4.7 Article

A 3D Dust Map Based on Gaia, Pan-STARRS 1, and 2MASS

期刊

ASTROPHYSICAL JOURNAL
卷 887, 期 1, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.3847/1538-4357/ab5362

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资金

  1. IDEX Paris-Saclay [ANR-11-IDEX-0003-02]
  2. NASA through ADAP [NNH17AE75I]
  3. Space Telescope Science Institute [HST-HF2-51367.001-A, NAS 5-26555]
  4. NSF [AST-1614941]
  5. National Aeronautics and Space Administration [NNX08AR22G]
  6. National Science Foundation [AST-1238877]
  7. National Aeronautics and Space Administration
  8. National Science Foundation
  9. FAS Division of Science, Research Computing Group at Harvard University

向作者/读者索取更多资源

We present a new three-dimensional map of dust reddening, based on Gaia parallaxes and stellar photometry from Pan-STARRS 1 and 2MASS. This map covers the sky north of a decl. of -30 degrees, out to a distance of a few kiloparsecs. This new map contains three major improvements over our previous work. First, the inclusion of Gaia parallaxes dramatically improves distance estimates to nearby stars. Second, we incorporate a spatial prior that correlates the dust density across nearby sightlines. This produces a smoother map, with more isotropic clouds and smaller distance uncertainties, particularly to clouds within the nearest kiloparsec. Third, we infer the dust density with a distance resolution that is four times finer than in our previous work, to accommodate the improvements in signal-to-noise enabled by the other improvements. As part of this work, we infer the distances, reddenings, and types of 799 million stars. (Our 3D dust map can be accessed at doi:10.7910/DVN/2EJ9TX.or through the Python package dustmaps, while our catalog of stellar parameters can be accessed at doi:10.7910/DVN/AV9GXO. More information about the map, as well as an interactive viewer, can be found at.argonaut.skymaps.info.) We obtain typical reddening uncertainties that are similar to 30% smaller than those reported in the Gaia DR2 catalog, reflecting the greater number of photometric passbands that enter into our analysis.

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