Volume 633, January 2020
|Number of page(s)||16|
|Section||Catalogs and data|
|Published online||10 January 2020|
Center for Astrophysics | Harvard & Smithsonian, 60 Garden St., Cambridge, MA 02138, USA
e-mail: firstname.lastname@example.org, email@example.com
2 Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
3 Kavli Institute for Particle Astrophysics and Cosmology, Physics and Astrophysics Building, 452 Lomita Mall, Stanford, CA 94305, USA
4 University of Vienna, Department of Astrophysics, Türkenschanzstraße 17, 1180 Vienna, Austria
5 Radcliffe Institute for Advanced Study, Harvard University, 10 Garden St, Cambridge, MA 02138, USA
Accepted: 12 August 2019
Accurate distances to local molecular clouds are critical for understanding the star and planet formation process, yet distance measurements are often obtained inhomogeneously on a cloud-by-cloud basis. We have recently developed a method that combines stellar photometric data with Gaia DR2 parallax measurements in a Bayesian framework to infer the distances of nearby dust clouds to a typical accuracy of ∼5%. After refining the technique to target lower latitudes and incorporating deep optical data from DECam in the southern Galactic plane, we have derived a catalog of distances to molecular clouds in Reipurth (2008, Star Formation Handbook, Vols. I and II) which contains a large fraction of the molecular material in the solar neighborhood. Comparison with distances derived from maser parallax measurements towards the same clouds shows our method produces consistent distances with ≲10% scatter for clouds across our entire distance spectrum (150 pc−2.5 kpc). We hope this catalog of homogeneous distances will serve as a baseline for future work.
Key words: local insterstellar matter / solar neighborhood / catalogs
Table A.1 is also available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (184.108.40.206) or via http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/633/A51. It is also available on the Harvard Dataverse at https://doi.org/10.7910/DVN/07L7YZ
An interactive 3D version of Fig. 2 is available at https://www.aanda.org
© ESO 2020
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