论文标题
用微弱的银河系星星映射盖亚(Gaia)视差在天空上的系统错误
Mapping Gaia parallax systematic errors over the sky with faint Milky Way stars
论文作者
论文摘要
通过Gaia任务测量的视差对天文学具有很大的意义,但是Gaia Dr2中的视差却具有取决于源位置和其他数量的系统误差。我们以微弱的银河系恒星以及GAIA目录的GOG模拟来探测Gaia Dr2 Dr2视差系统误差的空间依赖。视差信号集中在厚度g〜17的厚磁盘转弯恒星中,足以构建大多数天空中的视差系统误差的地图。这些地图按照Gaia扫描方向,更强的线性“疤痕”特征以及在较大尺度上的相干变化,在〜1度尺度上显示了局部规则的“华夫饼模式”。视差偏置图还保留了天体物理效应的痕迹,例如尘埃云。华夫饼模式从麦哲伦云的早期地图中知道,延伸到整个天空上。其局部RMS幅度平均为15 microarcsec,并且变化约为两个。该模式的强度从g = 13到g = 20的幅度增加了一个因子〜6。与类星体的视差和具有独立距离估计的恒星的相关性支持我们的偏置估计值。使用类似的方法,我们在正确的运动中绘制系统错误,并检查与视差系统的关系。我们提供一个代码包来访问和查询我们的偏差图。对普通恒星种群的类似测试应有助于量化未来盖亚版本中的系统错误。
Parallaxes measured by the Gaia mission have huge significance for astronomy, but parallaxes in Gaia DR2 are known to have systematic errors that depend on the source position and other quantities. We use the abundant information in faint Milky Way stars, along with the GOG simulation of the Gaia catalog, to probe the spatial dependence of Gaia DR2 parallax systematic errors in an empirical way. The parallax signal, concentrated in thick disk turnoff stars with magnitude G ~ 17, is sufficient to construct maps of the parallax systematic error over the majority of the sky. These maps show a locally regular "waffle pattern" on ~1 degree scales following Gaia scan directions, stronger linear "scar" features, and coherent variations on larger scales. The parallax bias maps also retain traces of astrophysical effects such as dust clouds. The waffle pattern, known from earlier maps of the Magellanic Clouds, extends over the entire sky; its local rms amplitude averages 15 microarcsec and varies by about a factor of two. The strength of this pattern increases by a factor ~6 from magnitude G = 13 to G = 20. Correlations with parallaxes of quasars and of stars with independent distance estimates support our bias estimates. Using similar methods, we map systematic errors in the proper motion and examine the relationship with the parallax systematics. We provide a code package to access and query our bias maps. Similar tests on the general stellar population should be useful in quantifying systematic errors in future Gaia releases.