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Albrecht Sievers

Publications and source records attributed to Albrecht Sievers.

At least 19 recordsLinked to original sources

Chemical diversity of dense cores in Orion B: The role of the environment

Prestellar cores are the sites of the earliest stages of star formation. Dust continuum observations are often used to identify and characterize their properties yet only a small fraction of them was observed and studied in terms of their composition and dynamical status. We explore the chemical diversity of prestellar cores and protostellar cores residing in the Orion B giant molecular cloud selected on their dust continuum emission to provide an unbiased view of their line emission properties and how they vary as function of the core parameters and environment. We make use of the large scale maps of Orion B in 25 molecular lines from which we extract information for a sample of 1001 cores selected using positions extracted from \textit{Herschel} dust continuum observations. The main properties of the core sample are derived using the Principal Component Analysis and additional maps of physical parameters: column density $N_{\rm{H_2}}$, far-ultraviolet (FUV) radiation field $G_0$ and mean volume gas density $n$. Additional high spectral resolution observations of $\rm C^{18}O(1-0)$ serve to evaluate the dynamical status of cores. The average line width of the cores is larger than what is typically expected for prestellar cores of closer star forming regions, which suggests that cores in Orion B are subjected to stronger turbulence affecting their stability. The first factor of the PCA analysis explaining the variation of the detected line intensities is the core column density of molecular gas. The second factor explains how the core chemical composition is strictly linked to their environment, which can be traced by the ratio of the external FUV radiation field over the core volume density, $G_0/n$. The third factor explaining the core chemical diversity is the mean density along the core line of sight, which is also associated with freeze-out and fractionation signatures.

astro-ph.GA

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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Estimating the dense gas mass of molecular clouds using spatially unresolved 3 mm line observations

We aim to develop a new method to infer the sub-beam probability density function (PDF) of H2 column densities and the dense gas mass within molecular clouds using spatially unresolved observations of molecular emission lines in the 3 mm band. We model spatially unresolved line integrated intensity measurements as the average of an emission function weighted by the sub-beam column density PDF. The emission function, which expresses the line integrated intensity as a function of the gas column density, is an empirical fit to high resolution (< 0.05 pc) multi-line observations of the Orion B molecular cloud. The column density PDF is assumed to be parametric, composed of a lognormal distribution at moderate column densities and a power law distribution at higher column densities. To estimate the sub-beam column density PDF, the emission model is combined with a Bayesian inversion algorithm (the Beetroots code), which takes account of thermal noise and calibration errors. We validate our method by demonstrating that it recovers the true column density PDF of the Orion B cloud, reproducing the observed emission line integrated intensities. We apply the method to 12CO(J=1-0), 13CO(J=1-0), C18O(J=1-0), HCN(J=1-0), HCO+(J=1-0) and N2H+(J=1-0) observations of a 700 x 700 pc2 field of view (FoV) in the nearby galaxy M51. On average, the model reproduces the observed intensities within 30%. The column density PDFs obtained for the spiral arm region within our test FoV are dominated by a power-law tail at high column densities, with slopes that are consistent with gravitational collapse. Outside the spiral arm, the column density PDFs are predominantly lognormal, consistent with supersonic isothermal turbulence. We calculate the mass associated with the powerlaw tail of the column density PDFs and observe a strong, linear correlation between this mass and the 24$\mu$m surface brightness.

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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.

astro-ph.IM

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.

astro-ph.GA

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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X-ray and multiwavelength polarization of Mrk 501 from 2022 to 2023

We present multiwavelength polarization measurements of the luminous blazar Mrk~501 over a 14-month period. The 2--8 keV X-ray polarization was measured with the Imaging X-ray Polarimetry Explorer (IXPE) with six 100-ks observations spanning from 2022 March to 2023 April. Each IXPE observation was accompanied by simultaneous X-ray data from NuSTAR, Swift/XRT, and/or XMM-Newton. Complementary optical-infrared polarization measurements were also available in the B, V, R, I, and J bands, as were radio polarization measurements from 4.85 GHz to 225.5 GHz. Among the first five IXPE observations, we did not find significant variability in the X-ray polarization degree and angle with IXPE. However, the most recent sixth observation found an elevated polarization degree at $>3\sigma$ above the average of the other five observations. The optical and radio measurements show no apparent correlations with the X-ray polarization properties. Throughout the six IXPE observations, the X-ray polarization degree remained higher than, or similar to, the R-band optical polarization degree, which remained higher than the radio value. This is consistent with the energy-stratified shock scenario proposed to explain the first two IXPE observations, in which the polarized X-ray, optical, and radio emission arises from different regions.

astro-ph.HE

The flaring activity of blazar AO 0235+164 during year 2021

Context. The blazar AO 0235+164, located at redshift $z=0.94$, has displayed interesting and repeating flaring activity in the past, the latest episodes occurring in 2008 and 2015. In 2020, the source brightened again, starting a new flaring episode that peaked in 2021. Aims. We study the origin and properties of the 2021 flare in relation to previous studies and the historical behavior of the source, in particular to the 2008 and 2015 flaring episodes. Methods. We analyze the multi-wavelength photo-polarimetric evolution of the source. From Very Long Baseline Array images, we derive the kinematic parameters of new components associated with the 2021 flare. We use this information to constrain a model for the spectral energy distribution of the emission during the flaring period. We propose an analytical geometric model to test whether the observed wobbling of the jet is consistent with precession. Results. We report the appearance of two new components that are ejected in a different direction than previously, confirming the wobbling of the jet. We find that the direction of ejection is consistent with that of a precessing jet.The derived period independently agrees with the values commonly found in the literature. Modeling of the spectral energy distribution further confirm that the differences between flares can be attributed to geometrical effects.

astro-ph.HE

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{\'e}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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Magnetic Field Properties inside the Jet of Mrk 421: Multiwavelength Polarimetry Including the Imaging X-ray Polarimetry Explorer

We conducted a polarimetry campaign from radio to X-ray wavelengths of the high-synchrotron-peak (HSP) blazar Mrk 421, including Imaging X-ray Polarimetry Explorer (IXPE) measurements on 2022 December 6-8. We detected X-ray polarization of Mrk 421 with a degree of $\Pi_{\rm X}$=14$\pm$1$\%$ and an electric-vector position angle $\psi_{\rm X}$=107$\pm$3$^{\circ}$ in the 2-8 keV band. From the time variability analysis, we find a significant episodic variation in $\psi_{\rm X}$. During 7 months from the first IXPE pointing of Mrk 421 in 2022 May, $\psi_{\rm X}$ varied across the range of 0$^{\circ}$ to 180$^{\circ}$, while $\Pi_{\rm X}$ maintained similar values within $\sim$10-15$\%$. Furthermore, a swing in $\psi_{\rm X}$ in 2022 June was accompanied by simultaneous spectral variations. The results of the multiwavelength polarimetry show that the X-ray polarization degree was generally $\sim$2-3 times greater than that at longer wavelengths, while the polarization angle fluctuated. Additionally, based on radio, infrared, and optical polarimetry, we find that rotation of $\psi$ occurred in the opposite direction with respect to the rotation of $\psi_{\rm X}$ over longer timescales at similar epochs. The polarization behavior observed across multiple wavelengths is consistent with previous IXPE findings for HSP blazars. This result favors the energy-stratified shock model developed to explain variable emission in relativistic jets. The accompanying spectral variation during the $\psi_{\rm X}$ rotation can be explained by a fluctuation in the physical conditions, e.g., in the energy distribution of relativistic electrons. The opposite rotation direction of $\psi$ between the X-ray and longer-wavelength polarization accentuates the conclusion that the X-ray emitting region is spatially separated from that at longer wavelengths.

astro-ph.HE

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.

astro-ph.GA

IXPE and multi-wavelength observations of blazar PG 1553+113 reveal an orphan optical polarization swing

The lower energy peak of the spectral energy distribution of blazars has commonly been ascribed to synchrotron radiation from relativistic particles in the jets. Despite the consensus regarding jet emission processes, the particle acceleration mechanism is still debated. Here, we present the first X-ray polarization observations of PG 1553+113, a high-synchrotron-peak blazar observed by the Imaging X-ray Polarimetry Explorer (IXPE). We detect an X-ray polarization degree of $(10\pm2)\%$ along an electric-vector position angle of $\psi_X=86^{\circ}\pm8^{\circ}$. At the same time, the radio and optical polarization degrees are lower by a factor of $\sim$3. During our IXPE pointing, we observed the first orphan optical polarization swing of the IXPE era, as the optical angle of PG 1553+113 underwent a smooth monotonic rotation by about 125$^\circ$, with a rate of $\sim$17 degrees per day. We do not find evidence of a similar rotation in either radio or X-rays, which suggests that the X-ray and optically emitting regions are separate or, at most, partially co-spatial. Our spectro-polarimetric results provide further evidence that the steady-state X-ray emission in blazars originates in a shock-accelerated and energy-stratified electron population.

astro-ph.HE

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,

astro-ph.IM

X-ray Polarization of BL Lacertae in Outburst

We report the first $> 99\%$ confidence detection of X-ray polarization in BL Lacertae. During a recent X-ray/$\gamma$-ray outburst, a 287 ksec observation (2022 November 27-30) was taken using the Imaging X-ray Polarimetry Explorer ({\it IXPE}), together with contemporaneous multiwavelength observations from the Neil Gehrels {\it Swift} observatory and {\it XMM-Newton} in soft X-rays (0.3--10~keV), {\it NuSTAR} in hard X-rays (3--70~keV), and optical polarization from the Calar Alto, and Perkins Telescope observatories. Our contemporaneous X-ray data suggest that the {\it IXPE} energy band is at the crossover between the low- and high-frequency blazar emission humps. The source displays significant variability during the observation, and we measure polarization in three separate time bins. Contemporaneous X-ray spectra allow us to determine the relative contribution from each emission hump. We find $>99\%$ confidence X-ray polarization $\Pi_{2-4{\rm keV}} = 21.7^{+5.6}_{-7.9}\%$ and electric vector polarization angle $\psi_{2-4{\rm keV}} = -28.7 \pm 8.7^{\circ}$ in the time bin with highest estimated synchrotron flux contribution. We discuss possible implications of our observations, including previous {\it IXPE} BL Lacertae pointings, tentatively concluding that synchrotron self-Compton emission dominates over hadronic emission processes during the observed epochs.

astro-ph.HE

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.

astro-ph.GA

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]

astro-ph.GA

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)

astro-ph.GA

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

CO isotopologue transitions are routinely observed in molecular clouds to probe the column density of the gas, the elemental ratios of carbon and oxygen, and to trace the kinematics of the environment. We aim 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. We use the Cramer Rao Bound (CRB) technique to analyze and estimate the precision of the physical parameters in the framework of local-thermodynamic-equilibrium excitation and radiative transfer with an additive 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 efficient for a common range of excitation temperatures and column densities (Tex > 6 K, N > 1e14 - 1e15 cm-2). Contrary to the general assumptions, the different 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 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. The CRB technique is a promising avenue for analyzing the estimation of physical parameters from the fit of spectral lines.

astro-ph.GA