Column Density Image Research Articles

Supervised machine learning on Galactic filaments

Context. Filaments host star formation and are fundamental structures of galaxies. Their diversity, as observed in the interstellar medium, from very low-density structures to very dense hubs, and their complex life cycles make their complete detection challenging over this large diversity range. Aims. Using 2D H2 column density images obtained as part of the Herschel Hi-GAL survey of the Galactic plane (Gp), we want to detect, simultaneously and using a single model, filaments over a large range of column density and contrast over the whole Gp. In particular, we target low-contrast and low-density structures that are particularly difficult to detect with classical algorithms. Methods. The whole H2 column density image of the Gp was subdivided into individual patches of 32 × 32 pixels. Following our proof of concept study aimed at exploring the potential of supervised learning for the detection of filaments, we propose an innovative supervised learning method based on adding information by encoding the position of these patches in the Gp. To allow the segmentation of the whole Gp, we introduced a random procedure that preserves the balance within the model training and testing datasets over the Gp plane. Four architectures and six models were tested and compared using different metrics. Results. For the first time, a segmentation of the whole Gp has been obtained using supervised deep learning. A comparison of the models based on metrics and astrophysical results shows that one of the architectures (PE-UNet-Latent), where the position encoding was done in the latent space gives the best performance to detect filaments over the whole range of density and contrast observed in the Gp. A normalized map of the whole Gp was also produced and reveals the highly filamentary structure of the Gp in all density regimes. We successfully tested the generalization of our best model by applying it to the 2D 12CO COHRS molecular data obtained on a 58.°8 portion (in longitude) of the plane. Conclusions. We demonstrate the interest of position encoding to allow the detection of filaments over the wide range of density and contrast observed in the Gp. The produced maps (both normalized and segmented) offer a unique opportunity for follow-up studies of the life cycle of Galactic filaments. The promising generalization possibility tested on a molecular dataset of the Gp opens new opportunities for systematic detection of filamentary structures in the big data context available for the Gp.

An Automated Chemical Exploration of NGC 6334I at 340 au Resolution

Much of the information gleaned from observations of star-forming regions comes from the analysis of their molecular emission spectra, particularly in the radio regime. The time-consuming nature of fitting synthetic spectra to observations interactively for such line-rich sources, however, often results in such analysis being limited to data extracted from a single-dish observation or a handful of pixels from an interferometric observation. Yet, star-forming regions display a wide variety of physical conditions that are difficult, if not impossible, to accurately characterize with such a limited number of spectra. We have developed an automated fitting routine that visits every pixel in the field of view of an Atacama Large Millimeter/submillimeter Array (ALMA) data cube and determines the best-fit physical parameters, including excitation temperature and column densities, for a given list of molecules. In this proof-of-concept work, we provide an overview of the fitting routine and apply it to 0.″26, 1.1 km s−1 resolution ALMA observations of two sites of massive star formation in NGC 6334I. Parameters were found for 21 distinct molecules by generating synthetic spectra across 7.48 GHz of spectral bandwidth between 280 and 351 GHz. Spatial images of the derived parameters for each of the >8000 pixels are presented with special attention paid to the C2H4O2 isomers and their relative variations. We highlight the greater scientific utility of the column density and velocity images of individual molecules compared to traditional moment maps of single transitions.

Neutral Hydrogen (H i) 21 cm as a Probe: Investigating Spatial Variations in Interstellar Turbulent Properties

Interstellar turbulence shapes the H i distribution in the Milky Way (MW). How this affects large-scale statistical properties of H i column density across the MW remains largely unconstrained. We use the ∼13,000 deg2 GALFA-H i survey to map statistical fluctuations of H i over the ±40 km s−1 velocity range. We calculate the spatial power spectrum (SPS) of the H i column density image by running a 3° kernel and measuring the SPS slope over a range of angular scales from 16′ to 20°. Due to GALFA’s complex observing and calibration strategy, we construct detailed estimates of the noise contribution and account for GALFA beam effects on the SPS. This allows us to systematically analyze H i images that trace a wide range of interstellar environments. We find that the SPS slope varies between ∼ −2.6 at high Galactic latitudes and ∼ −3.2 close to the Galactic plane. The range of SPS slope values becomes tighter when we consider H i optical depth and line-of-sight length caused by the plane-parallel geometry of the H i disk. This relatively uniform, large-scale distribution of the SPS slope is suggestive of large-scale turbulent driving being a dominant mechanism for shaping H i structures in the MW and/or the stellar feedback turbulence being efficiently dissipated within dense molecular clouds. Only at latitudes above 60° do we find evidence for the H i SPS slope being consistently more shallow. Those directions are largely within the Local Bubble, suggesting that the recent history of this cavity, shaped by multiple supernova explosions, has modified the turbulent state of H i and/or fractions of H i phases.

Supervised machine learning on Galactic filaments

Context. Filaments are ubiquitous in the Galaxy, and they host star formation. Detecting them in a reliable way is therefore key towards our understanding of the star formation process. Aims. We explore whether supervised machine learning can identify filamentary structures on the whole Galactic plane. Methods. We used two versions of UNet-based networks for image segmentation. We used H2 column density images of the Galactic plane obtained with Herschel Hi-GAL data as input data. We trained the UNet-based networks with skeletons (spine plus branches) of filaments that were extracted from these images, together with background and missing data masks that we produced. We tested eight training scenarios to determine the best scenario for our astrophysical purpose of classifying pixels as filaments. Results. The training of the UNets allows us to create a new image of the Galactic plane by segmentation in which pixels belonging to filamentary structures are identified. With this new method, we classify more pixels (more by a factor of 2 to 7, depending on the classification threshold used) as belonging to filaments than the spine plus branches structures we used as input. New structures are revealed, which are mainly low-contrast filaments that were not detected before. We use standard metrics to evaluate the performances of the different training scenarios. This allows us to demonstrate the robustness of the method and to determine an optimal threshold value that maximizes the recovery of the input labelled pixel classification. Conclusions. This proof-of-concept study shows that supervised machine learning can reveal filamentary structures that are present throughout the Galactic plane. The detection of these structures, including low-density and low-contrast structures that have never been seen before, offers important perspectives for the study of these filaments.

Mass segregation and sequential star formation in NGC 2264 revealed by Herschel

Context. The mass segregation of stellar clusters could be primordial rather than dynamical. Despite the abundance of studies of mass segregation for stellar clusters, those for stellar progenitors are still scarce, so the question concerning the origin and evolution of mass segregation is still open. Aims. Our goal is to characterize the structure of the NGC 2264 molecular cloud and compare the populations of clumps and young stellar objects (YSOs) in this region whose rich YSO population has shown evidence of sequential star formation. Methods. We separated the Herschel column density map of NGC 2264 into three subregions and compared their cloud power spectra using a multiscale segmentation technique. We extracted compact cloud fragments from the column density image, measured their basic properties, and studied their spatial and mass distributions. Results. In the whole NGC 2264 cloud, we identified a population of 256 clumps with typical sizes of ~0.1 pc and masses ranging from 0.08 M⊙ to 53 M⊙. Although clumps have been detected all over the cloud, most of the massive, bound clumps are concentrated in the central subregion of NGC 2264. The local surface density and the mass segregation ratio indicate a strong degree of mass segregation for the 15 most massive clumps, with a median Σ6 three times that of the whole clumps population and ΛMSR ≃ 8. We show that this cluster of massive clumps is forming within a high-density cloud ridge, which is formed and probably still fed by the high concentration of gas observed on larger scales in the central subregion. The time sequence obtained from the combined study of the clump and YSO populations in NGC 2264 suggests that the star formation started in the northern subregion, that it is now actively developing at the center, and will soon start in the southern subregion. Conclusions. Taken together, the cloud structure and the clump and YSO populations in NGC 2264 argue for a dynamical scenario of star formation. The cloud could first undergo global collapse, driving most clumps to centrally concentrated ridges. After their main accretion phase, some YSOs, and probably the most massive, would stay clustered while others would be dispersed from their birth sites. We propose that the mass segregation observed in some star clusters is inherited from that of clumps, originating from the mass assembly phase of molecular clouds.

Multi-phase Turbulence Density Power Spectra in the Perseus Molecular Cloud

Abstract We derive two-dimensional spatial power spectra of four distinct interstellar medium tracers, H i, 12CO(J = 1–0), 13CO(J = 1–0), and dust, in the Perseus molecular cloud, covering linear scales ranging from ∼0.1 pc to ∼90 pc. Among the four tracers, we find the steepest slopes of −3.23 ± 0.05 and −3.22 ± 0.05 for the uncorrected and opacity-corrected H i column density images. This result suggests that the H i in and around Perseus traces a non-gravitating, transonic medium on average, with a negligible effect from opacity. On the other hand, we measure the shallowest slope of −2.72 ± 0.12 for the 2MASS dust extinction data and interpret this as the signature of a self-gravitating, supersonic medium. Possible variations in the dust-to-gas ratio likely do not alter our conclusion. Finally, we derive slopes of −3.08 ± 0.08 and −2.88 ± 0.07 for the 12CO(1–0) and 13CO(1–0) integrated intensity images. Based on theoretical predictions for an optically thick medium, we interpret these slopes of roughly −3 as implying that both CO lines are susceptible to the opacity effect. While simple tests for the impact of CO formation and depletion indicate that the measured slopes of 12CO(1–0) and 13CO(1–0) are not likely affected by these chemical effects, our results generally suggest that chemically more complex and/or fully optically thick media may not be a reliable observational tracer for characterizing turbulence.

Plume propagation direction determination with SO<sub>2</sub> cameras

Abstract. SO2 cameras are becoming an established tool for measuring sulfur dioxide (SO2) fluxes in volcanic plumes with good precision and high temporal resolution. The primary result of SO2 camera measurements are time series of two-dimensional SO2 column density distributions (i.e. SO2 column density images). However, it is frequently overlooked that, in order to determine the correct SO2 fluxes, not only the SO2 column density, but also the distance between the camera and the volcanic plume, has to be precisely known. This is because cameras only measure angular extents of objects while flux measurements require knowledge of the spatial plume extent. The distance to the plume may vary within the image array (i.e. the field of view of the SO2 camera) since the plume propagation direction (i.e. the wind direction) might not be parallel to the image plane of the SO2 camera. If the wind direction and thus the camera–plume distance are not well known, this error propagates into the determined SO2 fluxes and can cause errors exceeding 50 %. This is a source of error which is independent of the frequently quoted (approximate) compensation of apparently higher SO2 column densities and apparently lower plume propagation velocities at non-perpendicular plume observation angles.Here, we propose a new method to estimate the propagation direction of the volcanic plume directly from SO2 camera image time series by analysing apparent flux gradients along the image plane. From the plume propagation direction and the known location of the SO2 source (i.e. volcanic vent) and camera position, the camera–plume distance can be determined. Besides being able to determine the plume propagation direction and thus the wind direction in the plume region directly from SO2 camera images, we additionally found that it is possible to detect changes of the propagation direction at a time resolution of the order of minutes. In addition to theoretical studies we applied our method to SO2 flux measurements at Mt Etna and demonstrate that we obtain considerably more precise (up to a factor of 2 error reduction) SO2 fluxes. We conclude that studies on SO2 flux variability become more reliable by excluding the possible influences of propagation direction variations.

From forced collapse to H ii region expansion in Mon R2: Envelope density structure and age determination withHerschel

The surroundings of HII regions can have a profound influence on their development, morphology, and evolution. This paper explores the effect of the environment on H II regions in the MonR2 molecular cloud. We aim to investigate the density structure of envelopes surrounding HII regions and to determine their collapse and ionisation expansion ages. The Mon R2 molecular cloud is an ideal target since it hosts an H II region association. Column density and temperature images derived from Herschel data were used together to model the structure of HII bubbles and their surrounding envelopes. The resulting observational constraints were used to follow the development of the Mon R2 ionised regions with analytical calculations and numerical simulations. The four hot bubbles associated with H II regions are surrounded by dense, cold, and neutral gas envelopes. The radial density profiles are reminiscent of those of low-mass protostellar envelopes. The inner parts of envelopes of all four HII regions could be free-falling because they display shallow density profiles. As for their outer parts, the two compact HII regions show a density profile, which is typical of the equilibrium structure of an isothermal sphere. In contrast, the central UCHii region shows a steeper outer profile, that could be interpreted as material being forced to collapse. The size of the heated bubbles, the spectral type of the irradiating stars, and the mean initial neutral gas density are used to estimate the ionisation expansion time, texp, 0.1Myr,for the dense UCHII and compact HII regions and 0.35 Myr for the extended HII region. The envelope transition radii between the shallow and steeper density profiles are used to estimate the time elapsed since the formation of the first proto stellar embryo, Tinf : 1Myr, for the ultra-compact, 1.5 / 3Myr for the compact, and greater than 6Myr for the extended HII regions.

COLD AND WARM ATOMIC GAS AROUND THE PERSEUS MOLECULAR CLOUD. II. THE IMPACT OF HIGH OPTICAL DEPTH ON THE HI COLUMN DENSITY DISTRIBUTION AND ITS IMPLICATION FOR THE HI-TO-H2TRANSITION

We investigate the impact of high optical depth on the HI saturation observed in the Perseus molecular cloud by using Arecibo HI emission and absorption measurements toward 26 radio continuum sources. The spin temperature and optical depth of individual HI components are derived along each line-of-sight, enabling us to estimate the correction for high optical depth. We examine two different methods for the correction, Gaussian decomposition and isothermal methods, and find that they are consistent (maximum correction factor ~ 1.2) likely due to the relatively low optical depth and insignificant contribution from the diffuse radio continuum emission for Perseus. We apply the correction to the optically thin HI column density on a pixel-by-pixel basis, and find that the total HI mass increases by ~10%. Using the corrected HI column density image and far-infrared data from the IRIS Survey, we then derive the H2 column density on ~0.4 pc scales. For five dark and star-forming sub-regions, the HI surface density is uniform with Sigma_HI ~ 7-9 solar mass/pc2, in agreement with the minimum HI surface density required for shielding H2 against photodissociation. As a result, Sigma_H2/Sigma_HI and Sigma_HI+Sigma_H2 show a tight relation. Our results are consistent with predictions for H2 formation in steady state and chemical equilibrium, and suggest that H2 formation is mainly responsible for the Sigma_HI saturation in Perseus. We also compare the optically thick HI with the observed "CO-dark" gas, and find that the optically thick HI only accounts for ~20% of the "CO-dark" gas in Perseus.

The W43-MM1 mini-starburst ridge, a test for star formation efficiency models

Context: Star formation efficiency (SFE) theories are currently based on statistical distributions of turbulent cloud structures and a simple model of star formation from cores. They remain poorly tested, especially at the highest densities. Aims: We investigate the effects of gas density on the SFE through measurements of the core formation efficiency (CFE). With a total mass of $\sim2\times10^4$ M$_\odot$, the W43-MM1 ridge is one of the most convincing candidate precursor of starburst clusters and thus one of the best place to investigate star formation. Methods: We used high-angular resolution maps obtained at 3 mm and 1 mm within W43-MM1 with the IRAM Plateau de Bure Interferometer to reveal a cluster of 11 massive dense cores (MDCs), and, one of the most massive protostellar cores known. An Herschel column density image provided the mass distribution of the cloud gas. We then measured the 'instantaneous' CFE and estimated the SFE and the star formation rate (SFR) within subregions of the W43-MM1 ridge. Results: The high SFE found in the ridge ($\sim$6% enclosed in $\sim$8 pc$^3$) confirms its ability to form a starburst cluster. There is however a clear lack of dense cores in the northern part of the ridge, which may be currently assembling. The CFE and the SFE are observed to increase with volume gas density while the SFR steeply decreases with the virial parameter, $\alpha_{vir}$. Statistical models of the SFR may well describe the outskirts of the W43-MM1 ridge but struggle to reproduce its inner part, which corresponds to measurements at low $\alpha_{vir}$. It may be that ridges do not follow the log-normal density distribution, Larson relations, and stationary conditions forced in the statistical SFR models.

LOW-VELOCITY SHOCKS TRACED BY EXTENDED SiO EMISSION ALONG THE W43 RIDGES: WITNESSING THE FORMATION OF YOUNG MASSIVE CLUSTERS

The formation of high-mass stars is tightly linked to that of their parental clouds. We here focus on the high-density parts of W43, a molecular cloud undergoing an efficient event of formation. The cloud structure is studied with a column density image derived from Herschel continuum maps obtained at 70, 160, 250, 350, and 500 micron. We identify two high-column density filamentary clouds, quoted as the W43-MM1 and W43-MM2 ridges, which both account for 1.5x10^4 Msun gas mass above 10^23 cm-2 and within areas of 5 and 14pc^2, respectively. We used the N_2H^+ 1--0 line to confirm that the W43-MM1 and W43-MM2 ridges are structures coherent in velocity and gravitationally bound, despite their large velocity dispersion and ~5 kms line widths. The most intriguing result of the W43 large program is the bright wide-spread SiO 2--1 emission: 1--11 K kms$ stretching an area of ~28 pc^2. Concentrated toward the W43-MM1 and W43-MM2 ridges and their immediate surroundings, it leads to a total luminosity of L_SiO 2-1 ~4 10^4 K kms kpc^2pc^2. We measured a steep relation between the luminosity and velocity extent of the SiO~2--1 lines and propose to use it to distinguish the low-velocity shocks observed here from the more classical high-velocity ones associated with outflows of high-mass young stellar objects. We used state-of-the-art shock models to demonstrate that low-velocity (<10 kms^-1) shocks with a small amount (10%) of Si atoms initially in gas phase or in grain mantles can explain the observed SiO column density in W43. The spatial and velocity overlaps between the ridges high-density gas (n_H2>10^4-10^5 cm^-3) and the shocked SiO gas suggests that ridges could be forming via colliding flows driven by gravity and accompanied by low-velocity shocks. This mechanism may be the initial conditions for the formation of young massive clusters in these ridges.

A HIGH-RESOLUTION STUDY OF THE H I-H2TRANSITION ACROSS THE PERSEUS MOLECULAR CLOUD

To investigate the fundamental principles of H2 formation in a giant molecular cloud (GMC), we derive the HI and H2 surface density (Sigma_HI and Sigma_H2) images of the Perseus molecular cloud on sub-pc scales (~0.4 pc). We use the far-infrared data from the Improved Reprocessing of the IRAS Survey and the V-band extinction image provided by the COMPLETE Survey to estimate the dust column density image of Perseus. In combination with the HI data from the Galactic Arecibo L-band Feed Array HI Survey and an estimate of the local dust-to-gas ratio, we then derive the Sigma_H2 distribution across Perseus. We find a relatively uniform Sigma_HI ~ 6-8 Msun pc^-2 for both dark and star-forming regions, suggesting a minimum HI surface density required to shield H2 against photodissociation. As a result, a remarkably tight and consistent relation is found between Sigma_H2/Sigma_HI and Sigma_HI+Sigma_H2. The transition between the HI- and H2-dominated regions occurs at N(HI)+2N(H2) ~ (8-14) x 10^20 cm^-2. Our findings are consistent with predictions for H2 formation in equilibrium, suggesting that turbulence may not be of primary importance for H2 formation. However, the importance of a warm neutral medium for H2 shielding, an internal radiation field, and the timescale of H2 formation still remain as open questions. We also compare H2 and CO distributions and estimate the fraction of "CO-dark" gas, f_DG ~ 0.3. While significant spatial variations of f_DG are found, we do not find a clear correlation with the mean V-band extinction.

Quantified H i morphology - III. Merger visibility times from H i in galaxy simulations

Major mergers of disk galaxies are thought to be a substantial driver in galaxy evolution. To trace the fraction and the rate galaxies are in mergers over cosmic times, several observational techniques, including morphological selection criteria, have been developed over the last decade. We apply this morphological selection of mergers to 21 cm radio emission line (HI) column density images of spiral galaxies in nearby surveys. In this paper, we investigate how long a 1:1 merger is visible in HI from N-body simulations. We evaluate the merger visibility times for selection criteria based on four parameters: Concentration, Asymmetry, M20, and the Gini parameter of second order moment of the flux distribution (GM). Of three selection criteria used in the literature, one based on Concentration and M20 works well for the HI perspective with a merger time scale of 0.4 Gyr. Of the three selection criteria defined in our previous paper, the GM performs well and cleanly selects mergers for 0.69 Gyr. The other two criteria (A-M20 and C-M20), select isolated disks as well, but perform best for face-on, gas-rich disks (T(merger) ~ 1 Gyr). The different visibility scales can be combined with the selected fractions of galaxies in any large HI survey to obtain merger rates in the nearby Universe. All-sky surveys such as WALLABY with ASKAP and the Medium Deep Survey with the APETIF instrument on Westerbork are set to revolutionize our perspective on neutral hydrogen and will provide an accurate measure of the merger fraction and rate of the present epoch.

CHARACTERIZING MAGNETOHYDRODYNAMIC TURBULENCE IN THE SMALL MAGELLANIC CLOUD

We investigate the nature and spatial variations of turbulence in the Small Magellanic Cloud (SMC) by applying several statistical methods on the neutral hydrogen (HI) column density image of the SMC and a database of isothermal numerical simulations. By using the 3rd and 4th statistical moments we derive the spatial distribution of the sonic Mach number (M_s) across the SMC. We find that about 90% of the HI in the SMC is subsonic or transonic. However, edges of the SMC `bar' have M_s=4 and may be tracing shearing or turbulent flows. Using numerical simulations we also investigate how the slope of the spatial power spectrum depends on both sonic and Alfven Mach numbers. This allows us to gauge the Alfven Mach number of the SMC and conclude that its gas pressure dominates over the magnetic pressure. The super-Alfvenic nature of the HI gas in the SMC is also highlighted by the bispectrum, a three-point correlation function which characterizes the level of non-Gaussianity in wave modes. We find that the bispectrum of the SMC HI column density displays similar large-scale correlations as numerical simulations, however it has localized enhancements of correlations. In addition, we find a break in correlations at a scale of 160 pc. This may be caused by numerous expanding shells of a similar size.

A New Comprehensive Catalogue of Infrared Dark Clouds

AbstractTo better characterise infrared dark clouds (IRDCs), and the star formation within them, a comprehensive catalogue of IRDCs has been constructed from the Spitzer GLIMPSE and MIPSGAL archival data. Mosaicing the individual survey blocks together, we have used a new extraction method to identify dark clouds up to 30′ in size, and produce a column density image of each cloud. In total the catalogue contains over 11,000 clouds, defined as connected regions with 8 micron optical depth &gt; 0.35 (corresponding to column densities &lt; 1022 cm−2). The extraction algorithm also identifies sub-structures (fragments) within each cloud. These Spitzer dark clouds (SDCs) range in mass from 10M⊙ to 104M⊙. About 80% of the SDCs were previously unidentified. Only ~ 30% of the SDCs are associated with 24μm point-like sources, leaving the majority of these clouds with no apparent sign of star formation activity. This new catalogue provides an important new resource for future studies of the initial conditions of star formation in the Galaxy.

The Complex Neutral Gas Dynamics of the Dwarf Starburst Galaxy NGC 625

We present new multiconfiguration H I aperture synthesis imaging of the nearby dwarf starburst galaxy NGC 625 obtained with the Australia Telescope Compact Array. Total H I column density images show gas well aligned with the optical major axis and low column density H I extending to greater than 6 optical scale lengths. The H I velocity field, on the other hand, is highly disturbed, with neutral gas at nearly all detected velocities within the central region. After considering various interpretations, we find that a blowout scenario most accurately describes the data. Since at our resolution we do not detect any large evacuated holes in the H I disk, we interpret this blowout to be the result of the extended (both spatially and temporally) star formation event that NGC 625 has undergone in the last 100 Myr. This is one of the clearest examples of H I outflow detected in a dwarf galaxy. We find no obvious external trigger for this extended star formation event. We detect strong radio continuum emission from the largest H II regions; comparing to our Hubble Space Telescope and ground-based Hα fluxes suggests either appreciable amounts of extinction toward the star formation regions or the contribution of nonthermal sources to the radio continuum luminosity.

Multifractal Scaling, Geometrical Diversity, and Hierarchical Structure in the Cool Interstellar Medium

Multifractal scaling (MFS) refers to structures that can be described as a collection of interwoven fractal subsets that exhibit power-law spatial-scaling behavior with a range of scaling exponents (concentration, or singularity strengths) and dimensions. The existence of MFS implies an underlying multiplicative (or hierarchical or cascade) process. Panoramic column density images of several nearby star-forming cloud complexes, constructed from IRAS data, are shown to exhibit such multifractal scaling, which we interpret as indirect but quantitative evidence for a nested hierarchical structure. The relation between the dimensions of the subsets and their concentration strengths (the multifractal spectrum) appears to satisfactorily order the observed regions in terms of the mixture of geometries present, from strong pointlike concentrations, to linelike filaments or fronts, to space-filling, diffuse structures. This multifractal spectrum is a global property of the regions studied and does not rely on any operational definition of clouds. The range of forms of the multifractal spectrum among the regions studied implies that the column density structures do not form a universality class, in contrast to indications for velocity and passive scalar fields in incompressible turbulence, providing another indication that the physics of highly compressible interstellar gas dynamics differs fundamentally from incompressible turbulence. There is no correlation between the geometrical properties of the regions studied and their level of internal star formation activity, a result that is also apparent from visual inspection. We discuss the viability of the multifractal spectrum as a measure of the structural complexity of the regions studied and emphasize the problematic dependence of all structural descriptors on the subjective preselection of the region to be described. A comparison of IRAS 100 μm column density (not intensity) images with 13CO, visual extinction, and C18O data suggests that structural details are captured by IRAS up to at least 30 mag of visual extinction, except in the vicinity of embedded stars, and that a lower column density connective structure not seen by other methods is revealed.

Cool dust and gas in the Small Magellanic Cloud

We present high-angular-resolution, far-infrared images of the Small Magellanic Cloud (SMC). The images were reconstructed from data obtained with the Infrared Astronomical Satellite (IRAS), using the Pyramid Maximum Entropy algorithm. The angular resolutions of the images are 1 arcmin at 12, 25 and 60 mu m, and 1.7 arcmin at 100 mu m, which provides an excellent complement to the recent neutral hydrogen (H I) survey from the Australia Telescope Compact Array, which has a resolution of 1.6 arcmin. We use the 60- and 100-mu m data, together with a standard dust model, to derive a temperature map and a dust column density distribution. Dust temperatures range from 23 to 45 K, which is, on average, warmer than for the Galaxy, although there is a deficit of warm, very small dust grains in the SMC. The total amount of cool dust in the SMC is 1.8(-0.2)(+1.3) x 10(4) M.. There is a significant variation of the observed dust-to-gas ratio across the SMC. This may be caused by corresponding variations in metallicity, but this explanation is not supported by the limited available data in the literature. Alternatively, there may be a large amount of molecular hydrogen (H(2)) in the SMC, similar to 8 x 10(8) M., and/or a large amount (similar to 10(6) M.) of cold dust (less than or equal to 15 K) not seen by IRAS or COBE/DIRBE. The average dust-to-atomic gas ratio is, by mass, 8.2 x 10(-5), which is a factor of similar to 30 below the Galactic value. The spatial power spectrum of the dust column density image can be approximated by P(d)(k) proportional to k(-3.1), which shows that, as with the H I power spectrum, there is no preferred scale size for dust clouds. A spatial coherence analysis shows that, over a wide range of spatial scales (greater than or similar to 50 pc), H I and dust are well correlated (> 60 per cent).

Recognition and characterization of hierarchical interstellar structure. II - Structure tree statistics

A new method of image analysis is described, in which images partitioned into 'clouds' are represented by simplified skeleton images, called structure trees, that preserve the spatial relations of the component clouds while disregarding information concerning their sizes and shapes. The method can be used to discriminate between images of projected hierarchical (multiply nested) and random three-dimensional simulated collections of clouds constructed on the basis of observed interstellar properties, and even intermediate systems formed by combining random and hierarchical simulations. For a given structure type, the method can distinguish between different subclasses of models with different parameters and reliably estimate their hierarchical parameters: average number of children per parent, scale reduction factor per level of hierarchy, density contrast, and number of resolved levels. An application to a column density image of the Taurus complex constructed from IRAS data is given. Moderately strong evidence for a hierarchical structural component is found, and parameters of the hierarchy, as well as the average volume filling factor and mass efficiency of fragmentation per level of hierarchy, are estimated. The existence of nested structure contradicts models in which large molecular clouds are supposed to fragment, in a single stage, into roughly stellar-mass cores.

Magnetohydrodynamic Turbulence at High-Latitude Regions of the Milky Way

We performed statistical analysis on the high-latitude molecular cloud MBM16 with data collected from the Galactic Arecibo L-Band Feed Array HI (GALFA-HI) Survey. We developed a code to convolve a circular kernel across a spatial column density image to create maps of the 3rd and 4th statistical moments. With these higher-order moment maps, we utilized a relationship derived purely from the theoretical MHD simulations of Burkhart et al. (2010) to directly estimate the sonic Mach number (Ms). We then looked at an estimate for the slope of the spatial power of our region to check our range of calculated Mach numbers and verify the reliability of our results. We found that the translucent, non-star forming molecular cloud, MBM16, can be considered largely subsonic to transonic, which is consistent with the conception of stars being dominant drivers of interstellar turbulence.Â