用多频周期图- II检测观测数据中的多个周期。频率分解器，一个并行化的时间序列分析算法
Detecting multiple periodicities in observational data with the multifrequency periodogram - II. Frequency Decomposer, a parallelized time-series analysis algorithm
摘要：
这是一种并行算法，可将噪声时间序列分解为多个正弦分量。该算法分析了所有可以发现的可疑周期，包括那些一眼看起来像别名或噪声，但后来可能被证明是真实变化的周期。在选择初始候选者之后，该算法对所有可能的组合执行完整的遍历，并计算每个这样的频率元组的严格的多频率统计显著性。仍然存活于该阈值程序的最大组合代表分析的结果。通过CUDA实现了图形处理器（GPU）上的并行计算，并带来了显着的性能提升。当没有合适的GPU设备可用时，仍然可以在传统的单线程模式下仅在CPU上运行FREDEC。为了验证我们的算法的实用性，我们将其应用到人工时间序列以及一些现实生活中的系外行星径向速度数据。我们证明，FREDEC可以成功地揭示几个已知的系外行星。此外，它还发现了一个新的$9.8$日变化的利克数据的五行星系统的55数控。这可能表明在与行星55 Cnc b的3：2重合度中存在第六颗小行星，尽管这一探测依赖于模型，仍然需要详细的验证。
英文摘要：
This is a parallelized algorithm performing a decomposition of a noisy time series into a number of sinusoidal components. The algorithm analyses all suspicious periodicities that can be revealed, including the ones that look like an alias or noise at a glance, but later may prove to be a real variation. After selection of the initial candidates, the algorithm performs a complete pass through all their possible combinations and computes the rigorous multifrequency statistical significance for each such frequency tuple. The largest combinations that still survived this thresholding procedure represent the outcome of the analysis. The parallel computing on a graphics processing unit (GPU) is implemented through CUDA and brings a significant performance increase. It is still possible to run FREDEC solely on CPU in the traditional single-threaded mode, when no suitable GPU device is available. To verify the practical applicability of our algorithm, we apply it to an artificial time series as well as to some real-life exoplanetary radial-velocity data. We demonstrate that FREDEC can successfully reveal several known exoplanets. Moreover, it detected a new $9.8$-day variation in the Lick data for the five-planet system of 55 Cnc. It might indicate the existence of a small sixth planet in the 3:2 commensurability with the planet 55 Cnc b, although this detection is model-dependent and still needs a detailed verification.
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。
