| Autor: |
Bron Emeric, Roueff Evelyne, Gerin Maryvonne, Pety Jérôme, Gratier Pierre, Le Petit Franck, Guzman Viviana, Orkisz Jan, de Souza Magalhaes Victor, Gaudel Mathilde, Palud Pierre, Einig Lucas, Bardeau Sébastien, Chainais Pierre, Chanussot Jocelyn, Goicoechea Javier, Hughes Annie, Kainulainen Jouni, Languignon David, Le Bourlot Jacques, Levrier François, Lis Darek, Liszt Harvey, Öberg Karin, Peretto Nicolas, Roueff Antoine, Sievers Albrecht, Thouvenin Pierre-Antoine, Tremblin Pascal |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
EPJ Web of Conferences, Vol 265, p 00023 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2100-014X |
| DOI: |
10.1051/epjconf/202226500023 |
| Popis: |
The ionization fraction in neutral interstellar clouds is a key physical parameter controlling multiple physical and chemical processes, and varying by orders of magnitude from the UV irradiated surface of the cloud to its cosmic-ray dominated central regions. Traditional observational tracers of the ionization fraction, which mostly rely on deuteration ratios of molecules like HCO+, suffer from the fact that the deuterated molecules are only detected in a tiny fraction of a given Giant Molecular Cloud (GMC). In [1], we propose a machine learning-based, semi-automatic method to search in a large dataset of astrochemical model results for new tracers of the ionization fraction, and propose several new tracers relevant in different ranges of physical conditions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
