论文标题

Gaia-verse II的完整性:Gaia DR2缺少恒星的几率是多少?

Completeness of the Gaia-verse II: what are the odds that a star is missing from Gaia DR2?

论文作者

Boubert, Douglas, Everall, Andrew

论文摘要

Gaia任务的第二个数据发布包含了令人难以置信的1,692,919,135来源的天文学和光度法,但是Gaia错过了多少源,它们躺在哪里?这个问题的答案对于任何试图与Gaia DR2绘制银河系的天文学家至关重要。我们通过利用它仅包含至少五个星体检测的来源的事实来推断Gaia Dr2的完整性。源实现这五个检测的几率取决于观察次数和观察到该来源导致检测的可能性。我们预测盖亚观察到每个源的次数,并假设检测的概率是幅度级的函数或分布作为数量级的函数。我们将这两个模型拟合到Gaia Dr2的17亿颗恒星,因此能够坚固地预测Gaia在天空中的完整性,这是幅度的函数。我们扩展了选择功能,以说明天空茂密地区的拥挤,并表明这至关重要,尤其是在银河凸起和大小的麦哲伦云中。我们发现,盖亚(Gaia)仍然99%的幅度​​限制在天空中从$ g = 18.9 $到$ 21.3 $不等。我们创建了一个新的Python软件包选择功能(https://github.com/gaiaverse/selectionfunctions),可轻松访问我们的选择功能。

The second data release of the Gaia mission contained astrometry and photometry for an incredible 1,692,919,135 sources, but how many sources did Gaia miss and where do they lie on the sky? The answer to this question will be crucial for any astronomer attempting to map the Milky Way with Gaia DR2. We infer the completeness of Gaia DR2 by exploiting the fact that it only contains sources with at least five astrometric detections. The odds that a source achieves those five detections depends on both the number of observations and the probability that an observation of that source results in a detection. We predict the number of times that each source was observed by Gaia and assume that the probability of detection is either a function of magnitude or a distribution as a function of magnitude. We fit both these models to the 1.7 billion stars of Gaia DR2, and thus are able to robustly predict the completeness of Gaia across the sky as a function of magnitude. We extend our selection function to account for crowding in dense regions of the sky, and show that this is vitally important, particularly in the Galactic bulge and the Large and Small Magellanic Clouds. We find that the magnitude limit at which Gaia is still 99% complete varies over the sky from $G=18.9$ to $21.3$. We have created a new Python package selectionfunctions (https://github.com/gaiaverse/selectionfunctions) which provides easy access to our selection functions.

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