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arXiv 1902.01425astro-ph.GA
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到局部分子云精确距离的大型星表:盖亚DR2版

A Large Catalog of Accurate Distances to Local Molecular Clouds: The Gaia DR2 Edition

Catherine Zucker, Joshua S. Speagle, Edward F. Schlafly, Gregory M. Green, Douglas P. Finkbeiner, Alyssa A. Goodman, João Alves

摘要:

我们提出了一个统一的目录,准确的距离本地分子云通知盖亚DR 2数据发布。我们的方法建立在Schlafly et al.(2014)的基础上。首先,我们推断的距离和消光恒星沿视线对云使用光学和近红外测光。当可用时,我们将从盖亚DR 2视差测量获得的恒星距离的知识。我们将这些每星距离消光估计建模为由来自普朗克的2-D形态的尘埃屏在未知距离处引起的,然后我们使用嵌套采样算法进行拟合。我们提供了Schlafly et al.(2014)的视线到Dame et al.(2001)和Magnani et al.(1985)云的更新距离,发现与早期的工作非常一致。对于27个云的子集,我们构建交互式像素化的距离地图,以进一步研究详细的云结构,并找到几个云显示清晰的距离梯度和/或由多个组件。我们使用这些地图来确定到这些云的鲁棒平均距离。我们的距离的特征组合不确定性约为5- 6%,尽管由于我们的单云模型的限制,对于更远距离的云,这可能更高。

英文摘要:

We present a uniform catalog of accurate distances to local molecular clouds informed by the Gaia DR2 data release. Our methodology builds on that of Schlafly et al. (2014). First, we infer the distance and extinction to stars along sightlines towards the clouds using optical and near-infrared photometry. When available, we incorporate knowledge of the stellar distances obtained from Gaia DR2 parallax measurements. We model these per-star distance-extinction estimates as being caused by a dust screen with a 2-D morphology derived from Planck at an unknown distance, which we then fit for using a nested sampling algorithm. We provide updated distances to the Schlafly et al. (2014) sightlines towards the Dame et al. (2001) and Magnani et al. (1985) clouds, finding good agreement with the earlier work. For a subset of 27 clouds, we construct interactive pixelated distance maps to further study detailed cloud structure, and find several clouds which display clear distance gradients and/or are comprised of multiple components. We use these maps to determine robust average distances to these clouds. The characteristic combined uncertainty on our distances is approximately 5-6%, though this can be higher for clouds at farther distances, due to the limitations of our single-cloud model.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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