建议建议变异性不对称性的幅度随着亮度和/或黑洞质量的增加而降低。变异性不对称的特征与自组织磁盘不稳定性模型的特征一致，这预测，随着扩散质量与增生盘的流入量的比率增加，可变性不对称性的幅度会降低。
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 autoencoder neural network to gain insight into the underlying processes. The autoencoder 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 autoencoder'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.
