论文标题
Markov Chain Monte Carlo和遗传算法的Gaia DR3天文轨道测定。具有恒星,替代和行星群众伴侣的系统
Gaia DR3 astrometric orbit determination with Markov Chain Monte Carlo and Genetic Algorithms. Systems with stellar, substellar, and planetary mass companions
论文作者
论文摘要
由于所需的子米利亚克(Subiliarcsond)精确度,因此绕行星星的星体发现非常困难,因此将该技术的应用限制在目标的基础上,以及全球的星际统计空间任务Hipparcos和Gaia。第三个GAIA数据发布包括第一个Gaia Astrestoric轨道溶液,其在估计的伴侣质量方面的敏感性延伸到行星质量状态。我们通过描述用于拟合轨道的方法,大量溶液的识别及其验证的方法来介绍“系外行李箱”对天体轨道溶液的Gaia DR3样本的贡献。然后,我们介绍解决方案参数的统计属性。使用Markov链蒙特卡洛和遗传算法,我们将与单个开普勒式星体轨道模型一起拟合34个月的Gaia DR3星体时间序列。使用显着性测试,使用Gaia径向速度测量值(如果有)进行内部一致性检查(在可用的情况下)以及文献径向速度和天文数据,从而导致一组被标记为“验证”的候选者,则进行了验证和验证步骤。我们确定了1162个来源的天体轨道解决方案,并为“验证”标签分配了198个解决方案。精确的伴侣质量估计在其他地方介绍。根据内部和外部验证和验证,我们估计样本中的虚假/不正确解决方案的水平在我们的非录音“候选样本中为约5-10%。我们证明,盖亚能够确认,有时还可以完善已知的轨道伴侣轨道以及确定新的候选者,从而为我们提供了从未来数据发布中的完整任务数据中对预期收获的积极前景。
Astrometric discovery of sub-stellar mass companions orbiting stars is exceedingly hard due to the required sub-milliarcsecond precision, limiting the application of this technique to only a few instruments on a target-per-target basis as well as the global astrometry space missions Hipparcos and Gaia. The third Gaia data release includes the first Gaia astrometric orbital solutions, whose sensitivity in terms of estimated companion mass extends down into the planetary-mass regime. We present the contribution of the `exoplanet pipeline' to the Gaia DR3 sample of astrometric orbital solutions by describing the methods used for fitting the orbits, the identification of significant solutions, and their validation. We then present an overview of the statistical properties of the solution parameters. Using both a Markov Chain Monte Carlo and Genetic Algorithm we fit the 34 months of Gaia DR3 astrometric time series with a single Keplerian astrometric-orbit model. Verification and validation steps are taken using significance tests, internal consistency checks using the Gaia radial velocity measurements (when available), as well as literature radial velocity and astrometric data, leading to a subset of candidates that are labelled as 'validated'. We determined astrometric-orbit solutions for 1162 sources and 198 solutions have been assigned the 'validated' label. Precise companion mass estimates are presented elsewhere. From internal and external verification and validation we estimate the level of spurious/incorrect solutions in our sample to be of the order of ~5-10% in our non-'validated' candidate samples. We demonstrate that Gaia is able to confirm and sometimes refine known orbital companion orbits as well as identify new candidates, providing us with a positive outlook of the expected harvest from the full mission data in future data releases.