光度时间序列中选定的变异性检测技术的比较性能
Comparative performance of selected variability detection techniques in photometric time series
摘要：
光度测量容易出现系统误差，这对低幅度变化检测提出了挑战。为了寻找一种通用的变异检测技术，能够恢复广泛的变异类型，包括目前未知的，我们测试了18个统计特性量化散射和/或亮度测量之间的相关性。我们比较了它们在识别可变物体方面的性能，这些可变物体是用从长焦镜头到1米级的望远镜获得的，并在从几分钟到几十年的时间尺度上探测可变性。测试数据集包括127539个天体的光变曲线，其中包括1251个各种类型的变星，并代表了一系列经常在地面变率调查中发现的观测条件。真实数据由模拟补充。我们提出了一个组合的两个指数，一起恢复广泛的变化类型的光度数据，其特征在于各种各样的采样模式，光度精度，和百分比的离群值测量。第一个指标是震级测量值的四分位距（IQR），它对时间尺度的变化敏感，对离群值敏感。它可以由光变曲线方差与均方连续差之比（1/h）来补充，这在检测比观测之间的典型时间间隔更长的时间尺度上的变异性方面是有效的。可变物体比亮度相似的非可变物体具有更大的1/h和/或IQR值。变异性检测的另一种方法是使用主成分分析来组合许多变异性指数。我们提出了124个以前未知的变星的测试数据中发现的。
英文摘要：
Photometric measurements are prone to systematic errors presenting a challenge to low-amplitude variability detection. In search for a general-purpose variability detection technique able to recover a broad range of variability types including currently unknown ones, we test 18 statistical characteristics quantifying scatter and/or correlation between brightness measurements. We compare their performance in identifying variable objects in seven time series data sets obtained with telescopes ranging in size from a telephoto lens to 1m-class and probing variability on time-scales from minutes to decades. The test data sets together include lightcurves of 127539 objects, among them 1251 variable stars of various types and represent a range of observing conditions often found in ground-based variability surveys. The real data are complemented by simulations. We propose a combination of two indices that together recover a broad range of variability types from photometric data characterized by a wide variety of sampling patterns, photometric accuracies, and percentages of outlier measurements. The first index is the interquartile range (IQR) of magnitude measurements, sensitive to variability irrespective of a time-scale and resistant to outliers. It can be complemented by the ratio of the lightcurve variance to the mean square successive difference, 1/h, which is efficient in detecting variability on time-scales longer than the typical time interval between observations. Variable objects have larger 1/h and/or IQR values than non-variable objects of similar brightness. Another approach to variability detection is to combine many variability indices using principal component analysis. We present 124 previously unknown variable stars found in the test data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
