Open Access
Erratum
This article is an erratum for:
[https://doi.org/10.1051/0004-6361/201935093]


Issue
A&A
Volume 647, March 2021
Article Number C1
Number of page(s) 1
Section Interstellar and circumstellar matter
DOI https://doi.org/10.1051/0004-6361/201935093e
Published online 02 March 2021

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.

Table 1

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).

References

  1. Green, G. M., Schlafly, E. F., Finkbeiner, D., et al. 2018, MNRAS, 478, 651 [Google Scholar]
  2. Lallement, R., Capitanio, L., Ruiz-Dern, L., et al. 2018, A&A, 616, A132 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  3. Rezaei Kh, S., Bailer-Jones, C., Hanson, R., & Fouesneau, M. 2017, A&A, 598, A125 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  4. Rezaei Kh, S., Bailer-Jones, C. A., Hogg, D. W., & Schultheis, M. 2018, A&A, 618, A168 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Sale, S., & Magorrian, J. 2018, MNRAS, 481, 494 [Google Scholar]

© R. H. Leike and T. A. Enßlin 2021

Licence Creative Commons
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.

All Tables

Table 1

Comparison of the different dust inference methods with the one performed in this paper.

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