Quantitative inference of the H2 column densities from 3mm molecular emission: case study towards Orion B
Journal article, 2021

Context. Based on the finding that molecular hydrogen is unobservable in cold molecular clouds, the column density measurements of molecular gas currently rely either on dust emission observation in the far-infrared, which requires space telescopes, or on star counting, which is limited in angular resolution by the stellar density. The (sub)millimeter observations of numerous trace molecules can be effective using ground-based telescopes, but the relationship between the emission of one molecular line and the H-2 column density is non-linear and sensitive to excitation conditions, optical depths, and abundance variations due to the underlying physico- chemistry.Aims. We aim to use multi-molecule line emission to infer the H-2 molecular column density from radio observations.Methods. We propose a data-driven approach to determine the H-2 gas column densities from radio molecular line observations. We use supervised machine-learning methods (random forest) on wide-field hyperspectral IRAM-30m observations of the Orion B molecular cloud to train a predictor of the H-2 column density, using a limited set of molecular lines between 72 and 116 GHz as input, and the Herschel-based dust-derived column densities as "ground truth" output.Results. For conditions similar to those of the Orion B molecular cloud, we obtained predictions of the H-2 column density within a typical factor of 1.2 from the Herschel-based column density estimates. A global analysis of the contributions of the different lines to the predictions show that the most important lines are (CO)-C-13(1-0), (CO)-C-12(1-0), (CO)-O-18(1-0), and HCO+(1-0). A detailed analysis distinguishing between diffuse, translucent, filamentary, and dense core conditions show that the importance of these four lines depends on the regime, and that it is recommended that the N2H+(1-0) and CH3OH(2(0)-1(0)) lines be added for the prediction of the H-2 column density in dense core conditions.Conclusions. This article opens a promising avenue for advancing direct inferencing of important physical parameters from the molecular line emission in the millimeter domain. The next step will be to attempt to infer several parameters simultaneously (e.g., the column density and far-UV illumination field) to further test the method.

methods: statistical

ISM: clouds

ISM: molecules


Pierre Gratier

University of Bordeaux

Jerome Pety

Institut de Radioastronomie Millimétrique (IRAM)

Université Paris PSL

Emeric Bron

Université Paris PSL

Antoine Roueff

Aix Marseille University

Jan Orkisz

Chalmers, Space, Earth and Environment, Astronomy and Plasmaphysics, Galactic Astrophysics

Maryvonne Gerin

Université Paris PSL

Victor de Souza Magalhaes

Institut de Radioastronomie Millimétrique (IRAM)

Mathilde Gaudel

Université Paris PSL

Maxime Vono

University of Toulouse

Sebastien Bardeau

Institut de Radioastronomie Millimétrique (IRAM)

Jocelyn Chanussot

Université Grenoble Alpes

Pierre Chainais

University of Lille

Javier R. Goicoechea

CSIC - Instituto de Fisica Fundamental (IFF)

Viviana V. Guzman

Pontificia Universidad Catolica de Chile

Annie Hughes

Paul Sabatier University

Jouni Kainulainen

Chalmers, Space, Earth and Environment, Astronomy and Plasmaphysics, Galactic Astrophysics

David Languignon

Université Paris PSL

Jacques Le Bourlot

Université Paris PSL

Franck Le Petit

Université Paris PSL

Francois Levrier

Université Paris PSL

Harvey Liszt

National Radio Astronomy Observatory

Nicolas Peretto

Cardiff University

Evelyne Rouefe

Université Paris PSL

Albrecht Sievers

Institut de Radioastronomie Millimétrique (IRAM)

Astronomy and Astrophysics

0004-6361 (ISSN) 1432-0746 (eISSN)

Vol. 645 A27

Subject Categories

Astronomy, Astrophysics and Cosmology

Atom and Molecular Physics and Optics

Theoretical Chemistry



More information

Latest update

3/9/2021 1