天文学进展2016，Vol.34Issue(1)：74-93,20.DOI:10.3969/j.issn.1000-8349.2016.01.05
天文光变周期提取算法综述
Review of Periodicity Searching Algorithms of Astronomical Light Curves
摘要
Abstract
In astronomy, large amounts of light curve data have been accumulated as the development of increasing number of survey projects. The research of those light curve data is vital as they carry plenty of information about many important physical parameters. The study on the variability of light curve, for example, is very helpful for understanding the physical mechanism of light curves, forecasting outbursts, estimating celestial ob ject mass and so on. Traditional variability study based on Fourier transform works well for time series data that are equally spaced in time, while that is not necessarily the case for light curve data since they are usually unevenly sampled due to various factors such as the dynamics of celestial ob jects, observational and instrumental condition and so on. Besides, light curve data are normally affected by noise to various extent. Therefore, algorithms based on uneven sampling ought to be explored and applied for the study of light curves. This paper summarizes the three types of numerical techniques for identifying periodicity of light curves in frequency domain, time domain and time-frequency domain, which mainly includes Lomb-Scargle periodogram, Jurkevich method, Weighted Wavelet Z Transformation, and so on. The performance of those algorithms is analyzed and the advantages and drawbacks of each of them are reviewed. A conclusion and discussion is provided in the end based on the analysis and comparison of the above algorithms.关键词
非均匀采样时间序列/周期/频域/时域/时-频域Key words
unevenly spaced time series/periodicity/frequency-domain/time-domain/time-frequency domain分类
天文学引用本文复制引用
安涛,王俊义,陆相龙,劳保强,魏延恒,董典桥,陆扬,伍筱聪..天文光变周期提取算法综述[J].天文学进展,2016,34(1):74-93,20.基金项目
科技部政府间科技合作专项"SKA 科学数据处理关键技术研究" （）
科技部973 项目"SKA 建设准备阶段关键问题研究"(2013CB837900) （2013CB837900）
