arXiv subjects

Jacques Le Bourlot

Publications and source records attributed to Jacques Le Bourlot.

At least 19 recordsLinked to original sources

arXiv2026

Physical conditions in PDRs revealed by IGRINS ro-vibrational H2 observations

We compare H2 high ro-vibrational observations of 5 PDRs (S140, IC63, Horsehead Nebula, NGC 2023 and Orion Bar) obtained with the IGRINS spectrograph to PDR models produced with the Meudon PDR code, in order to estimate the physical conditions and to constrain the physical and chemical processes that govern PDRs. We use newly flux-calibrated and extinction-corrected IGRINS H2 observations covering the 1.45-2.45 um range at a resolution of 45000, and adjust Meudon PDR models using both a simple chi2 minimization approach and a robust method using Bayesian inversion followed by posterior exploration via an advanced MCMC technique. The PDR models use specific incident FUV spectra for each PDRs based on theoretical stellar spectra from the Pollux database. The Meudon PDR code is able to reproduce more than 85% of the observed H2 ro-vibrational line intensities within a factor of two. We find that (1) a realistic modeling of the incident FUV field (both in term of geometry and of spectral shape) and (2) the inclusion of recent data on collisional de-excitation rates for high vibrational levels of H2 are key to this success. H2 ro-vibrational emission lines are found to provide good constraints on both the thermal pressure and the incident FUV field strength, G0, although with a non-negligible remaining degeneracy in most PDRs. Additional constraints, such as the spatial scales of the PDR derived from ALMA or JWST observations, are found to be able to lift this degeneracy. For low excitation PDRs, the observations provide evidence that nascent H2 molecules formed on grains have relatively low rotational energy and high vibrational energy, as predicted by theoretical and experimental studies of the surface formation of H2.

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arXiv2025

A Tentative Detection of Molecular Hydrogen (H$_2$) Emission Lines at Cosmic Dawn

We present a theoretical framework for interpreting far-ultraviolet (FUV) fluorescent emission from molecular hydrogen (H$_2$) in high-redshift galaxies, motivated by the unique capabilities of the James Webb Space Telescope (JWST) to probe the rest frame FUV at cosmic dawn. Using the Meudon photodissociation region (PDR) code, we model the H$_2$ fluorescence spectrum under extreme interstellar medium (ISM) conditions in terms of high pressure ($10^{11}~\mathrm{K~ cm^{-3}}$), high radiation field ($10^6$ $G_0$) combined with low metallicity ($Z = 0.1~Z_\odot$) and high cosmic ionization rate ($ζ= 10^{-14}~\mathrm{s}^{-1}$), characteristic of early galaxies. As a case study, we apply this framework to stacked NIRSpec spectra from the JWST Advanced Deep Extragalactic Survey (JADES) for galaxies at redshifts $z\geq7$. The stacked spectrum exhibits emission features consistent in profile and wavelength with the predicted H$_2$ fluorescence lines, including a blue shift suggestive of an outflow of molecular gas. Although individual features remain below robust detection thresholds, this demonstration illustrates the feasibility of using FUV fluorescence modeling to guide and interpret JWST spectroscopy of the molecular ISM at high redshift. Our framework provides a foundation for future searches for molecular hydrogen emission and the study of galactic feedback processes in the early universe.

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arXiv2025

PDRs4All XVII: Formation and excitation of HD in photodissociation regions. Application to the Orion Bar

The James Webb Space Telescope enabled the first detection of several rovibrational emission lines of HD in the Orion Bar, a prototypical photodissociation region. This provides an incentive to examine the physics of HD in dense and strong PDRs. Using the latest data available on HD excitation by collisional, radiative and chemical processes, our goal is to unveil HD formation and excitation processes in PDRs by comparing our state-of-the-art PDR model with observations made in the Orion Bar and discuss if and how HD can be used as a complementary tracer of physical parameters in the emitting region. We compute detailed PDR models, using an upgraded version of the Meudon PDR code, which are compared to NIRSpec data using excitation diagrams and synthetic emission spectra. The models predict that HD is mainly produced in the gas phase via the reaction D + H2 = H + HD at the front edge of the PDR and that the D/HD transition is located slightly closer to the edge than the H/H2 transition. Rovibrational levels are excited by UV pumping. In the observations, HD rovibrational emission is detected close to the H/H2 dissociation fronts of the Orion Bar and peaks where vibrationally excited H2 peaks, rather than at the maximum emission of pure rotational H2 levels. We derive an excitation temperature around Tex ~ 480 - 710 K. Due to high continuum in the Orion Bar, fringes lead to high noise levels beyond 15 $μ$m, no pure rotational lines of HD are detected. The comparison to PDR models shows that a range of thermal pressure P = (3-9)x10$^7$ K cm$^{-3}$ with no strong constraints on the intensity of the UV field are compatible with HD observations. This range of pressure is compatible with previous estimates from H2 observations with JWST. This is the first time that observations of HD emission lines in the near-infrared are used to put constraints on the thermal pressure in the PDR.

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arXiv2025

Tracers of the ionization fraction in dense and translucent molecular gas: II. Using mm observations to constrain ionization fraction across Orion B

The ionization fraction ($f_\mathrm{e}=n_\mathrm{e}/n_\mathrm{H}$) is a crucial parameter of interstellar gas, yet estimating it requires deep knowledge of molecular gas chemistry and observations of specific lines, such as those from isotopologs like HCO$^+$ and N$_2$H$^+$, which are detectable only in dense cores. Previous challenges in constraining $f_\mathrm{e}$ over large areas stemmed from the limitations of observational tracers and chemical models. Recent models have identified molecular line ratios that can trace $f_\mathrm{e}$ in different environments within molecular clouds. In this study, we analyze various molecular lines in the 3-4 mm range to derive the ionization fraction across the Orion B giant molecular cloud. We focus on dense and translucent gas, exploring variations with gas density ($n$) and the far-ultraviolet (FUV) radiation field ($G_0$). Our findings show that the ionization fraction ranges from $10^{-5.5}$ to $10^{-4}$ in translucent gas and $10^{-8}$ to $10^{-6}$ in dense gas. Notably, $f_\mathrm{e}$ is sensitive to $G_0$ in dense, UV-illuminated regions, decreasing with increasing volume density ($f_\mathrm{e} \propto n^{-0.227}$ for dense and $f_\mathrm{e} \propto n^{-0.3}$ for translucent gas) and increasing with $G_0$. In translucent gas, differing line ratios yield consistent fe values, indicating the importance of electron excitation of HCN and HNC. For dense gas, we recommend using the CN(1-0)/N$_2$H$^+$(1-0) ratio for upper limits on fe and C$^{18}$O(1-0)/HCO$^+$(1-0) for lower limits. In translucent environments, CCH(1-0)/HNC(1-0) effectively traces $f_\mathrm{e}$. The higher fe values in translucent gas align with the C$^+$/CI/CO transition, while values in dense gas are adequate for coupling with the magnetic field.

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arXiv2025

Beetroots: spatially-regularized Bayesian inference of physical parameter maps -- Application to Orion

The current generation of millimeter receivers is able to produce cubes of 800 000 pixels by 200 000 frequency channels to cover several square degrees over the 3 mm atmospheric window. Estimating the physical conditions of the interstellar medium (ISM) with an astrophysical model on such datasets is challenging. Common approaches tend to converge to local minima and typically poorly reconstruct regions with low signal-to-noise ratio (S/N). This instrumental revolution thus calls for new scalable data analysis techniques. We present Beetroots, a Python software that performs Bayesian reconstruction of maps of physical conditions from observation maps and an astrophysical model. It relies on an accurate statistical model, exploits spatial regularization to guide estimations, and uses state-of-the-art algorithms. It also assesses the ability of the astrophysical model to explain the observations, providing feedback to improve ISM models. We demonstrate the power of Beetroots with the Meudon PDR code on synthetic data, and then apply it to estimate physical condition maps in the full Orion molecular cloud 1 (OMC-1) star forming region based on Herschel molecular line emission maps. The application to the synthetic case shows that Beetroots can currently analyse maps with up to ten thousand pixels, addressing large variations of S/N, escaping from local minima, and providing consistent uncertainty quantifications. On a laptop, the inference runtime ranges from a few minutes for 100-pixel maps to 28 hours for 8100-pixel maps. The results on the OMC-1 maps are consistent with independent estimations from the literature, and improve our understanding of the region. This work paves the way towards systematic and rigorous analyses of observations produced by current and future instruments.

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arXiv2024

Inelastic H + H$^+_3$ Collision rates and their impact in the determination of the excitation temperature of H$^+_3$

Context. In dffuse interstellar clouds the excitation temperature derived from the lowest levels of H$^+_3$ is systematically lower than that derived from H2. The differences may be attributed to the lack of state-specific formation and destruction rates of H$^+_3$ needed to thermalize the two species. Aims. In this work, we want to check the role of rotational excitation collisions of H$^+_3$ with atomic hydrogen on its excitation temperature. Methods. A time independent close-coupling method is used to calculate the state-to-state rate coefficients, using a very accurate and full dimensional potential energy surface recently developed for H$^+_4$. A symmetric top approach is used to describe a frozen H$^+_3$ as equilateral triangle. Results. Rotational excitation collision rate coefficients of H$^+_3$ with atomic Hydrogen have been derived in a temperature range appropriate to diffuse interstellar conditions up to $(J; K; \pm) = (7; 6; +)$ and $(J; K; \pm) = (6; 4; +)$ for its ortho and para forms. This allows to have a consistent set of collisional excitation rate coefficients and to improve the previous study where these contributions were speculated. Conclusions. The new state-specific inelastic H$^+_3$ + H rate coeffcients yield differences up to 20% in the excitation temperature, and their impact increases with decreasing molecular fraction. We also confirm the impact of chemical state-to-state destruction reactions in the excitation balance of H$^+_3$ , and that reactive H + H$^+_3$ collisions are also needed to account for possible further ortho to para transitions

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arXiv2024

A highly efficient Voigt program for line profile computation

Evaluation of the Voigt function, a convolution of a Lorentzian and a Gaussian profile, is essential in various fields such as spectroscopy, atmospheric science, and astrophysics. Efficient computation of the function is crucial, especially in applications where the function may be called for an enormous number of times. In this paper, we present a highly efficient novel algorithm and its Fortran90 implementation for the practical evaluation of the Voigt function with accuracy in the order of 1.0e-6. The algorithm uses improved fits based on Chebyshev subinterval polynomial approximation for functions in two variables. The algorithm significantly outperforms widely-used competitive algorithms in the literature, in terms of computational speed, making it highly suitable for real-time applications and large-scale data processing tasks. The substantial improvement in efficiency positions the present algorithm and computer code as a valuable tool in relevant scientific domains. The algorithm has been adopted and implemented in the Meudon PDR code at Paris Observatory and is recommended for similar applications and simulation packages.

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arXiv2024

Toward a robust physical and chemical characterization of heterogeneous lines of sight: The case of the Horsehead nebula

Dense cold molecular cores/filaments are surrounded by an envelope of translucent gas. Some of the low-J emission lines of CO and HCO$^+$ isotopologues are more sensitive to the conditions either in the translucent environment or in the dense cold one. We propose a cloud model composed of three homogeneous slabs of gas along each line of sight (LoS), representing an envelope and a shielded inner layer. IRAM-30m data from the ORION-B large program toward the Horsehead nebula are used to demonstrate the method's capability. We use the non-LTE radiative transfer code RADEX to model the line profiles from the kinetic temperature $T_{kin}$, the volume density $n_{H_2}$, kinematics and chemical properties of the different layers. We then use a maximum likelihood estimator to simultaneously fit the lines of the CO and HCO$^+$ isotopologues. We constrain column density ratios to limit the variance on the estimates. This simple heterogeneous model provides good fits of the fitted lines over a large part of the cloud. The decomposition of the intensity into three layers allows to discuss the distribution of the estimated physical/chemical properties along the LoS. About 80$\%$ the CO integrated intensity comes from the envelope, while $\sim55\%$ of that of the (1-0) and (2-1) lines of C$^{18}$O comes from the inner layer. The $N(^{13}CO)/N(C^{18}O)$ in the envelope increases with decreasing $A_v$, and reaches $25$ in the pillar outskirts. The envelope $T_{kin}$ varies from 25 to 40 K, that of the inner layer drops to $\sim 15$ K in the western dense core. The inner layer $n_{H_2}$ is $\sim 3\times10^4\,\text{cm}^{-3}$ toward the filament and it increases by a factor $10$ toward dense cores. The proposed method correctly retrieves the physical/chemical properties of the Horsehead nebula and offers promising prospects for less supervised model fits of wider-field datasets.

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arXiv2024

Quantifying the informativity of emission lines to infer physical conditions in giant molecular clouds. I. Application to model predictions

Observations of ionic, atomic, or molecular lines are performed to improve our understanding of the interstellar medium (ISM). However, the potential of a line to constrain the physical conditions of the ISM is difficult to assess quantitatively, because of the complexity of the ISM physics. The situation is even more complex when trying to assess which combinations of lines are the most useful. Therefore, observation campaigns usually try to observe as many lines as possible for as much time as possible. We search for a quantitative statistical criterion to evaluate the constraining power of a (or combination of) tracer(s) with respect to physical conditions in order to improve our understanding of the statistical relationships between ISM tracers and physical conditions and helps observers to motivate their observation proposals. The best tracers are obtained by comparing the mutual information between a physical parameter and different sets of lines. We apply this method to simulations of radio molecular lines emitted by a photodissociation region similar to the Horsehead Nebula that would be observed at the IRAM 30m telescope. We search for the best lines to constrain the visual extinction $A_v^{tot}$ or the far UV illumination $G_0$. The most informative lines change with the physical regime (e.g., cloud extinction). Short integration time of the CO isotopologue $J=1-0$ lines already yields much information on the total column density most regimes. The best set of lines to constrain the visual extinction does not necessarily combine the most informative individual lines. Precise constraints on $G_0$ are more difficult to achieve with molecular lines. They require spectral lines emitted at the cloud surface (e.g., [CII] and [CI] lines). This approach allows one to better explore the knowledge provided by ISM codes, and to guide future observation campaigns.

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arXiv2024

PDRs4All IX. Sulfur elemental abundance in the Orion Bar

One of the main problems in astrochemistry is determining the amount of sulfur in volatiles and refractories in the interstellar medium. The detection of the main sulfur reservoirs (icy H$_2$S and atomic gas) has been challenging, and estimates are based on the reliability of models to account for the abundances of species containing less than 1% of the total sulfur. The high sensitivity of the James Webb Space Telescope provides an unprecedented opportunity to estimate the sulfur abundance through the observation of the [S I] 25.249 $μ$m line. We used the [S III] 18.7 $μ$m, [S IV] 10.5 $μ$m, and [S l] 25.249 $μ$m lines to estimate the amount of sulfur in the ionized and molecular gas along the Orion Bar. For the theoretical part, we used an upgraded version of the Meudon photodissociation region (PDR) code to model the observations. New inelastic collision rates of neutral atomic sulfur with ortho- and para- molecular hydrogen were calculated to predict the line intensities. The [S III] 18.7 $μ$m and [S IV] 10.5 $μ$m lines are detected over the imaged region with a shallow increase (by a factor of 4) toward the HII region. We estimate a moderate sulfur depletion, by a factor of $\sim$2, in the ionized gas. The corrugated interface between the molecular and atomic phases gives rise to several edge-on dissociation fronts we refer to as DF1, DF2, and DF3. The [S l] 25.249 $μ$m line is only detected toward DF2 and DF3, the dissociation fronts located farthest from the HII region. The detailed modeling of DF3 using the Meudon PDR code shows that the emission of the [S l] 25.249 $μ$m line is coming from warm ($>$ 40 K) molecular gas located at A$_{\rm V}$ $\sim$ 1$-$5 mag from the ionization front. Moreover, the intensity of the [S l] 25.249 $μ$m line is only accounted for if we assume the presence of undepleted sulfur.

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arXiv2024

Bias versus variance when fitting multi-species molecular lines with a non-LTE radiative transfer model

Robust radiative transfer techniques are requisite for efficiently extracting the physical and chemical information from molecular rotational lines.We study several hypotheses that enable robust estimations of the column densities and physical conditions when fitting one or two transitions per molecular species. We study the extent to which simplifying assumptions aimed at reducing the complexity of the problem introduce estimation biases and how to detect them.We focus on the CO and HCO+ isotopologues and analyze maps of a 50 square arcminutes field. We used the RADEX escape probability model to solve the statistical equilibrium equations and compute the emerging line profiles, assuming that all species coexist. Depending on the considered set of species, we also fixed the abundance ratio between some species and explored different values. We proposed a maximum likelihood estimator to infer the physical conditions and considered the effect of both the thermal noise and calibration uncertainty. We analyzed any potential biases induced by model misspecifications by comparing the results on the actual data for several sets of species and confirmed with Monte Carlo simulations. The variance of the estimations and the efficiency of the estimator were studied based on the Cram{é}r-Rao lower bound.Column densities can be estimated with 30% accuracy, while the best estimations of the volume density are found to be within a factor of two. Under the chosen model framework, the peak 12CO(1--0) is useful for constraining the kinetic temperature. The thermal pressure is better and more robustly estimated than the volume density and kinetic temperature separately. Analyzing CO and HCO+ isotopologues and fitting the full line profile are recommended practices with respect to detecting possible biases.Combining a non-local thermodynamic equilibrium model with a rigorous analysis of the accuracy allows us to obtain an efficient estimator and identify where the model is misspecified. We note that other combinations of molecular lines could be studied in the future.

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arXiv2023

Neural network-based emulation of interstellar medium models

The interpretation of observations of atomic and molecular tracers in the galactic and extragalactic interstellar medium (ISM) requires comparisons with state-of-the-art astrophysical models to infer some physical conditions. Usually, ISM models are too time-consuming for such inference procedures, as they call for numerous model evaluations. As a result, they are often replaced by an interpolation of a grid of precomputed models. We propose a new general method to derive faster, lighter, and more accurate approximations of the model from a grid of precomputed models. These emulators are defined with artificial neural networks (ANNs) designed and trained to address the specificities inherent in ISM models. Indeed, such models often predict many observables (e.g., line intensities) from just a few input physical parameters and can yield outliers due to numerical instabilities or physical bistabilities. We propose applying five strategies to address these characteristics: 1) an outlier removal procedure; 2) a clustering method that yields homogeneous subsets of lines that are simpler to predict with different ANNs; 3) a dimension reduction technique that enables to adequately size the network architecture; 4) the physical inputs are augmented with a polynomial transform to ease the learning of nonlinearities; and 5) a dense architecture to ease the learning of simple relations. We compare the proposed ANNs with standard classes of interpolation methods to emulate the Meudon PDR code, a representative ISM numerical model. Combinations of the proposed strategies outperform all interpolation methods by a factor of 2 on the average error, reaching 4.5% on the Meudon PDR code. These networks are also 1000 times faster than accurate interpolation methods and require ten to forty times less memory. This work will enable efficient inferences on wide-field multiline observations of the ISM.

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arXiv2023

Deep learning denoising by dimension reduction: Application to the ORION-B line cubes

Context. The availability of large bandwidth receivers for millimeter radio telescopes allows the acquisition of position-position-frequency data cubes over a wide field of view and a broad frequency coverage. These cubes contain much information on the physical, chemical, and kinematical properties of the emitting gas. However, their large size coupled with inhomogenous signal-to-noise ratio (SNR) are major challenges for consistent analysis and interpretation.Aims. We search for a denoising method of the low SNR regions of the studied data cubes that would allow to recover the low SNR emission without distorting the signals with high SNR.Methods. We perform an in-depth data analysis of the 13 CO and C 17 O (1 -- 0) data cubes obtained as part of the ORION-B large program performed at the IRAM 30m telescope. We analyse the statistical properties of the noise and the evolution of the correlation of the signal in a given frequency channel with that of the adjacent channels. This allows us to propose significant improvements of typical autoassociative neural networks, often used to denoise hyperspectral Earth remote sensing data. Applying this method to the 13 CO (1 -- 0) cube, we compare the denoised data with those derived with the multiple Gaussian fitting algorithm ROHSA, considered as the state of the art procedure for data line cubes.Results. The nature of astronomical spectral data cubes is distinct from that of the hyperspectral data usually studied in the Earth remote sensing literature because the observed intensities become statistically independent beyond a short channel separation. This lack of redundancy in data has led us to adapt the method, notably by taking into account the sparsity of the signal along the spectral axis. The application of the proposed algorithm leads to an increase of the SNR in voxels with weak signal, while preserving the spectral shape of the data in high SNR voxels.Conclusions. The proposed algorithm that combines a detailed analysis of the noise statistics with an innovative autoencoder architecture is a promising path to denoise radio-astronomy line data cubes. In the future, exploring whether a better use of the spatial correlations of the noise may further improve the denoising performances seems a promising avenue. In addition,

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arXiv2023

Understanding the temperatures of H3+ and H2 in diffuse interstellar sightlines

The triatomic hydrogen ion H3+ is one of the most important species for the gas phase chemistry of the interstellar medium. Observations of H3+ are used to constrain important physical and chemical parameters of interstellar environments. However, the temperatures inferred from the two lowest rotational states of H3+ in diffuse lines of sight - typically the only ones observable - appear consistently lower than the temperatures derived from H2 observations in the same sightlines. All previous attempts at modelling the temperatures of H3+ in the diffuse interstellar medium failed to reproduce the observational results. Here we present new studies, comparing an independent master equation for H3+ level populations to results from the Meudon PDR code for photon dominated regions. We show that the populations of the lowest rotational states of H3+ are strongly affected by the formation reaction and that H3+ ions experience incomplete thermalisation before their destruction by free electrons. Furthermore, we find that for quantitative analysis more than two levels of H3+ have to be considered and that it is crucial to include radiative transitions as well as collisions with H2. Our models of typical diffuse interstellar sightlines show very good agreement with observational data, and thus they may finally resolve the perceived temperature difference attributed to these two fundamental species.

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arXiv2022

Gas kinematics around filamentary structures in the Orion B cloud

Understanding the initial properties of star-forming material and how they affect the star formation process is key. From an observational point of view, the feedback from young high-mass stars on future star formation properties is still poorly constrained. In the framework of the IRAM 30m ORION-B large program, we obtained observations of the translucent and moderately dense gas, which we used to analyze the kinematics over a field of 5 deg^2 around the filamentary structures. We used the ROHSA algorithm to decompose and de-noise the C18O(1-0) and 13CO(1-0) signals by taking the spatial coherence of the emission into account. We produced gas column density and mean velocity maps to estimate the relative orientation of their spatial gradients. We identified three cloud velocity layers at different systemic velocities and extracted the filaments in each velocity layer. The filaments are preferentially located in regions of low centroid velocity gradients. By comparing the relative orientation between the column density and velocity gradients of each layer from the ORION-B observations and synthetic observations from 3D kinematic toy models, we distinguish two types of behavior in the dynamics around filaments: (i) radial flows perpendicular to the filament axis that can be either inflows (increasing the filament mass) or outflows and (ii) longitudinal flows along the filament axis. The former case is seen in the Orion B data, while the latter is not identified. We have also identified asymmetrical flow patterns, usually associated with filaments located at the edge of an HII region. This is the first observational study to highlight feedback from HII regions on filament formation and, thus, on star formation in the Orion B cloud. This simple statistical method can be used for any molecular cloud to obtain coherent information on the kinematics.

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arXiv2020

Sustained oscillations in Interstellar chemistry models

Non-linear behavior in interstellar chemical models has been recognized for 25 years now. Different mechanisms account for the possibility of multiple fixed-points at steady state, characterized by the ionization degree of the gas. Chemical oscillations are also a natural behaviour of non-linear chemical models. We study under which conditions spontaneous sustained chemical oscillations are possible, and what kind of biffurcations lead to, or quench, the occurrence of such oscillations. Methods. The well known Ordinary Differential Equations (ODE) integrator VODE is used to explore initial conditions and parameter space in a gas phase chemical model of a dark interstellar cloud. We recall that the time evolution of the various chemical abundances under fixed temperature conditions depends on the density over cosmic ionization rate nH/ζ ratio. We also report the occurrence of naturally sustained oscillations for a limited but well defined range of control parameters. The period of oscillations is within the range of characteristic time scales of interstellar processes and could lead to spectacular resonances in time dependent models. Reservoir species (C, CO, NH3, ...) oscillation amplitudes are generally less than a factor two. However, these amplitudes reach a factor ten to thousand for low abundance species, e.g. HCN, ND3, that may play a key role for diagnostic purposes.The mechanism responsible for oscillations is tightly linked to the chemistry of nitrogen, and requires long chains of reactions such as found in multi-deuteration processes.

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arXiv2020

Quantitative inference of the $H_2$ column densities from 3 mm molecular emission: A case study towards Orion B

Molecular hydrogen being unobservable in cold molecular clouds, the column density measurements of molecular gas currently rely either on dust emission observation in the far-IR or on star counting. (Sub-)millimeter observations of numerous trace molecules are effective from ground based telescopes, but the relationships between the emission of one molecular line and the H2 column density (NH2) is non-linear and sensitive to excitation conditions, optical depths, abundance variations due to the underlying physico-chemistry. We aim to use multi-molecule line emission to infer NH2 from radio observations. We propose a data-driven approach to determine NH2 from radio molecular line observations. We use supervised machine learning methods (Random Forests) on wide-field hyperspectral IRAM-30m observations of the Orion B molecular cloud to train a predictor of NH2, using a limited set of molecular lines as input, and the Herschel-based dust-derived NH2 as ground truth output. For conditions similar to the Orion B molecular cloud, we obtain predictions of NH2 within a typical factor of 1.2 from the Herschel-based estimates. An analysis of the contributions of the different lines to the predictions show that the most important lines are $^{13}$CO(1-0), $^{12}$CO(1-0), C$^{18}$O(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 to add the N$_2$H$^+$(1-0) and CH$_3$OH(20-10) lines for the prediction of NH2 in dense core conditions. This article opens a promising avenue to directly infer important physical parameters from the molecular line emission in the millimeter domain. The next step will be to try to infer several parameters simultaneously (e.g., NH2 and far-UV illumination field) to further test the method. [Abridged]

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arXiv2020

Tracers of the ionization fraction in dense and translucent gas: I. Automated exploitation of massive astrochemical model grids

The ionization fraction plays a key role in the physics and chemistry of the neutral interstellar medium, 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 they are part of. As large field-of-view hyperspectral maps become available, new tracers may be found. We search for the best observable tracers of the ionization fraction based on a grid of astrochemical models. We build grids of models that sample randomly a large space of physical conditions (unobservable quantities such as gas density, temperature, etc.) and compute the corresponding observables (line intensities, column densities) and the ionization fraction. We estimate 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. In both translucent medium and cold dense medium conditions, several observable tracers with very good predictive power for the ionization fraction are found. Several 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. 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.). (abridged)

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