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arXiv 2209.13992astro-ph.EPastro-ph.IMastro-ph.SR
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利用傅立叶分析确定轨道要素。II。盖亚天体测量学及其与径向速度的组合

Analytical determination of orbital elements using Fourier analysis. II. Gaia astrometry and its combination with radial velocities

J. -B. Delisle, D. Ségransan

摘要:

自2014年以来,欧空局的全球天体测量太空任务盖亚一直在监测10亿颗恒星的位置。分析如此庞大的数据集在所涉及的数据处理方面具有挑战性。特别是,使用盖亚天体测量法对恒星的单个或多个伴星(行星、棕矮星或恒星)进行盲检测和表征需要高效的算法。在这篇文章中,我们提出了一套分析方法来检测和表征同伴在扫描空间天体测量时间序列,以及通过结合天体测量和径向速度时间序列。我们提出了一个一般的线性周期图框架,我们推导出周期图峰值的虚警概率(FAP)的解析公式。一旦一个显着的峰值已被确定,我们提供分析估计的基础上的信号的傅立叶分解的同伴的所有轨道要素。周期图,FAP,和轨道要素的估计可以计算的天体测量和径向速度时间序列单独或串联。这些方法与更精确和计算更密集的数值算法(例如,最小二乘最小化,马尔可夫链蒙特卡罗,遗传算法)。特别是,我们的分析近似可以用作初始条件,以加速数值算法的收敛。我们的形式主义已经在第三次盖亚数据发布的盖亚系外行星管道中部分实现。由于盖亚天体测量时间序列尚未公开,我们说明了我们的方法的基础上依巴谷数据,连同地面CORALIE径向速度,为三个目标已知主机的同伴:HD 223636(HIP 117622),HD 17289(HIP 12726),和HD 3277(HIP 2790)。

英文摘要:

The ESA global astrometry space mission Gaia has been monitoring the position of a billion stars since 2014. The analysis of such a massive dataset is challenging in terms of the data processing involved. In particular, the blind detection and characterization of single or multiple companions to stars (planets, brown dwarfs, or stars) using Gaia astrometry requires highly efficient algorithms. In this article, we present a set of analytical methods to detect and characterize companions in scanning space astrometric time series as well as via a combination of astrometric and radial velocity time series. We propose a general linear periodogram framework and we derive analytical formulas for the false alarm probability (FAP) of periodogram peaks. Once a significant peak has been identified, we provide analytical estimates of all the orbital elements of the companion based on the Fourier decomposition of the signal. The periodogram, FAP, and orbital elements estimates can be computed for the astrometric and radial velocity time series separately or in tandem. These methods are complementary with more accurate and more computationally intensive numerical algorithms (e.g., least-squares minimization, Markov chain Monte Carlo, genetic algorithms). In particular, our analytical approximations can be used as an initial condition to accelerate the convergence of numerical algorithms. Our formalism has been partially implemented in the Gaia exoplanet pipeline for the third Gaia data release. Since the Gaia astrometric time series are not yet publicly available, we illustrate our methods on the basis of Hipparcos data, together with on-ground CORALIE radial velocities, for three targets known to host a companion: HD 223636 (HIP 117622), HD 17289 (HIP 12726), and HD 3277 (HIP 2790).

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。

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