Learning from model grids: Tracers of the ionization fraction in the ISM - Observatoire de Paris Access content directly
Proceedings EPJ Web of Conferences Year : 2022

Learning from model grids: Tracers of the ionization fraction in the ISM

Pierre Gratier
  • Function : Author
Viviana Guzman
  • Function : Author
Jan Orkisz
  • Function : Author
Victor de Souza Magalhaes
  • Function : Author
Pierre Palud
  • Function : Author
Lucas Einig
  • Function : Author
Sébastien Bardeau
  • Function : Author
Pierre Chainais
  • Function : Author
Javier Goicoechea
  • Function : Author
Annie Hughes
  • Function : Author
Jouni Kainulainen
  • Function : Author
François Levrier
Darek Lis
  • Function : Author
Harvey Liszt
  • Function : Author
Karin Öberg
  • Function : Author
Nicolas Peretto
  • Function : Author
Antoine Roueff
Pierre-Antoine Thouvenin
  • Function : Author
Pascal Tremblin
  • Function : Author

Abstract

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.
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Dates and versions

obspm-03994706 , version 1 (19-02-2023)

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Emeric Bron, Evelyne Roueff, Maryvonne Gerin, Jérôme Pety, Pierre Gratier, et al.. Learning from model grids: Tracers of the ionization fraction in the ISM. EPJ Web of Conferences, 265, pp.00023, 2022, ⟨10.1051/epjconf/202226500023⟩. ⟨obspm-03994706⟩
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