Quantitative inference of the H2 column ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Quantitative inference of the H2 column densities from 3 mm molecular emission: case study towards Orion B
Auteur(s) :
Gratier, Pierre [Auteur correspondant]
FORMATION STELLAIRE 2020
Laboratoire d'Astrophysique de Bordeaux [Pessac] [LAB]
Pety, Jérôme [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Institut de RadioAstronomie Millimétrique [IRAM]
Bron, Emeric [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Roueff, Antoine [Auteur]
PhyTI [PhyTI]
Institut FRESNEL [FRESNEL]
Orkisz, Jan [Auteur]
Chalmers University of Technology [Gothenburg, Sweden]
Gerin, Maryvonne [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
de Souza Magalhaes, Victor [Auteur]
Institut de RadioAstronomie Millimétrique [IRAM]
Gaudel, Mathilde [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Vono, Maxime [Auteur]
Signal et Communications [IRIT-SC]
Bardeau, Sébastien [Auteur]
Institut de RadioAstronomie Millimétrique [IRAM]
Chanussot, Jocelyn [Auteur]
GIPSA - Signal Images Physique [GIPSA-SIGMAPHY]
Apprentissage de modèles à partir de données massives [Thoth]
Chainais, Pierre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Goicoechea, Javier [Auteur]
Instituto de Física Fundamental [Madrid] [IFF]
Guzmán, Viviana [Auteur]
Pontificia Universidad Católica de Chile [UC]
Hughes, Annie [Auteur]
Institut de recherche en astrophysique et planétologie [IRAP]
Kainulainen, Jouni [Auteur]
Chalmers University of Technology [Gothenburg, Sweden]
Languignon, David [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Le Bourlot, Jacques [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Le Petit, Franck [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Levrier, François [Auteur]
Astrophysique
Liszt, Harvey [Auteur]
National Radio Astronomy Observatory [Charlottesville] [NRAO]
Peretto, Nicolas [Auteur]
School of Physics and Astronomy [Cardiff]
Roueff, Evelyne [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Sievers, Albrecht [Auteur]
Institut de RadioAstronomie Millimétrique [IRAM]
FORMATION STELLAIRE 2020
Laboratoire d'Astrophysique de Bordeaux [Pessac] [LAB]
Pety, Jérôme [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Institut de RadioAstronomie Millimétrique [IRAM]
Bron, Emeric [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Roueff, Antoine [Auteur]
PhyTI [PhyTI]
Institut FRESNEL [FRESNEL]
Orkisz, Jan [Auteur]
Chalmers University of Technology [Gothenburg, Sweden]
Gerin, Maryvonne [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
de Souza Magalhaes, Victor [Auteur]
Institut de RadioAstronomie Millimétrique [IRAM]
Gaudel, Mathilde [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Vono, Maxime [Auteur]
Signal et Communications [IRIT-SC]
Bardeau, Sébastien [Auteur]
Institut de RadioAstronomie Millimétrique [IRAM]
Chanussot, Jocelyn [Auteur]
GIPSA - Signal Images Physique [GIPSA-SIGMAPHY]
Apprentissage de modèles à partir de données massives [Thoth]
Chainais, Pierre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Goicoechea, Javier [Auteur]
Instituto de Física Fundamental [Madrid] [IFF]
Guzmán, Viviana [Auteur]
Pontificia Universidad Católica de Chile [UC]
Hughes, Annie [Auteur]
Institut de recherche en astrophysique et planétologie [IRAP]
Kainulainen, Jouni [Auteur]
Chalmers University of Technology [Gothenburg, Sweden]
Languignon, David [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Le Bourlot, Jacques [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Le Petit, Franck [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Levrier, François [Auteur]
Astrophysique
Liszt, Harvey [Auteur]
National Radio Astronomy Observatory [Charlottesville] [NRAO]
Peretto, Nicolas [Auteur]
School of Physics and Astronomy [Cardiff]
Roueff, Evelyne [Auteur]
Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres [LERMA]
Sievers, Albrecht [Auteur]
Institut de RadioAstronomie Millimétrique [IRAM]
Titre de la revue :
Astronomy and Astrophysics - A&A
Pagination :
A27
Éditeur :
EDP Sciences
Date de publication :
2021-01
ISSN :
0004-6361
Mot(s)-clé(s) en anglais :
methods: statistical
ISM: clouds
ISM: molecules
ISM: clouds
ISM: molecules
Discipline(s) HAL :
Physique [physics]/Astrophysique [astro-ph]
Informatique [cs]
Informatique [cs]
Résumé en anglais : [en]
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 ...
Lire la suite >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 H2 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 H2 molecular column density from radio observations.Methods. We propose a data-driven approach to determine the H2 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 H2 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 H2 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 13CO(1–0), 12CO(1–0), C18O(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(20–10) lines be added for the prediction of the H2 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.Lire moins >
Lire la suite >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 H2 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 H2 molecular column density from radio observations.Methods. We propose a data-driven approach to determine the H2 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 H2 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 H2 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 13CO(1–0), 12CO(1–0), C18O(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(20–10) lines be added for the prediction of the H2 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.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Projet ANR :
Collections :
Source :
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- https://hal.archives-ouvertes.fr/hal-03017404v2/document
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- http://arxiv.org/pdf/2008.13417
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- https://hal.archives-ouvertes.fr/hal-03017404v2/document
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- https://hal.archives-ouvertes.fr/hal-03017404v2/document
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- https://hal.archives-ouvertes.fr/hal-03017404v2/document
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- aa37871-20.pdf
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- 2008.13417
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