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

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

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. First, we infer the distance and extinction to stars along sightlines toward 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 2D 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. sightlines toward the Dame et al. and Magnani et al. 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 ≈5%–6%, though this can beh igher for clouds at greater distances, due to the limitations of our single-cloud model.

Organisation(s)
Department of Astrophysics
External organisation(s)
Harvard-Smithsonian Center for Astrophysics, Lawrence Berkeley National Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Harvard University
Journal
The Astrophysical Journal
Volume
879
No. of pages
20
ISSN
0004-637X
DOI
https://doi.org/10.3847/1538-4357/ab2388
Publication date
07-2019
Peer reviewed
Yes
Austrian Fields of Science 2012
103003 Astronomy, 103004 Astrophysics
Keywords
ASJC Scopus subject areas
Astronomy and Astrophysics, Space and Planetary Science
Portal url
https://ucrisportal.univie.ac.at/en/publications/fa29ebf2-13fd-42d1-ae50-6e0af22b4226