Volume 645, January 2021
|Number of page(s)||28|
|Section||Interstellar and circumstellar matter|
|Published online||23 December 2020|
Tracers of the ionization fraction in dense and translucent gas
I. Automated exploitation of massive astrochemical model grids
LERMA, Observatoire de Paris, PSL Research University, CNRS, Sorbonne Universités,
92190 Meudon, France
2 LERMA, Observatoire de Paris, PSL Research University, CNRS, Sorbonne Universités, 75014 Paris, France
3 IRAM, 300 rue de la Piscine, 38406 Saint Martin d’Hères, France
4 Laboratoire d’Astrophysique de Bordeaux, Univ. Bordeaux, CNRS, B18N, Allee Geoffroy Saint-Hilaire, 33615 Pessac, France
5 Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile
6 Chalmers University of Technology, Department of Space, Earth and Environment, 412 93 Gothenburg, Sweden
7 University of Toulouse, IRIT/INP-ENSEEIHT, CNRS, 2 rue Charles Camichel, BP 7122, 31071 Toulouse cedex 7, France
8 Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL, 59651 Villeneuve d’Ascq, France
9 Instituto de Física Fundamental (CSIC). Calle Serrano 121, 28006 Madrid, Spain
10 Institut de Recherche en Astrophysique et Planétologie (IRAP), Université Paul Sabatier, Toulouse cedex 4, France
11 Laboratoire de Physique de l’Ecole normale supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-Diderot, Sorbonne Paris Cité, Paris, France
12 National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903, USA
13 Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138, USA
14 School of Physics and Astronomy, Cardiff University, Queen’s buildings, Cardiff CF24 3AA, UK
15 Aix-Marseille University, CNRS, Centrale Marseille, Institut Fresnel, Marseille, France
Accepted: 2 July 2020
Context. The ionization fraction in the neutral interstellar medium (ISM) plays a key role in the physics and chemistry of the ISM, from controlling the coupling of the gas to the magnetic field to allowing fast ion-neutral reactions that drive interstellar chemistry. Most estimations of the ionization fraction have relied on deuterated species such as DCO+, whose detection is limited to dense cores representing an extremely small fraction of the volume of the giant molecular clouds that they are part of. As large field-of-view hyperspectral maps become available, new tracers may be found. The growth of observational datasets is paralleled by the growth of massive modeling datasets and new methods need to be devised to exploit the wealth of information they contain.
Aims. We search for the best observable tracers of the ionization fraction based on a grid of astrochemical models, with the broader aim of finding a general automated method applicable to searching for tracers of any unobservable quantity based on grids of models.
Methods. We built grids of models that randomly sample a large range of physical conditions (unobservable quantities such as gas density, temperature, elemental abundances, etc.) and computed the corresponding observables (line intensities, column densities) and the ionization fraction. We estimated the predictive power of each potential tracer by training a random forest model to predict the ionization fraction from that tracer, based on these model grids.
Results. In both translucent medium and cold dense medium conditions, we found several observable tracers with very good predictive power for the ionization fraction. Many tracers in cold dense medium conditions are found to be better and more widely applicable than the traditional DCO+/HCO+ ratio. We also provide simpler analytical fits for estimating the ionization fraction from the best tracers, and for estimating the associated uncertainties. We discuss the limitations of the present study and select a few recommended tracers in both types of conditions.
Conclusions. The method presented here is very general and can be applied to the measurement of any other quantity of interest (cosmic ray flux, elemental abundances, etc.) from any type of model (PDR models, time-dependent chemical models, etc.).
Key words: ISM: clouds / ISM: molecules / methods: statistical / methods: numerical / astrochemistry
© E. Bron et al. 2020
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