Abstract The active galactic nuclei (AGN) are among the most powerful sources with an inherent, pronounced and random variation of brightness. The randomness of their time series is so subtle as to blur the border between aperiodic fluctuations and noisy oscillations. This poses challenges to analysing of such time series because neither visual inspection nor pre-exisitng methods can identify well oscillatory signals in them. Thus, there is a need for an objective method for periodicity detection. Here we review our a new data analysis method that combines a two-dimensional correlation (2D) of time series with the powerful methods of Gaussian processes. To demonstrate the utility of this technique, we apply it to two example problems which were not exploited enough: damped rednoised artificial time series mimicking AGN time series and newly published observed time series of changing look AGN (CL AGN) NGC 3516. The method successfully detected periodicities in both types of time series. Identified periodicity of ~4 yr in NGC 3516 allows us to speculate that if the thermal instability formed in its accretion disc (AD) on a time scale resembling detected periodicity then AD radius could be ~0.0024 pc.

中文翻译：

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活动星系核时间序列周期性的二维相关分析

摘要 活动星系核 (AGN) 是最强大的源之一，具有固有的、显着的和随机的亮度变化。他们的时间序列的随机性非常微妙，以至于模糊了非周期性波动和嘈杂振荡之间的界限。这给分析此类时间序列带来了挑战，因为视觉检查和预先存在的方法都无法识别其中的良好振荡信号。因此，需要一种客观的周期性检测方法。在这里，我们回顾了一种新的数据分析方法，该方法将时间序列的二维相关性 (2D) 与高斯过程的强大方法相结合。为了演示该技术的实用性，我们将其应用于两个未被充分利用的示例问题：阻尼红噪声人工时间序列模仿 AGN 时间序列和新发布的观察到的变化外观 AGN (CL AGN) NGC 3516 时间序列。该方法成功检测了两种类型的时间序列中的周期性。在 NGC 3516 中确定的约 4 年的周期使我们能够推测，如果在类似于检测到的周期的时间尺度上在其吸积盘 (AD) 中形成的热不稳定性，那么 AD 半径可能是约 0.0024 pc。