Volume 647, March 2021
|Number of page(s)||1|
|Section||Interstellar and circumstellar matter|
|Published online||02 March 2021|
Charting nearby dust clouds using Gaia data only (Corrigendum)
Max Planck Institute for Astrophysics,
2 Ludwig-Maximilians-Universität, Geschwister-Scholl Platz 1, 80539 Munich, Germany
Key words: dust, extinction / local insterstellar matter / methods: data analysis / solar neighborhood / errata, addenda
In Table 1 we presented a comparison of different dust inference methods and their applications. The following corrections are in order for that table:
In the row labeled “parallax uncertainty,” all methods except Green et al. (2018) and Sale & Magorrian (2018) take the parallax uncertainty into account during data selection in addition to what is stated in the table. Hereby the term “parallax” may refer to both astrometric parallaxes, that is to say distance estimates derived from the angular displacement of stars due to the observers displacement, as well as photometric parallaxes, that is distances derived from spectra using stellar models.
In the column labeled “Kh et al. (2018b),” we misclassified the method of Rezaei Kh et al. (2018) as a 2D method. The method takes correlations in three dimensions into account similarly to Lallement et al. (2018), Sale & Magorrian (2018), and our own method. Furthermore, in the row “max voxel resolution” we stated the voxel resolution to be 200 pc, but it should be noted that the grid of this method is irregular and the voxel resolution is on average higher in angular direction. Thus 200 pc is the minimum voxel resolution for this method.
A corrected table is found below.
Comparison of the different dust inference methods with the one performed in this paper.
In our main text, in the second paragraph of the introduction we cite “Kh et al 2017,” which mistakenly refers to an IAU proceeding. The correct reference is Rezaei Kh et al. (2017).
- Green, G. M., Schlafly, E. F., Finkbeiner, D., et al. 2018, MNRAS, 478, 651 [NASA ADS] [CrossRef] [Google Scholar]
- Lallement, R., Capitanio, L., Ruiz-Dern, L., et al. 2018, A&A, 616, A132 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Rezaei Kh, S., Bailer-Jones, C., Hanson, R., & Fouesneau, M. 2017, A&A, 598, A125 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Rezaei Kh, S., Bailer-Jones, C. A., Hogg, D. W., & Schultheis, M. 2018, A&A, 618, A168 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Sale, S., & Magorrian, J. 2018, MNRAS, 481, 494 [NASA ADS] [CrossRef] [Google Scholar]
© R. H. Leike and T. A. Enßlin 2021
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Open Access funding provided by Max Planck Society.
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