论文标题
表征Gaia径向速度样品选择功能在其天然光度法中
Characterising the Gaia Radial Velocity sample selection function in its native photometry
论文作者
论文摘要
GAIA DR2径向速度样品（GDR2RVS）在720万颗恒星上提供了六维相位信息，对于推断银河系的性质具有很大的价值。然而，该样品的定量和准确的建模受到阻碍，而没有知识和包含良好的选择函数。在这里，我们通过对内部完整性的估计来得出选择函数，即与所有GAIA DR2源（GDR2ALL）相比，GDR2RVS源的比率。我们表明，这种选择函数或“完整性”取决于基本可观察到的物品，特别是明显的GRV和颜色G-GRP，但也取决于周围的源密度和天空位置，完整性表现出独特的小规模结构。我们确定一个具有很高完整性的大小和颜色区域，提供了实现选择功能的近似但简单的方式。对于更严格，更详细的说明，我们提供了Python代码来查询我们的选择功能，以及具有额外质量削减的自定义选择功能的工具和ADQL查询。
The Gaia DR2 radial velocity sample (GDR2RVS), which provides six-dimensional phase-space information on 7.2 million stars, is of great value for inferring properties of the Milky Way. Yet a quantitative and accurate modelling of this sample is hindered without knowledge and inclusion of a well-characterized selection function. Here we derive the selection function through estimates of the internal completeness, i.e. the ratio of GDR2RVS sources compared to all Gaia DR2 sources (GDR2all). We show that this selection function or "completeness" depends on basic observables, in particular the apparent magnitude GRVS and colour G-GRP, but also on the surrounding source density and on sky position, where the completeness exhibits distinct small-scale structure. We identify a region of magnitude and colour that has high completeness, providing an approximate but simple way of implementing the selection function. For a more rigorous and detailed description we provide python code to query our selection function, as well as tools and ADQL queries that produce custom selection functions with additional quality cuts.
