ORION-B project publications

Consortium ADS library   link-ads

Sorted by decreasing date

18. Quantifying the informativity of emission lines to infer physical conditions in giant molecular clouds. I. Application to model predictions, Lucas Einig, Pierre Palud, Antoine Roueff, Jérôme Pety, Emeric Bron, Franck Le Petit, Maryvonne Gerin, Jocelyn Chanussot, Pierre Chainais, Pierre-Antoine Thouvenin, David Languignon, Ivana Bešlić, Simon Coudé, Helena Mazurek, Jan H. Orkisz, Miriam G. Santa-Maria, Léontine Ségal, Antoine Zakardjian, Sébastien Bardeau, Karine Demyk, Victor de Souza Magalhães, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, François Levrier, Jacques Le Bourlot, Dariusz C. Lis, Harvey S. Liszt, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, A&A, 2024, doi:10.1051/0004-6361/202451588

Context. 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.
Aims. We have searched for a quantitative statistical criterion to evaluate the full constraining power of a (combination of) tracer(s) with respect to physical conditions. Our goal with such a criterion is twofold. First, we want to improve our understanding of the statistical relationships between ISM tracers and physical conditions. Secondly, by exploiting this criterion, we aim to propose a method that helps observers to make their observation proposals; for example, by choosing to observe the lines with the highest constraining power given limited resources and time.
Methods. We propose an approach based on information theory, in particular the concepts of conditional differential entropy and mutual information. The best (combination of) tracer(s) is obtained by comparing the mutual information between a physical parameter and different sets of lines. The presented analysis is independent of the choice of the estimation algorithm (e.g., neural network or χ2 minimization).We applied this method to simulations of radio molecular lines emitted by a photodissociation region similar to the Horsehead Nebula. In this simulated data, we considered the noise properties of a state-of-the-art single dish telescope such as the IRAM 30m telescope. We searched for the best lines to constrain the visual extinction, AV, or the ultraviolet illumination field, G0. We ran this search for different gas regimes, namely translucent gas, filamentary gas, and dense cores.
Results. The most informative lines change with the physical regime (e.g., cloud extinction). However, the determination of the optimal (combination of) line(s) to constrain a physical parameter such as the visual extinction depends not only on the radiative transfer of the lines and chemistry of the associated species, but also on the achieved mean signal-to-noise ratio. The short integration time of the CO isotopologue J = 1—0 lines already yields much information on the total column density for a large range of (AV, G0) space. The best set of lines to constrain the visual extinction does not necessarily combine the most informative individual lines. Precise constraints on the radiation field are more difficult to achieve with molecular lines. They require spectral lines emitted at the cloud surface (e.g., [CII] and [CI] lines).
Conclusions. This approach allows one to better explore the knowledge provided by ISM codes, and to guide future observation campaigns.

17. Bias versus variance when fitting multi-species molecular lines with a non-LTE radiative transfer model, Antoine Roueff, Jérôme Pety, Maryvonne Gerin, Léontine Ségal, Javier R. Goicoechea, Harvey S. Liszt , Pierre Gratier, Ivana Bešlić, Lucas Einig, Mathilde Gaudel, Jan H. Orkisz, Pierre Palud, Miriam G. Santa-Maria, Victor de Souza Magalhães, Antoine Zakardjian, Sebastien Bardeau, Emeric E. Bron, Pierre Chainais, Simon Coudé, Karine Demyk, Viviana V. Guzmán, Annie Hughes, David Languignon , François Levrier , Dariusz C. Lis, Jacques Le Bourlot, Franck Le Petit, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, Pierre-Antoine Thouvenin, A&A, 2024, doi:10.1051/0004-6361/202449148

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 Cramér-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.

16. The magnetic field in the Flame nebula, Ivana Bešlić, Simon Coudé, Dariusz C. Lis, Maryvonne Gerin, Paul F. Goldsmith, Jérôme Pety, Antoine Roueff, Karine Demyk, Charles D. Dowell, Lucas Einig, Javier R. Goicoechea, Francois Levrier, Jan H. Orkisz, Nicolas Peretto, Miriam G. Santa-Maria, Nathalie Ysard, Antoine Zakardjian, A&A, 2024, doi:10.1051/0004-6361/202348376

Star formation is essential in galaxy evolution and the cycling of matter. The support of interstellar clouds against gravitational collapse by magnetic (B-) fields has been proposed to explain the low observed star formation efficiency in galaxies and the Milky Way. Despite the Planck satellite providing a 5-15' all-sky map of the B-field geometry in the diffuse interstellar medium, higher spatial resolution observations are required to understand the transition from diffuse gas to gravitationally unstable filaments. NGC 2024, the Flame Nebula, in the nearby Orion B molecular cloud, contains a young, expanding HII region and a dense filament that harbors embedded protostellar objects. Therefore, NGC 2024 is an excellent opportunity to study the role of B-fields in the formation, evolution, and collapse of filaments, as well as the dynamics and effects of young HII regions on the surrounding molecular gas. We combine new 154 and 216 micron dust polarization measurements carried out using the HAWC+ instrument aboard SOFIA with molecular line observations of 12CN (1—0) and HCO+ (1—0) from the IRAM 30-meter telescope to determine the B-field geometry and to estimate the plane of the sky magnetic field strength across the NGC 2024. The HAWC+ observations show an ordered B-field geometry in NGC 2024 that follows the morphology of the expanding HII region and the direction of the main filament. The derived plane of the sky B-field strength is moderate, ranging from 30 to 80 micro G. The strongest B-field is found at the northern-west edge of the HII region, characterized by the highest gas densities and molecular line widths. In contrast, the weakest field is found toward the filament in NGC 2024. The B-field has a non-negligible influence on the gas stability at the edges of the expanding HII shell (gas impacted by the stellar feedback) and the filament (site of the current star formation).

15. HCN emission from translucent gas and UV-illuminated cloud edges revealed by wide-field IRAM 30 m maps of the Orion B GMC. Revisiting its role as a tracer of the dense gas reservoir for star formation, Miriam G. Santa-Maria, Javier R. Goicoechea, Jérôme Pety, Maryvonne Gerin, Jan H. Orkisz, Franck Le Petit,Lucas Einig, Pierre Palud, Victor de Souza Magalhães, Ivana Bešlić, Léontine Ségal, Sébastien Bardeau, Emeric Bron, Pierre Chainais, Jocelyn Chanussot, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, David Languignon, Franck Levrier, Dariusz C. Lis, Harvey S. Liszt, Jacques Le Bourlot, Yoko Oya, Karin Öberg, Nicolas Peretto, Evelyne Roueff, Antoine Roueff, Albrecht Sievers, Pierre-Antoine Thouvenin, Satoshi Yamamoto, A&A, 2023, doi:10.1051/0004-6361/202346598

Context. Massive stars form within dense clumps inside giant molecular clouds (GMCs). Finding appropriate chemical tracers of the dense gas (n(H2) > several 104 cm-3 or AV > 8 mag) and linking their line luminosity with the star formation rate is of critical importance.
Aims. Our aim is to determine the origin and physical conditions of the HCN-emitting gas and study their relation to those of other molecules.
Methods. In the context of the IRAM 30m ORION-B large program, we present 5 deg2 (~250 pc2) HCN, HNC, HCO+, and CO J =1—0 maps of the Orion B GMC, complemented with existing wide-field [CI] 492 GHz maps, as well as new pointed observations of rotationally excited HCN, HNC, H13CN, and HN13C lines. We compare the observed HCN line intensities with radiative transfer models including line overlap effects and electron excitation. Furthermore, we study the HCN/HNC isomeric abundance ratio with updated photochemical models.
Results. We spectroscopically resolve the HCN J = 1—0 hyperfine structure (HFS) components (and partially resolved J = 2—1 and 3—2 components). We detect anomalous HFS line intensity (and line width) ratios almost everywhere in the cloud. About 70% of the total HCN J = 1—0 luminosity, L'(HCN J = 1—0) = 110 K km s-1 pc-2, arises from AV < 8 mag. The HCN/CO J = 1—0 line intensity ratio, widely used as a tracer of the dense gas fraction, shows a bimodal behavior with an inflection point at AV < 3 mag typical of translucent gas and illuminated cloud edges. We find that most of the HCN J = 1—0 emission arises from extended gas with n(H2) < 104 cm-3, and even lower density gas if the ionization fraction is χe ≥ 10-5 and electron excitation dominates. This result contrasts with the prevailing view of HCN J = 1—0 emission as a tracer of dense gas and explains the low-AV branch of the HCN/CO J = 1—0 intensity ratio distribution. Indeed, the highest HCN/CO ratios (~ 0.1) at AV < 3 mag correspond to regions of high [CI] 492 GHz/CO J = 1—0 intensity ratios (>1) characteristic of low-density photodissociation regions. The low surface brightness (≲ 1 K km s-1) and extended HCN and HCO+ J = 1—0 emission scale with IFIR - a proxy of the stellar far-ultraviolet (FUV) radiation field - in a similar way. Together with CO J = 1—0, these lines respond to increasing IFIR up to G0 ≃ 20. On the other hand, the bright HCN J = 1—0 emission (> 6 K km s-1) from dense gas in star-forming clumps weakly responds to IFIR once the FUV field becomes too intense (G0 > 1500). In contrast, HNC J = 1—0 and [CI] 492 GHz lines weakly respond to IFIR for all G0. The different power law scalings (produced by different chemistries, densities, and line excitation regimes) in a single but spatially resolved GMC resemble the variety of Kennicutt-Schmidt law indexes found in galaxy averages.
Conclusions. Given the widespread and extended nature of the [CI] 492 GHz emission, as well as its spatial correlation with that of HCO+, HCN, and 13CO J = 1—0 lines (in this order), we argue that the edges of GMCs are porous to FUV radiation from nearby massive stars. Enhanced FUV radiation favors the formation and excitation of HCN on large scales, not only in dense star-forming clumps, and it leads to a relatively low value of the dense gas mass to total luminosity ratio, α (HCN) = 29 M⊙/(K km s-1 pc2) in Orion B. As a corollary for extragalactic studies, we conclude that high HCN/CO J = 1—0 line intensity ratios do not always imply the presence of dense gas, which may be better traced by HNC than by HCN.

14. Neural network-based emulation of interstellar medium models, Pierre Palud, Lucas Einig, Franck Le Petit, Emeric Bron, Pierre Chainais, Jocelyn Chanussot, Jérôme Pety, Pierre-Antoine Thouvenin, David Languignon, Ivana Bešlić, Miriam G. Santa-Maria, Jan H. Orkisz, Léontine Ségal, Antoine Zakardjian, Sébastien Bardeau, Maryvonne Gerin, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, François Levrier, Harvey S. Liszt, Jacques Le Bourlot, Antoine Roueff, Albrecht Sievers, A&A, 2023, doi:10.1051/0004-6361/202347074

Context. 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 timeconsuming 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.
Aims. We propose a new general method to derive faster, lighter, and more accurate approximations of the model from a grid of precomputed models for use in inference procedures.
Methods. These emulators are defined with artificial neural networks (ANNs) with adapted architectures and are fitted using regression strategies instead of interpolation methods. The specificities inherent in ISM models need to be addressed to design and train adequate ANNs. Indeed, such models often predict numerous observables (e.g., line intensities) from just a few input physical parameters and can yield outliers due to numerical instabilities or physical bistabilities and multistabilities. 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 us 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 simpler relations between line intensities and physical parameters.
Results. We compare the proposed ANNs with four standard classes of interpolation methods, nearest-neighbor, linear, spline, and radial basis function (RBF), to emulate a representative ISM numerical model known as the Meudon PDR code. Combinations of the proposed strategies produce networks that outperform all interpolation methods in terms of accuracy by a factor of 2 in terms of the average error (reaching 4.5% on the Meudon PDR code) and a factor of 3 for the worst-case errors (33%). These networks are also 1000 times faster than accurate interpolation methods and require ten to forty times less memory.
Conclusions. This work will enable efficient inferences on wide-field multiline observations of the ISM.

13. Deep learning denoising by dimension reduction: Application to the ORION-B line cubes, Lucas Einig, Jérôme Pety, Antoine Roueff, Paul Vandame, Jocelyn Chanussot, Maryvonne Gerin, Jan H. Orkisz, Pierre Palud, Miriam G. Santa-Maria, Victor de Souza Magalhães, Ivana Bešlić, Sébastien Bardeau, Emeric Bron, Pierre Chainais, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, Jouni Kainulainen, David Languignon, Rosine Lallement, François Levrier, Dariusz C. Lis, Harvey S. Liszt, Jacques Le Bourlot, Franck Le Petit, Karin Öberg, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, Pierre-Antoine Thouvenin, Pascal Tremblin, A&A, 2023, doi:10.1051/0004-6361/202346064

Context. The availability of large bandwidth receivers for millimeter radio telescopes allows for the acquisition of position-position-frequency data cubes over a wide field of view and a broad frequency coverage. These cubes contain a lot of information on the physical, chemical, and kinematical properties of the emitting gas. However, their large size coupled with an inhomogenous signal-to-noise ratio (S/N) are major challenges for consistent analysis and interpretation.
Aims. We searched for a denoising method of the low S/N regions of the studied data cubes that would allow the low S/N emission to be recovered without distorting the signals with a high S/N.
Methods. We performed an in-depth data analysis of the 13CO and C17O (1—0) data cubes obtained as part of the ORION-B large program performed at the IRAM 30 m telescope. We analyzed 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 has allowed us to propose significant improvements of typical autoassociative neural networks, often used to denoise hyperspectral Earth remote sensing data. Applying this method to the 13CO (1—0) cube, we were able to 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 in the S/N in voxels with a weak signal, while preserving the spectral shape of the data in high S/N 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 to be a promising avenue. In addition, dealing with the multiplicative noise associated with the calibration uncertainty at high S/N would also be beneficial for such large data cubes.

12. Efficient Sampling of Non Log-Concave Posterior Distributions With Mixture of Noises, Pierre Palud, Pierre-Antoine Thouvenin, Pierre Chainais, Emeric Bron, Franck Le Petit, IEEE Transactions on Signal Processing, 2023, arXiv May 2023

This article focuses on a challenging class of inverse problems that is often encountered in applications. The forward model is a complex non-linear black-box, potentially non-injective, whose outputs cover multiple decades in amplitude. Observations are supposed to be simultaneously damaged by additive and multiplicative noises and censorship. As needed in many applications, the aim of this work is to provide uncertainty quantification on top of parameter estimates. The resulting log-likelihood is intractable and potentially non-log-concave. An adapted Bayesian approach is proposed to provide credibility intervals along with point estimates. An MCMC algorithm is proposed to deal with the multimodal posterior distribution, even in a situation where there is no global Lipschitz constant (or it is very large). It combines two kernels, namely an improved version of PMALA (Li, 2016) and a Multiple Try Metropolis (MTM) kernel (Liu et al., 2021). This sampler addresses all the challenges induced by the complex form of the likelihood. The proposed method is illustrated on classical test multimodal distributions as well as on a challenging and realistic inverse problem in astronomy.

11. Gas kinematics around filamentary structures in the Orion B cloud, Mathilde Gaudel, Jan H. Orkisz, Maryvonne Gerin, Jérôme Pety, Antoine Roueff, Antoine Marchal, François Levrier, Marc-Antoine Miville-Deschênes, Javier R. Goicoechea, Evelyne Roueff, Franck Le Petit, Victor de Souza Magalhães, Pierre Palud, Miriam G. Santa-Maria, Maxime Vono, Sébastien Bardeau, Emeric, Bron, Pierre Chainais, Jocelyn Chanussot, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, Jouni Kainulainen, David Languignon, Jacques Le Bourlot, Franck Le Petit, François Levrier, Harvey S. Liszt, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, A&A, 2022, doi:10.1051/0004-6361/202142109

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 deg2 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.

10. Revealing which Combinations of Molecular Lines are Sensitive to the Gas Physical Parameters of Molecular Clouds. Astrophysics Meet Data Science towards the Orion B Cloud, Jérôme Pety, Maryvonne Gerin, Emeric Bron, Pierre Gratier, Jan H. Orkisz, Pierre Palud, Antoine Roueff, Lucas Einig, Miriam G. Santa-Maria, Victor de Souza Magalhães, Sébastien Bardeau, Jocelyn Chanussot, Pierre Chainais, Javier R. Goicoechea, Viviana V. Guzmán, Annie Hughes, Jouni Kainulainen, David Languignon, François Levrier, Dariusz C. Lis, EPJ Web of Conferences, 2022, doi:10.1051/epjconf/202226500048

Atoms and molecules have long been thought to be versatile tracers of the cold neutral gas in the universe, from high-redshift galaxies to star forming regions and proto-planetary disks, because their internal degrees of freedom bear the signature of the physical conditions where these species reside. However, the promise that molecular emission has a strong diagnostic power of the underlying physical and chemical state is still hampered by the difficulty to combine sophisticated chemical codes with gas dynamics. It is therefore important 1) to acquire self-consistent data sets that can be used as templates for this theoretical work, and 2) to reveal the diagnostic capabilities of molecular lines accurately. The advent of sensitive wideband spectrometers in the (sub)- millimeter domain (e.g., IRAM-30m/EMIR, NOEMA, ...) during the 2010s has allowed us to image a significant fraction of a Giant Molecular Cloud with enough sensitivity to detect tens of molecular lines in the 70 - 116 GHz frequency range. Machine learning techniques applied to these data start to deliver the next generation of molecular line diagnostics of mass, density, temperature, and radiation field.

9. Learning from model grids: Tracers of the ionization fraction in the ISM, Emeric Bron, Evelyne Roueff, Maryvonne Gerin, Jérôme Pety, Pierre Gratier, Franck Le Petit, Guzmán, V. Viviana, Jan H. Orkisz, Victor de Souza Magalhães, Mathilde Gaudel, Pierre Palud, Lucas Einig, Sébastien Bardeau, Pierre Chainais, Jocelyn Chanussot, Javier Goicoechea, Annie Hughes, Jouni Kainulainen, David Languignon, Jacques Le Bourlot, François Levrier, Harvey S. Liszt, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, EPJ Web of Conferences, 2022, doi:10.1051/epjconf/202226500023

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.

8. Quantitative inference of the H2 column densities from 3 mm molecular emission: A case study towards Orion B, Pierre Gratier, Jérôme Pety, Emeric Bron, Antoine Roueff, Jan H. Orkisz, Maryvonne Gerin, Victor de Souza Magalhães, Mathilde Gaudel, Maxime Vono, Sébastien Bardeau, Jocelyn Chanussot, Pierre Chainais, Javier R. Goicoechea, Viviana V. Guzmán, Annie Hughes, Jouni Kainulainen, David Languignon, Jacques Le Bourlot, Franck Le Petit, François Levrier, Harvey S. Liszt, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, A&A, 2021, doi:10.1051/0004-6361/202037871

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.

7. Tracers of the ionization fraction in dense and translucent gas: I. Automated exploitation of massive astrochemical model grids, Emeric Bron, Evelyne Roueff, Maryvonne Gerin, Jérôme Pety, Pierre Gratier, Franck Le Petit, Viviana V. Guzmán, Jan H. Orkisz, Victor de Souza Magalhães, Mathilde Gaudel, Maxime Vono, Sébastien Bardeau, Pierre Chainais, Javier R. Goicoechea, Annie Hughes, Jouni Kainulainen, David Languignon, Jacques Le Bourlot, François Levrier, Harvey S. Liszt, Karin Öberg, Nicolas Peretto, Antoine Roueff, Albrecht Sievers, A&A, 2021, doi:10.1051/0004-6361/202038040

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.).

6. C18O, 13CO, and 12CO abundances and excitation temperatures in the Orion B molecular cloud: An analysis of the precision achievable when modeling spectral line within the Local Thermodynamic Equilibrium approximation, Antoine Roueff, Maryvonne Gerin, Pierre Gratier, Francois Levrier, Jérôme Pety, Mathilde Gaudel, Javier R. Goicoechea, Jan H. Orkisz, Victor de Souza Magalhães, Maxime Vono, Sébastien Bardeau, Emeric Bron, Jocelyn Chanussot, Pierre Chainais, Viviana V. Guzmán, Annie Hughes, Jouni Kainulainen, David Languignon, Jacques Le Bourlot, Franck Le Petit, Harvey S. Liszt, Antoine Marchal, Marc-Antoine Miville-Deschenes, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, A&A, 2021, doi:10.1051/0004-6361/202037776

Context. CO isotopologue transitions are routinely observed in molecular clouds for the purpose of probing the column density of the gas and the elemental ratios of carbon and oxygen, in addition to tracing the kinematics of the environment.
Aims. Our study is aimed at estimating the abundances, excitation temperatures, velocity field, and velocity dispersions of the three main CO isotopologues towards a subset of the Orion B molecular cloud, which includes IC 434, NGC 2023, and the Horsehead pillar.
Methods. We used the Cramer Rao bound (CRB) technique to analyze and estimate the precision of the physical parameters in the framework of local-thermodynamic-equilibrium (LTE) excitation and radiative transfer with added white Gaussian noise. We propose a maximum likelihood estimator to infer the physical conditions from the 1—0 and 2—1 transitions of CO isotopologues. Simulations show that this estimator is unbiased and proves efficient for a common range of excitation temperatures and column densities (Tex > 6 K, N > 1014-1015 cm-2).
Results. Contrary to general assumptions, the various CO isotopologues have distinct excitation temperatures and the line intensity ratios between different isotopologues do not accurately reflect the column density ratios. We find mean fractional abundances that are consistent with previous determinations towards other molecular clouds. However, significant local deviations are inferred, not only in regions exposed to the UV radiation field, but also in shielded regions. These deviations result from the competition between selective photodissociation, chemical fractionation, and depletion on grain surfaces. We observe that the velocity dispersion of the C18O emission is 10% smaller than that of 13CO. The substantial gain resulting from the simultaneous analysis of two different rotational transitions of the same species is rigorously quantified.
Conclusions. The CRB technique is a promising avenue for analyzing the estimation of physical parameters from the fit of spectral lines. Future works will generalize its application to non-LTE excitation and radiative transfer methods.

5. A dynamically young, gravitationally stable network of filaments in Orion B, Jan H. Orkisz, Nicolas Peretto, Jérôme Pety, Maryvonne Gerin, François Levrier, Emeric Bron, Sébastien Bardeau, Javier R. Goicoechea, Pierre Gratier, Viviana V. Guzmán, Annie Hughes, David Languignon, Franck Le Petit, Harvey S. Liszt, Karin Öberg, Evelyne Roueff, Albrecht Sievers, Pascal Tremblin, A&A, 2019, doi:10.1051/0004-6361/201833410

Context. Filaments are a key step on the path that leads from molecular clouds to star formation. However, their characteristics, for instance their width, are heavily debated and the exact processes that lead to their formation and fragmentation into dense cores still remain to be fully understood.
Aims. We aim at characterising the mass, kinematics, and stability against gravitational collapse of a statistically significant sample of filaments in the Orion B molecular cloud, which is renown for its very low star formation efficiency.
Methods. We characterised the gas column densities and kinematics over a field of 1.9 deg2, using C18O (J = 1—0) data from the IRAM 30 m large programme ORION-B at angular and spectral resolutions of 23.5″ and 49.5 kHz, respectively. Using two different Hessian-based filters, we extracted and compared two filamentary networks, each containing over 100 filaments.
Results. Independent of the extraction method, the filament networks have consistent characteristics. The filaments have widths of ~0.12 +/- 0.04 pc and show a wide range of linear (~1−100 M⊙ pc—1) and volume densities (~2 × 103— 2 × 105 cm-3). Compared to previous studies, the filament population is dominated by low-density, thermally sub-critical structures, suggesting that most of the identified filaments are not collapsing to form stars. In fact, only ~1% of the Orion B cloud mass covered by our observations can be found in super-critical, star-forming filaments, explaining the low star formation efficiency of the region. The velocity profiles observed across the filaments show quiescence in the centre and coherency in the plane of the sky, even though these profiles are mostly supersonic.
Conclusions. The filaments in Orion B apparently belong to a continuum which contains a few elements comparable to already studied star-forming filaments, for example in the IC 5146, Aquila or Taurus regions, as well as many lower density, gravitationally unbound structures. This comprehensive study of the Orion B filaments shows that the mass fraction in super-critical filaments is a key factor in determining star formation efficiency.

4. Clustering the Orion B giant molecular cloud based on its molecular emission, Emeric Bron, Chloé Daudon, Jérôme Pety, François Levrier, Maryvonne Gerin, Pierre Gratier, Jan H. Orkisz, Viviana Guzmán, Sébastien Bardeau, Javier R. Goicoechea, Harvey S. Liszt, Karin Öberg, Nicolas Peretto, Albrecht Sievers, Pascal Tremblin, A&A, 2018, doi:10.1051/0004-6361/201731833

Context. Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs).
Aims. We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud.
Methods. We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional probability density function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis.
Results. A clustering analysis based only on the J = 1—0 lines of three isotopologues of CO proves sufficient to reveal distinct density/column density regimes (nH~ 100 cm-3, 500 cm-3, and >1000 cm-3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1—0 line of HCO+ and the N = 1—0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH ~7 × 103cm-3, 4 × 104cm-3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1—0) lines. These distinctions are only possible because the high-density regions are spatially resolved.
Conclusions. Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers.

3. Dissecting the molecular structure of the Orion B cloud: Insight from Principal Component Analysis, Pierre Gratier, Emeric Bron, Maryvonne Gerin, Jérôme Pety, Viviana V. Guzmán, Jan H. Orkisz, Sébastien Bardeau, Javier R. Goicoechea, Franck Le Petit, Harvey S. Liszt, Karin Öberg, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, Pascal Tremblin, A&A, 2017, doi:10.1051/0004-6361/201629847

Context. The combination of wideband receivers and spectrometers currently available in (sub )millimeter observatories start to deliver wide-field hyperspectral imaging of the interstellar medium. Tens of spectral lines can be observed over degree wide fields in about fifty hours. This wealth of data calls for restating the physical questions about the interstellar medium in statistical terms.
Aims. We aim at gaining information on the physical structure of the interstellar medium from a statistical analysis of many lines from different species over a large field of view, without requiring detailed radiative transfer or astrochemical modeling.
Methods. We coupled a nonlinear rescaling of the data with one of the simplest multivariate analysis methods, namely the Principal Component Analysis, to decompose the observed signal into components that we interpret first qualitatively and then quantitatively based on our deep knowledge of the observed region and of the astrochemistry at play.
Results. We identify 3 principal components, linear composition of line brightness temperatures, that are correlated at various levels with the column density, the volume density and the UV radiation field.
Conclusions. When sampling a sufficiently diverse mixture of physical parameters are observed, it is possible to decompose the molecular emission in order to gain physical insight on the observed interstellar medium. This opens a new avenue for future studies of the interstellar medium.

2. Turbulence and star formation efficiency in molecular clouds: solenoidal versus compressive motions in Orion B, Jan H. Orkisz, Jérôme Pety, Maryvonne Gerin, Emeric Bron, Viviana V. Guzmán, Sébastien Bardeau, Javier R. Goicoechea, Pierre Gratier, Franck Le Petit, François Levrier, Harvey S. Liszt, Karin Öberg, Nicolas Peretto, Evelyne Roueff, Albrecht Sievers, Pascal Tremblin, A&A, 2017, doi:10.1051/0004-6361/201629220

Context. The nature of turbulence in molecular clouds is one of the key parameters that control star formation efficiency: compressive motions, as opposed to solenoidal motions, can trigger the collapse of cores, or mark the expansion of HII regions.
Aims. We try to observationally derive the fractions of momentum density (ρv) contained in the solenoidal and compressive modes of turbulence in the Orion B molecular cloud and relate these fractions to the star formation efficiency in the cloud.
Methods. The implementation of a statistical method applied to a 13CO (J = 1—0) datacube obtained with the IRAM-30m telescope, enables us to retrieve 3-dimensional quantities from the projected quantities provided by the observations, which yields an estimate of the compressive versus solenoidal ratio in various regions of the cloud.
Results. Despite the Orion B molecular cloud being highly supersonic (mean Mach number ∼ 6), the fractions of motion in each mode diverge significantly from equipartition. The cloud’s motions are, on average, mostly solenoidal (excess > 8% with respect to equipartition), which is consistent with its low star formation rate. On the other hand, the motions around the main star forming regions (NGC 2023 and NGC 2024) prove to be strongly compressive.
Conclusions. We have successfully applied to observational data a method that has so far only been tested on simulations, and we have shown that there can be a strong intra-cloud variability of the compressive and solenoidal fractions, these fractions being in turn related to the star formation efficiency. This opens a new possibility for star formation diagnostics in galactic molecular clouds.

1. The anatomy of the Orion B Giant Molecular Cloud: A local template for studies of nearby galaxies, Jérôme Pety, Viviana V. Guzmán, Jan H. Orkisz, Harvey S. Liszt, Maryvonne Gerin, Emeric Bron, Sébastien Bardeau, Javier R. Goicoechea, Pierre Gratier, Franck Le Petit, François Levrier, Karin Öberg, Evelyne Roueff, Albrecht Sievers, A&A, 2017, doi:10.1051/0004-6361/201629862

Context. Molecular lines and line ratios are commonly used to infer properties of extra-galactic star forming regions. The new generation of millimeter receivers almost turns every observation into a line survey. Full exploitation of this technical advancement in extra-galactic study requires detailed bench-marking of available line diagnostics.
Aims. We aim to develop the Orion B Giant Molecular Cloud (GMC) as a local template for interpreting extra-galactic molecular line observations.
Methods. We use the wide-band receiver at the IRAM-30 m to spatially and spectrally resolve the Orion B GMC. The observations cover almost 1 square degree at 26'' resolution with a bandwidth of 32 GHz from 84 to 116 GHz in only two tunings. Among the mapped spectral lines are the 12CO, 13CO, C18O, C17O, HCN, HNC, 12CN, C2H, HCO+, N2H+ (1—0), and 12CS, 32SO, SiO, c-C3H2, CH3OH (2—1) transitions.
Results. We introduce the molecular anatomy of the Orion B GMC, including relationships between line intensities and gas column density or far-UV radiation fields, and correlations between selected line and line ratios. We also obtain a dust-traced gas mass that is less than approximately one third the CO-traced mass, using the standard XCO conversion factor. The presence of over-luminous CO can be traced back to the dependence of the CO intensity on UV illumination. As a matter of fact, while most lines show some dependence on the UV radiation field, CN and C2H are the most sensitive. Moreover, dense cloud cores are almost exclusively traced by N2H+. Other traditional high-density tracers, such as HCN(1—0), are also easily detected in extended translucent regions at a typical density of ∼500 H2.cm-3. In general, we find no straightforward relationship between line critical density and the fraction of the line luminosity coming from dense gas regions.
Conclusions. Our initial findings demonstrate that the relationships between line (ratio) intensities and environment in GMCs are more complicated than often assumed. Sensitivity (i.e., the molecular column density), excitation, and, above all, chemistry contribute to the observed line intensity distributions, and they must be considered together when developing the next generation of extra-galactic molecular line diagnostics of mass, density, temperature, and radiation field.