揭示噪声和不规则采样时间序列中的延迟模式：天文学应用
Uncovering delayed patterns in noisy and irregularly sampled time series: an astronomy application
摘要：
我们研究的问题，估计两个信号之间的时间延迟表示延迟，不规则采样和嘈杂的版本相同的基本模式。我们提出并证明了一个进化算法的（超）参数估计的内核为基础的技术的背景下，天文问题，即估计两个引力透镜信号之间的时间延迟从遥远的类星体。混合类型（整数和实数）用于表示进化算法中的变量。我们测试了几个人工数据集上的算法，也对类星体Q0957+561的真实天文观测。通过对结果进行统计分析，我们提出了一个详细的比较，我们的方法与最流行的方法在天体物理学的时间延迟估计。我们的方法产生了更准确和更稳定的时间延迟估计：对于Q0957+561，我们获得了图像A和B之间的时间延迟为419.6天。我们的方法可以很容易地应用到当前国家的最先进的天文学光学监测数据，但也可以应用于其他学科涉及类似的时间序列数据。
英文摘要：
We study the problem of estimating the time delay between two signals representing delayed, irregularly sampled and noisy versions of the same underlying pattern. We propose and demonstrate an evolutionary algorithm for the (hyper)parameter estimation of a kernel-based technique in the context of an astronomical problem, namely estimating the time delay between two gravitationally lensed signals from a distant quasar. Mixed types (integer and real) are used to represent variables within the evolutionary algorithm. We test the algorithm on several artificial data sets, and also on real astronomical observations of quasar Q0957+561. By carrying out a statistical analysis of the results we present a detailed comparison of our method with the most popular methods for time delay estimation in astrophysics. Our method yields more accurate and more stable time delay estimates: for Q0957+561, we obtain 419.6 days for the time delay between images A and B. Our methodology can be readily applied to current state-of-the-art optical monitoring data in astronomy, but can also be applied in other disciplines involving similar time series data.
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