Column Density Research Articles

Regarding the Detection of Interstellar C4 and C5 Molecules

Abstract Analysis of very high signal-to-noise ratio (S/N) spectra of reddened stars allowed us to determine an upper limit (UL) of the column density N(C4). We developed a robust calibration of the N(C4) based on the C4 gas-phase spectrum profile at 3789 Å. The UL of the column density can be calculated using the equation N UL(C4) = 8.963 × 1015/(S/N), where S/N is in the wavelength range ∼3790 Å. Nondetection of this molecule was confirmed in stars exhibiting a high abundance of C2 and C3 molecules. According to our calibration, assuming an optimistic estimate of the ratio N ( C 3 ) N ( C 4 ) = 10, even for the star HD 147889 with the highest known to date column density of C3, the S/N required for detecting the C4 molecule is about 12,000 per pixel, which is a challenging task. Despite this tough conclusion regarding the possibility of detecting the interstellar molecule C4, we also tried to find a link between known lines of C5 at 4975 and 5109 Å and weak interstellar features. The expected C5 4975 Å feature coincides well with weak diffuse interstellar band (DIB) 4975, while the search for the 5109 Å C5 band is badly conditioned by the overlap with a broad spectral feature, which is a blend of stellar and interstellar lines. However, we found a rather good correlation between the equivalent width of DIB 4975 and N(C2), making the search for C5 not hopeless. If DIB 4975 is formed by C5, its column density is only 2 times lower than that of C3.

A Global Census of Metals in the Universe

Abstract We present a census of the mass density of metals and their evolution with cosmic time on a global scale throughout the Universe, synthesizing robust estimates of metals in stars, hot intracluster gas, and gaseous absorbers tracing neutral gas as well as ionized gas in the circumgalactic and intergalactic media. We observe an order of magnitude increase in the stellar metal mass density from z ∼ 2.5 to 0.7, over which time stars emerge as the most important metal reservoir at low redshifts, housing ∼30% of the total expected metal density at z ∼ 0.1. Hot virialized intracluster/intragroup gas accounts for ∼15% and 10% of metals at z ∼ 0.1 and 0.7, respectively. Using metallicity measurements from the COS CGM Compendium, KODIAQ-Z, and the HD-LLS surveys covering redshifts z < 1 to z ∼ 2–3.5, we investigate the global distribution of metals in extragalactic cool ionized gas as a function of H i column density. During the period from z ≈ 3 to z < 1, the global metal density of cool (T ∼ 104−5 K) gas has doubled. However, the fractional contribution of the ionized gas to the total expected metal density decreased from ∼20% at z ∼ 3 to ∼4% at z < 1. The cosmic metal density of all gas phases has increased with cosmic time, reflecting an “inside-out” metal dispersion by feedback mechanisms and galactic outflows.

An Extremely Metal-poor Lyα Emitter Candidate at z = 6 Revealed through Absorption Spectroscopy

Abstract We report the discovery of a Lyα emitter (LAE) candidate in the immediate foreground of the quasar PSO J158-14 at z QSO = 6.0685 at a projected distance ∼29 pkpc that is associated with an extremely metal-poor absorption system. This system was found in archival observations of the quasar field with the Very Large Telescope (VLT)/Multi-Unit Spectroscopic Explorer (MUSE) and was previously missed in searches of absorption systems using quasar absorption line spectroscopy, as it imparts no detectable metal absorption lines on the background quasar spectrum. The detected Lyα emission line at a redshift of z LAE = 6.0323 is well aligned with the outer edge of the quasar’s proximity zone and can plausibly cause its observed damping wing if it is associated with a proximate subdamped Lyα absorption system with a column density of log N HI / cm − 2 ≈ 19.7 . A >10 hr medium-resolution spectrum of the quasar observed with the Magellan/Folded-port InfraRed Echellette (FIRE) and VLT/X-Shooter spectrographs reveals a metallicity constraint of [Z/H] < −3. Such low metallicity makes this system an extremely metal-poor galaxy candidate and provides an exciting site to study possible signatures of Population III stars.

A New High-latitude H i Cloud Complex Entrained in the Northern Fermi Bubble

Abstract We report the discovery of 11 high-velocity H i clouds at Galactic latitudes of 25°–30°, likely embedded in the Milky Way’s nuclear wind. The clouds are detected with deep Green Bank Telescope 21 cm observations of a 3 . ° 2 × 6 . ° 2 field around QSO 1H1613-097, located behind the northern Fermi Bubble. Our measurements reach 3σ limits on N HI as low as 3.1 × 1017 cm−2, more than twice as sensitive as previous H i studies of the bubbles. The clouds span −180 ≤ v LSR ≤ −90 km s−1 and are the highest-latitude 21 cm high-velocity cloud detected inside the bubbles. Eight clouds are spatially resolved, showing coherent structures with sizes of 4–28 pc, peak column densities of log(N HI/cm2) = 17.9–18.7, and H i masses up to 1470 M ⊙. Several exhibit internal velocity gradients. Their presence at such high latitudes is surprising, given the short expected survival times for clouds expelled from the Galactic center. These objects may be fragments of a larger cloud disrupted by interaction with the surrounding hot gas.

Maximizing the scientific application of Pandora column observations of HCHO and NO2

Abstract. As part of the Pandonia Global Network (PGN), Pandora spectrometers are widely deployed around the world. These ground-based remote-sensing instruments are federated such that they employ a common algorithm and data protocol for reporting on trace gas column densities and lower-atmospheric profiles using two modes based on direct-sun and sky-scan observations. To aid users in the analysis of Pandora observations, the PGN standard quality flagging procedure assigns flags to the data indicating high, medium, and low quality. This work assesses the suitability of these data quality flags for filtering data in the scientific analysis of formaldehyde (HCHO) and nitrogen dioxide (NO2), two critical precursors controlling tropospheric ozone production. Pandora data flagged as high quality assure scientifically valid data and are often more abundant for direct-sun NO2 columns. For direct-sun HCHO and for sky-scan observations of both molecules, large amounts of data flagged as low quality also appear to be valid. Upon closer inspection of the data, independent uncertainty is shown to be a better indicator of data quality than the standard quality flags. After applying a filter to independent uncertainty, Pandora data flagged as medium or low quality in both modes can be demonstrated to be scientifically useful. The utility of this filtering method is demonstrated by correlating contemporaneous but independent direct-sun and sky-scan observations. When evaluated across 15 Pandora sites in North America, this new filtering method can recover as much as 90 % of data that would have previously been discarded. This method suggests that standard PGN criteria for atmospheric variability and the normalized root mean squared error are too stringent, as they are responsible for downgrading most of the recovered data. A method is also developed for combining the direct-sun and sky-scan observations into a single dataset by accounting for biases between the two observing modes and differences in measurement integration times. These combined data provide a more continuous record that is useful for interpreting Pandora observations against other independent variables such as hourly observations of surface ozone. When Pandora HCHO columns are correlated with surface ozone measurements, data filtered by independent uncertainty exhibit similarly strong and more robust relationships than high-quality data alone. These results suggest that Pandora data users should carefully assess data across all quality flags and consider their potential for useful application to scientific analysis. The present study provides a method for maximizing use of Pandora data with the expectation of more robust satellite validation and comparisons with ground-based observations in support of air quality studies.

Modeling Mgii Resonance Doublet Spectra from Star-forming Galaxies at z ~ 1

Abstract We investigate the properties of cold gas at $10^4~\rm K$ around star-forming galaxies at z ~ 1 using Mg II spectra through radiative transfer modeling. We utilize a comprehensive dataset of 624 galaxies from the MAGG and MUDF programs. We focus on Mg II emission from galaxies and their outskirts to explore the cold gas within galaxies and the circumgalactic medium (CGM). We model Mg II spectra for 167 individual galaxies and stacked data for different stellar mass bins. The Mg II spectrum and surface brightness vary significantly with stellar mass. In low-mass galaxies (M*/M⊙ < 109), Mg II emission is observed in both core (Rp < 10 kpc) and halo regions (10 kpc <Rp < 30 kpc), while in higher mass galaxies (M*/M⊙ > 1010), strong core absorption and more extended halo emission are prominent. This indicates that more massive galaxies have more cold gas. Radiative transfer modeling allows us to investigate key parameters such as the Mg II column density NMgII and the outflow velocity vexp. We identify a negative correlation between NMgII and vexp. Since higher stellar mass galaxies exhibit a higher NMgII and lower vexp, this suggests an abundance of slowly moving cold gas in massive galaxies. In addition, the fitting results of halo spectra indicate the presence of intrinsic Mg II absorption and strong anisotropy of the cold gas distribution around massive galaxies. This study is not only a proof-of-concept of modeling spatially varying Mg II spectra but also enhances our understanding of the CGM and provides insights into the mass-dependent properties of cold gas in and around galaxies.

Narrow absorption lines from intervening material in supernovae. II. Galaxy properties

The interstellar medium (ISM) has a number of tracers such as the łambdałambda 5890, 5896 absorption lines that are evident in the spectra of galaxies but also in those of individual astrophysical sources such as stars, novae, or quasars. Here, we investigate narrow absorption features in the spectra of nearby supernovae (SNe) and compare them to local ($<0.5$ kpc) and global host galaxy properties. With a large and heterogeneous sample of spectra, we are able to recover the known relations of ISM with galaxy properties: larger columns of ISM gas are found in environments that are more massive, more actively star-forming, younger, and viewed from a more inclined angle. Most trends are stronger for local properties than global properties, and we find that the ISM column density decreases exponentially with the offset from the host galaxy centre, as expected for a gas distribution following an exponential radial profile. We also confirm trends for the velocity of galactic outflows increasing with radius. The current study demonstrates the capability of individual light sources to serve as ubiquitous tracers of ISM properties across various environments and galaxies.

BASIL: Fast broadband line-rich spectral-cube fitting and image visualization via Bayesian quadrature

Mapping the spatial distributions and abundances of complex organic molecules in hot cores and hot corinos surrounding nascent stars is crucial for understanding the astrochemical pathways and the inheritance of prebiotic material by nascent planetary systems. However, the line-rich spectra from these sources pose significant challenges for robustly fitting molecular parameters due to severe line blending and unidentified lines. We present an efficient framework, Bayesian Active Spectral-cube Inference and Learning (BASIL), for estimating molecular parameter maps -- excitation temperature, column density, centroid velocity, and line width -- for hundreds of molecules based on the local thermodynamic equilibrium (LTE) model, applied to wideband spectral datacubes of line-rich sources. The main aim is to allow the simultaneous fitting of hundreds of molecules to disentangle line blending issues and map the kinematic and abundance spatial distributions of the molecular parameter maps. We adopted stochastic variational inference (SVI) to infer molecular parameters from spectra at individual positions, achieving a balance between fitting accuracy and computational speed. For obtaining parameter maps, instead of querying every location or pixel, we introduced an active learning framework based on Bayesian quadrature and its parallelization. Specifically, we assessed and selected the locations or pixels of spectrum that are most informative for estimating the entire set of parameter maps by training a Gaussian processes (GP) model. By greedily selecting locations with maximum information gain, we achieve sublinear convergence: the estimation error of the GP model for parameter maps drops rapidly in the early stages of iterations and then stabilizes. At this point, we can halt the fitting process, providing a fast and reasonably accurate visualization of the molecular parameter maps, while further accuracy is obtained through additional iterations of model training by querying more locations. We benchmarked our algorithm using a synthetic spectral cube of 40,000 ($200 200$) pixels, in which each pixel contains 138,016 frequency grids, and fit an LTE model with SVI to obtain four spectral parameters for a list of 117 molecules (117times4 dimensions). Our algorithm is able to estimate 468 molecule parameter maps for 40,000 pixels in ∼180 hours (18 iterations of 50 parallel fittings, ∼10 hours per batch), achieving a comparable root mean square error across all data points. The full analysis is done on a high-memory server with multi-core CPUs. In contrast, a traditional MCMC fitting would take approximately ∼ 2 10^6 hours to achieve the same level of accuracy, while requiring significant manual tuning. In particular, with two iterations of ∼20 hours computational time, the GP model predicts parameter maps that are visually accurate. Additional training iterations provide progressively more accurate results. This quick visualization meets the demands of big data in modern astronomical surveys.

Investigate the GeV gamma-ray emissions from the Perseus molecular cloud

ABSTRACT We study the GeV gamma-ray emissions toward the dense cores IC 348, NGC 1333, and Barnard 1 (B1) with a scale of about 5 pc in the Perseus molecular cloud (MC) using the Fermi Large Area Telescope. We reconstruct a background model and find that the column density distribution of molecular hydrogen (H$_2$) + neutral atomic hydrogen (${\rm H\, {\small I}}$) + dark gas template provides the best-fitting template for spatial analysis, which supports a hadronic origin of the gamma-ray emissions from the dense cores in the Perseus MC. All three cores exhibit hard gamma-ray spectra (photon index $\sim$2.3), which are consistent with those of young massive star clusters. The gamma-ray spectra of IC 348 and B1 are higher than those derived from the local cosmic rays (CRs), likely originating from inelastic interactions between protons accelerated by massive stellar winds and ambient gas. The gamma-ray spectrum of NGC 1333 exhibits a slight excess above 2 GeV, but a slight deficit below 2 GeV when compared to the spectrum derived from the local CRs. We argue that the suppression of the CR spectrum in NGC 1333 is probably caused by the slow diffusion of CRs, and the distinct characteristic compared to the other two cores may be linked to its nature as a reflection nebula.

Observed Latitudinal, Longitudinal and Temporal Variability of Io's Atmosphere Simulated by a Purely Sublimation Driven Atmosphere

Abstract How much of Io's atmosphere is driven by volcanic outgassing or sublimation of surface frost is a question with a considerable history. We develop a time dependent surface temperature model including thermal inertia and the exact celestial geometry to model the radiation driven global structure and temporal evolution of Io's atmosphere. We show that many observations can be explained by assuming a purely sublimation driven atmosphere. We find that a thermal diffusivity yields an averaged atmospheric column density decreasing by more than one order of magnitude from the equator to the poles in accordance with the observed spatial variations of Io's column densities. Our model produces a strong day‐night‐asymmetry with modeled column density variations of almost two orders of magnitude at the equator as well as a sub‐anti‐Jovian hemisphere asymmetry, with maximum dayside column densities of for the sub‐Jovian and for the anti‐Jovian hemisphere. Both are consistent with the observed temporal and large‐scale longitudinal variation of Io's atmosphere. We find that the diurnal variations of the surface temperature affect the subsurface structure up to a depth of 0.6 m. Furthermore, we quantify seasonal effects with Io having a northern summer close to perihelion and a northern winter close to aphelion. Finally, we found that at Io's anomalous warm polar regions a conductive heat flux of at least 1.2 is necessary to reach surface temperatures consistent with observations.

Delving into the depths of NGC 3783 with XRISM

We present our study of the X-Ray Imaging and Spectroscopy Mission (XRISM) observation of the Seyfert-1 galaxy NGC 3783. XRISM’s Resolve microcalorimeter has enabled, for the first time, a detailed characterization of the highly ionized outflows in this active galactic nucleus. Our analysis constrains their outflow and turbulent velocities, along with their ionization parameter (ξ) and column density (NH). The high-resolution Resolve spectrum reveals a distinct series of Fe absorption lines between 6.4 and 7.8 keV, ranging from Fe XVIII to Fe XXVI. At lower energies (1.8−3.3 keV), absorption features from Si, S, and Ar are also detected. Our spectroscopy and photoionization modeling of the time-averaged Resolve spectrum uncovers six outflow components, five of which exhibit relatively narrow absorption lines with outflow velocities ranging from 560 to 1170 km s−1. In addition, a broad absorption feature is detected, which is consistent with Fe XXVI outflowing at 14 300 km s−1 (0.05 c). The kinetic luminosity of this component is 0.8−3% of the bolometric luminosity. Our analysis of the Resolve spectrum shows that more highly ionized absorption lines are intrinsically broader than those of lower-ionization species, indicating that the turbulent velocity of the six outflow components (ranging from 0 to 3500 km s−1) increases with ξ. Furthermore, we find that the column density (NH) of the outflows generally declines with the ionization parameter up to log ξ = 3.2 but rises beyond this point, suggesting a complex ionization structure. The absorption profile of the Fe XXV resonance line is intriguingly similar to UV absorption lines (Lyα and C IV) observed by the Hubble Space Telescope, from which we infer that the outflows are clumpy in nature. Our XRISM/Resolve results from lower- and higher-ionization regimes support a “hybrid wind” scenario in which the observed outflows have multiple origins and driving mechanisms. We explore various interpretations of our findings within active galactic nucleus wind models.

The most massive star clusters in molecular clouds: Insights from the integrated cloud-wide initial mass function (ICIMF) theory

Abstract The combination of the high-resolution ALMA, JWST and HST observations provides unprecedented insights into the connection between individual molecular clouds and their internal stellar populations in nearby galaxies. The molecular clouds in five nearby galaxies were identified based on the integrated intensity maps of CO (2−1) emission from ALMA observations. We used the JWST 21 $\mu$m data to estimate the star formation rate (SFR) surface density of the clouds and calculate the masses of the embedded stellar populations in the clouds. After matching the star cluster and stellar association catalogs derived from the HST observations with the identified molecular clouds, we found clear correlations between the physical parameters of molecular clouds and their internal stellar populations. Based on the masses of the total stellar populations and their corresponding clouds, we obtained a typical value of the cloud-scale star formation efficiency (SFE), ≈1.4 %. The mass of the most massive cluster (Mcluster, max) in a cloud is positively proportional to the mass (Mcloud), the column density, the SFR sand the SFR surface density of the cloud. The observed Mcluster, max − Mcloud relation can be interpreted theoretically on the basis of the integrated cloud-wide IMF (ICIMF) theory, which provides a quantitative framework for understanding the correlations between molecular clouds and their internal stellar populations.

Sensitivity of the neutrino transmission coefficient at high energies to the Earth’s density profile

Abstract The flux of atmospheric and astrophysical neutrinos measured in {\bf ultra - high - energy} neutrino detectors is strongly dependent on the description of the propagation and absorption of the neutrinos during the passage through Earth to the detector. In particular, the attenuation of the incident neutrino flux depends on the details of the matter structure between the source and the detector. In this paper, we will investigate the impact of different descriptions for the density profile of Earth on the transmission coefficient, defined as the ratio between the flux measured in the detector and the incoming neutrino flux. We will consider five different models for the Earth's density profile and estimate how these different models modify the target column density and transmission coefficients for different flavors. The results are derived by solving the cascade equations taking into account the {\bf neutral current} interactions and tau regeneration. A comparison with approximated solutions is also presented. Our results indicated that the predictions are sensitive to the model considered for the density profile, with the simplified three layer model providing a satisfactory description when compared with the {\bf Preliminary Reference Earth Model} results. {\bf Our results also showed that the more simplified models with two or one layer fail mainly for neutrinos that cross a small column of matter and are not good approximations for the neutrino propagation. These findings highlight the importance of using realistic Earth density models in ultra-high-energy neutrino analyses, as simplified models may lead to misestimations in the predicted attenuation effects.

MINDS: Water reservoirs of compact planet-forming dust discs

Context. Millimetre-compact dust discs are thought to have efficient radial drift of icy dust pebbles. It has been hypothesised that this drift could produce an enhanced cold (T < 400 K) H2O reservoir in their inner discs. Mid-infrared spectral surveys, now including the James Webb Space Telescope (JWST), pave the way to explore this hypothesis. In this work, we test this theory for eight compact discs (Rdust < 60 au) with JWST-MIRI/MRS observations. Aims. To explore the H2O distribution in the inner discs and consider whether these discs are enhanced in cold H2O emission, we analyse the different reservoirs that can be probed with the pure rotational lines (>10 µm) by JWST: hot (T > 800 K), intermediate (400 < T < 800 K), and cold (T < 400 K). Methods. We probed the H2O reservoirs with JWST-MIRI observations for a sample of eight compact discs through parametric column density profiles (power laws, jump abundances, and parabolas), multiple-component (two or three) slab models, and line flux ratios. Results. We find that not all compact discs show strong enhancements of the cold H2O reservoir; instead, we propose three different classes of inner disc H2O distributions. Four of our discs (BP Tau, CY Tau, DR Tau, and RNO 90; i.e. type N or ‘normal’ discs) appear to have similar H2O distributions to many of the large and structured discs, as indicated by the slab model fitting and the line flux ratios. These discs have a small cold reservoir, suggesting the inward drift of dust, but it is not as efficient as hypothesised before. Only two discs (FT Tau and XX Cha; type E or cold H2O enhanced discs) do show a strong enhancement of the cold H2O emission, in agreement with the original hypothesis. The two remaining discs (CX Tau and DN Tau; type P or H2O-poor discs) are found to be very H2O-poor, yet they show emission from either the hot or immediate reservoirs (depending on the fit) in addition to emission from the cold one. For the three types, we find that different parametrisation schemes are able to provide a good description of the observed H2O spectra. Overall, a jump abundance at a free temperature is amongst the preferred profiles for all three types, suggesting that this profile can provide a good description of the observed reservoirs for most discs. The multiple-component analysis yields similar results to those of the parametric models. However, in some cases, a power law can give an entirely different distribution compared to the other parametric models. Finally, we also report the detection of other molecules in these discs, including a tentative detection of CH4 in CY Tau. Conclusions. Not all compact discs follow the hypothesis that their cold H2O reservoir is enhanced following efficient radial drift. Therefore, we introduced a classification based on the observed H2O reservoirs, which should hold for all (isolated) discs: type N, type E, and type P. Type N discs are considered to behave as many other (large and structured) discs, with all three reservoirs present; yet the cold emission is not enhanced. The type E discs show strong enhancements of the cold H2O emission, while the type P discs are generally H2O-poor.

The Robust Detection and Spatial Distribution of Acetaldehyde in Orion KL: Atacama Large Millimeter/submillimeter Array Observations and Chemical Modeling

Abstract Despite the organic molecule inventory detected in the Orion Kleinmann–Low Nebula (Orion KL), acetaldehyde (CH3CHO)—one of the most ubiquitous interstellar aldehydes—has not been firmly identified with millimeter-wave interferometry. We analyze extensive Atacama Large Millimeter/submillimeter Array archival data sets (142–355 GHz) to search for acetaldehyde, revealing two distinct acetaldehyde emission peaks and one component with more complex kinematic structures. One peak aligns with MF10/IRc2, where emissions of other O-bearing complex organic molecules are rarely reported, while the other is coincident with the ethanol peak in the southwest region of the hot core. The MF10/IRc2 detection suggests unique chemistry, possibly influenced by repeated heating events. In contrast, codetection with ethanol indicates an ice origin and suggests a potential chemical relationship between the two species. We determine acetaldehyde column densities and kinetic temperatures toward these two peaks under local thermodynamic equilibrium assumptions and compare its distribution with ethanol and other molecules that have an aldehyde (HCO) group, such as methyl formate, glycolaldehyde, and formic acid. Toward the ethanol peak, the observed abundance ratios between HCO-containing species are analyzed using a chemical model. The model suggests two key points: (1) the destruction of ethanol to form acetaldehyde in the ice may contribute to the observed correlation between the two species; and (2) a long cold-collapse timescale and a methyl formate binding energy similar to or lower than water are needed to explain the observations. The relative abundance ratios obtained from the model are highly sensitive to the assumed kinetic temperature, which accounts for the high spatial variability of the aldehyde ratios observed toward Orion KL.

The HI-to-H_2 transition in the Draco cloud

In recent decades, significant attention has been dedicated to analytical and observational studies of the atomic hydrogen (̋I) to molecular hydrogen (H_2) transition in the interstellar medium. We focussed on the Draco diffuse cloud to gain deeper insights into the physical properties of the transition from ̋I to H_2. We employed the total hydrogen column density probability distribution function (N-PDF) derived from Herschel dust observations and the N_̊m HI-PDF obtained from ̋I data collected by the Effelsberg ̋I survey. The N-PDF of the Draco cloud exhibits a double-log-normal distribution, whereas the N$_ ̊m HI $-PDF follows a single log-normal distribution. The ̋I-to-H_2 transition is identified as the point where the two log-normal components of the dust N-PDF contribute equally; it occurs at A_ ̊m V ∼ 0.33 (N ∼ 6.2 cm^-2). The low-column-density segment of the dust N-PDF corresponds to the cold neutral medium, which is characterized by a temperature of around 100 K. The higher-column-density part is predominantly associated with H_2. The shape of the Draco N-PDF is qualitatively reproduced by numerical simulations. In the absence of substantial stellar feedback, such as radiation or stellar winds, turbulence exerts a significant influence on the thermal stability of the gas and can regulate the condensation of gas into denser regions and its subsequent evaporation. Recent observations of the ionized carbon line at 158 μm in Draco support this scenario. Using the KOSMA-tau photodissociation model, we estimate a gas density of n ∼ 50 cm^-3 and a temperature of ∼ 100 K at the location of the ̋I-to-H_2 transition. Both the molecular and atomic gas components are characterized by supersonic turbulence and strong mixing, suggesting that simplified steady-state chemical models are not applicable under these conditions.

Significant reflection and absorption effects in the X-ray emission of the intermediate polar IGR J17195-4100

Context. X-ray emission is emitted from shock-heated plasma in magnetic cataclysmic variables, particularly in intermediate polars, and is processed by absorption and scattering before reaching the observer. Aims. We investigate these effects in the X-ray emission of the intermediate polar IGR J17195-4100 by carrying out the X-ray spectral analysis, and examining spin modulation and hardness ratio. Methods. We present high-sensitivity broadband X-ray spectral analysis by combining NuSTAR and XMM-Newton observations in the 0.3–78.0 keV energy range. X-ray spectral analysis is performed using six composite models, including the angle-dependent reflection model (reflect), multi-temperature plasma emission models (CEVMKL, MKCFLOW), and photoionised and/or neutral partially covering absorption models (zxipcf, pcfabs) within XSPEC. We also examine the spin modulation in four energy ranges and the hardness ratio to determine the absorption and scattering effects. Results. We find that the spectrum is best modelled with a reflection amplitude (Ω) of 0.58 −0.26+0.38, an ionisation parameter, log(ξ), of 1.46−0.23+0.44 with an equivalent hydrogen column density of 3.09−0.68+2.26 × 1022 cm−2, a neutral absorber, and a multi-temperature plasma temperature of 27.14−2.13+2.0 keV. In addition, we detect effects of electron scattering in the NuSTAR band, leading to a modulation amplitude of approximately a steady 9%, which rises to 15% after 20 keV. Conclusions. We stress that these effects significantly affect the X-ray emission of intermediate polars and should be considered to obtain a good representation of the intrinsic spectrum.

NeuralPDR: neural differential equations as surrogate models for photodissociation regions

Abstract Computational astrochemical models are essential for helping us interpret and understand the observations of different astrophysical environments. In the age of high-resolution telescopes such as JWST and ALMA, the substructure of many objects can be resolved, raising the need for astrochemical modeling at these smaller scales, meaning that the simulations of these objects need to include both the physics and chemistry to accurately model the observations. The computational cost of the simulations coupling both the three-dimensional hydrodynamics and chemistry is enormous, creating an opportunity for surrogate models that can effectively substitute the chemical solver. In this work we present surrogate models that can replace the original chemical code, namely Latent Augmented Neural Ordinary Differential Equations. We train these surrogate architectures on three datasets of increasing physical complexity, with the last dataset derived directly from a three-dimensional simulation of a molecular cloud using a photodissociation region (PDR) code, 3D-PDR. We show that these surrogate models can provide speedup and reproduce the original observable column density maps of the dataset. This enables the rapid inference of the chemistry (on the GPU), allowing for the faster statistical inference of observations or increasing the resolution in hydrodynamical simulations of astrophysical environments.

Self-supervised accurate remote sensing atmospheric missing data reconstruction: a masked auto-encoder solution

ABSTRACT Remote sensing atmospheric products are crucial for monitoring and analysis air quality. However, missing data can severely affect the completeness and accuracy of datasets, limiting their validity and reliability in subsequent analyses and applications. This study introduced a framework based on masked auto-encoder structure tailored to reconstruct missing data in remote sensing atmospheric products. Leveraging a self-supervised approach, real missing pattern masks were employed to construct training datasets, enhancing the model’s ability to generalize and accurately recover missing values. Experiments on POMINO-TROPOMI N O 2 vertical column density data show that by integrating residual multi-attention in the encoder and a multi-layered spatial attention in the decoder, the model achieved an overall test R 2 of 0.85 for datasets with less than 40% missing, showing its effectiveness and generalizability. This research contributes a novel perspective to atmospheric data recovery, offering a reliable tool for enhancing the completeness and accuracy of remote sensing atmospheric products.

Investigating the Hi distribution and kinematics of ESO444-G084 and [KKS2000]23: New insights from the MHONGOOSE survey

We present the neutral atomic hydrogen ( distribution, kinematics, mass modelling, and gravitational stability of the dwarf irregular galaxies ESO444--G084 and KKS2000 23 using high spatial, spectral, and column density sensitivity data from the MeerKAT observations of nearby galactic objects: Observing Southern Emitters (MHONGOOSE) survey obtained with MeerKAT. ESO444--G084 exhibits centrally concentrated emission, while KKS2000 23 has irregularly distributed high-density pockets. The total fluxes measured down to column density thresholds of cm ) and cm ) are nearly the same, suggesting that the increase in the diameter at lower column densities is primarily due to the larger beam size, and that no significant additional emission is detected. The total masses are ((1.1 ± 0.1) ⊙ ) for ESO444--G084 and ((6.1 ± 0.3) ⊙ ) for KKS2000 23. We derived rotation curves using 3D kinematic modelling tools Python fully automated TiRiFiC (PyFAT) and tilted ring fitting code (TiRiFiC), which allow us to fully capture the gas kinematics. Both galaxies exhibit disk-like rotation, with ESO444--G084 showing a kinematic warp beyond (∼1.8) kpc. Its relatively fast-rising rotation curve suggests a more centrally concentrated dark matter distribution, whereas KKS2000 3.4,μ m = 0.20) for ESO444--G084 and (0.18) for KKS2000 gas /Σ_ crit ), linking these with recent star formation traced by hydrogen-alpha (H(α)) and far-ultraviolet (FUV) emission. ESO444--G084 supports localised star formation despite global stability, while KKS2000 23 is gravitationally unstable yet lacks strong H(α) emission, suggesting that turbulence, gas depletion, or past feedback suppresses star formation. The absence of detectable inflows or outflows implies that internal processes regulate star formation. This study highlights the interplay between morphology, kinematics, dark matter distribution, and disk stability, demonstrating how internal mechanisms shape dwarf galaxy evolution.