Issue |
A&A
Volume 671, March 2023
|
|
---|---|---|
Article Number | A54 | |
Number of page(s) | 16 | |
Section | Galactic structure, stellar clusters and populations | |
DOI | https://doi.org/10.1051/0004-6361/202243326 | |
Published online | 07 March 2023 |
Bayesian inference of three-dimensional gas maps
II. Galactic HI⋆
Institute for Theoretical Physics and Cosmology (TTK), RWTH Aachen University, Sommerfeldstr. 16, 52074 Aachen, Germany
e-mail: pmertsch@physik.rwth-aachen.de, vhmphan@physik.rwth-aachen.de
Received:
14
February
2022
Accepted:
23
November
2022
The 21 cm emission from atomic hydrogen (H I ) is one of the most important tracers of the structure and dynamics of the interstellar medium. Thanks to Galactic rotation, the line is Doppler shifted and, assuming a model for the velocity field, data from gas line surveys can be deprojected along the line of sight. However, given our vantage point in the Galaxy, such a reconstruction suffers from a number of ambiguities. Here, we argue that those can be cured by exploiting the spatial coherence of the gas density that is implied by the physical processes shaping it. We have adopted a Bayesian inference framework that allows reconstructing the three-dimensional map of H I and quantifying its uncertainty. We employ data from the HI4PI compilation to produce three-dimensional maps of Galactic H I. The reconstructed density shows structure on a variety of scales. In particular, some spurs and spiral arms can be identified with ease. We discuss the morphology of the surface mass density and the radial and vertical profiles.
Key words: Galaxy: structure / ISM: kinematics and dynamics / ISM: atoms / methods: statistical
The reconstructed three-dimensional H I densities are available at https://doi.org/10.5281/zenodo.5956696
© The Authors 2023
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.
This article is published in open access under the Subscribe to Open model. Subscribe to A&A to support open access publication.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.