GRAPE：天文周期估算的遗传程序
GRAPE: Genetic Routine for Astronomical Period Estimation
摘要：
周期估计是许多可变天体分类中的一项重要任务。在这里，我们介绍葡萄：用于天文周期估计的遗传例程，一种遗传算法，用于处理具有虚假和混叠伪像的测量数据。它使用贝叶斯广义Lomb-Scargle（BGLS）健身功能，旨在与利物浦望远镜进行的Skycam调查一起使用。我们构建了一组模拟光变曲线使用常规和Skycam调查节奏与四种类型的信号：正弦，双，对称食二进制和偏心食二进制。我们将GRAPE和BGLS周期图应用于这些数据，并表明GRAPE的性能优于正弦和正弦光变曲线上的周期图，相对命中率分别提高了18.2%和6.4%。对称食双星和偏心食双星的光变曲线在两种方法上的表现相似。我们表明，Skycam的节奏是足够的，以正确地估计所有的正弦曲线形状的光变曲线的周期，虽然这降低与非正弦形状的增加，对称二进制和偏心二进制光变曲线分别下降了20%，30%和35%。GRAPE的运行时间表明，具有超过500-1000个数据点的光变曲线在更少的计算时间内实现了类似的性能。GRAPE性能可以通过具有过采样微调网格的频谱来匹配，代价是运行时间几乎加倍。最后，我们提出了改进，这将扩大这种方法的准周期信号的检测和使用的多波段光变曲线。
英文摘要：
Period estimation is an important task in the classification of many variable astrophysical objects. Here we present GRAPE: Genetic Routine for Astronomical Period Estimation, a genetic algorithm optimised for the processing of survey data with spurious and aliased artefacts. It uses a Bayesian Generalised Lomb-Scargle (BGLS) fitness function designed for use with the Skycam survey conducted at the Liverpool Telescope. We construct a set of simulated light curves using both regular and Skycam survey cadence with four types of signal: sinusoidal, sawtooth, symmetric eclipsing binary and eccentric eclipsing binary. We apply GRAPE and a BGLS periodogram to this data and show that the performance of GRAPE is superior to the periodogram on sinusoidal and sawtooth light curves with relative hit rate improvement of 18.2% and 6.4% respectively. The symmetric and eccentric eclipsing binary light curves have similar performance on both methods. We show the Skycam cadence is sufficient to correctly estimate the period for all of the sinusoidal shape light curves although this degrades with increased non-sinusoidal shape with sawtooth, symmetric binary and eccentric binary light curves down by 20%, 30% and 35% respectively. The runtime of GRAPE demonstrates that light curves with more than 500-1000 data points achieve similar performance in less computing time. The GRAPE performance can be matched by a frequency spectrum with an oversampled fine-tuning grid at the cost of almost doubling the runtime. Finally, we propose improvements which will extend this method to the detection of quasi-periodic signals and the use of multiband light curves.
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