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A Gaia Early DR3 Mock Stellar Catalog: Galactic Prior and Selection Function

机译:A Gaia早期DR3模拟Stellar目录:银河预先和选择功能

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We present a mock stellar catalog, matching in volume, depth and data model the content of the planned Gaia early data release 3 (Gaia EDR3). We have generated our catalog (GeDR3mock) using galaxia, a tool to sample stars from an underlying Milky Way (MW) model or from N-body data. We used an updated Besancon Galactic model together with the latest PARSEC stellar evolutionary tracks, now also including white dwarfs. We added the Magellanic clouds and realistic open clusters with internal rotation. We empirically modeled uncertainties based on Gaia DR2 (GDR2) and scaled them according to the longer baseline in Gaia EDR3. The apparent magnitudes were reddened according to a new selection of 3D extinction maps. To help with the Gaia selection function we provide all-sky magnitude limit maps in G and BP for a few relevant GDR2 subsets together with the routines to produce these maps for user-defined subsets. We supplement the catalog with photometry and extinctions in non-Gaia bands. The catalog is available in the Virtual Observatory () and can be queried just like the actual Gaia EDR3 will be. We highlight a few capabilities of the Astronomy Data Query Language with educative catalog queries. We use the data extracted from those queries to compare GeDR3mock to GDR2, which emphasises the importance of adding observational noise to the mock data. Since the underlying truth, e.g., stellar parameters, is know in GeDR3mock, it can be used to construct priors as well as mock data tests for parameter estimation. All code, models and data used to produce GeDR3mock are linked and contained in galaxia_wrap (), a python package, representing a fast galactic forward model, able to project MW models and N-body data into realistic Gaia observables.
机译:我们展示了一个模拟的恒星目录,匹配卷,深度和数据模型计划的Gaia早期数据版本3的内容(Gaia EDR3)。我们已经使用Galaxia生成了我们的目录(GEDR3Mock),该工具是从底层银河系(MW)模型或N身体数据的样本星星的工具。我们使用了一个更新的BEANCON银河模型以及最新的Parsec Stellar进化轨道,现在也包括白矮星。我们在内部旋转中添加了麦哲伦云和现实的开放集群。我们基于Gaia Dr2(GDR2)的经验上建模的不确定性,并根据Gaia EDR3中的较长基线缩放它们。根据一系列3D消光图的新选择,表观幅度被打红了。为了帮助Gaia选择功能,我们将G和BP中的全天幅度限制映射与例程一起提供一些相关的GDR2子集,以为用户定义的子集生产这些地图。我们在非Gaia带中的光度测定和灭绝补充目录。目录在虚拟观察台()中可用,可以像实际的盖亚EDR3一样查询。我们突出了带有教育目录查询的天文数据查询语言的一些功能。我们使用从那些查询中提取的数据将GEDR3Mock与GDR2进行比较,这强调向模拟数据添加观察噪声的重要性。由于基础事实,例如恒星参数,在GEDR3Mock中知道,它可以用于构建前沿以及用于参数估计的模拟数据测试。用于生成GEDR3Mock的所有代码,模型和数据都包含在Galaxia_Wrap()中包含的Python封装,代表快速的银河前向模型,能够将MW模型和N-Body数据投影成现实的Gaia可观察到。

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    Max Planck Inst Astron Konigstuhl 17 D-69117 Heidelberg Germany;

    Heidelberg Univ Astron Rechen Inst Zentrum Astron Monchhofstr 12-14 D-69120 Heidelberg Germany;

    Max Planck Inst Astron Konigstuhl 17 D-69117 Heidelberg Germany;

    Osservatorio Astron Padova INAF Vicolo Osservatorio 5 I-35122 Padua Italy;

    Univ Barcelona IEEC UB Inst Ciencies Cosmos Marti &

    Franques 1 E-08028 Barcelona Spain;

    Max Planck Inst Astron Konigstuhl 17 D-69117 Heidelberg Germany;

    Univ Padua Dipartimento Fis &

    Astron Galileo Galilei Vicolo Osservatorio 3 I-35122 Padua Italy;

    Max Planck Inst Astron Konigstuhl 17 D-69117 Heidelberg Germany;

    Osservatorio Astron Padova INAF Vicolo Osservatorio 5 I-35122 Padua Italy;

    Univ Sydney Sch Phys Sydney Inst Astron Sydney NSW 2006 Australia;

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