We present Berkeley-Illinois-Maryland Association (BIMA) millimeter interferometer observations of giant molecular clouds (GMCs) along a spiral arm in M31. The observations consist of a survey using ...the compact configuration of the interferometer and follow-up, higher resolution observations on a subset of the detections in the survey. The data are processed using an analysis algorithm designed to extract GMCs and correct their derived properties for observational biases, thereby facilitating comparison with Milky Way data. The algorithm identifies 67 GMCs, of which 19 have a sufficient signal-to-noise ratio to accurately measure their properties. The GMCs in this portion of M31 are indistinguishable from those found in the Milky Way, having a similar size-line width relationship and distribution of virial parameters, confirming the results of previous, smaller studies. The velocity gradients and angular momenta of the GMCs are comparable to the values measured in M33 and the Milky Way, and in all cases are below expected values based on the local galactic shear. The studied region of M31 has an interstellar radiation field, metallicity, Toomre Q parameter, and midplane volume density similar to those of the inner Milky Way, so the similarity of GMC populations between the two systems is not surprising.
We reanalyze the catalogs of molecular clouds in the Local Group to determine the parameters of their mass distributions in a uniform manner. The analysis uses the error‐in‐variables method of ...parameter estimation, which accounts not only for the variance of the sample when drawn from a parent distribution, but also for errors in the mass measurements. Testing the method shows that it recovers the underlying properties of cumulative mass distribution without bias while accurately reflecting uncertainties in the parameters. Clouds in the inner disk of the Milky Way follow a truncated power‐law distribution with index
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and maximum mass of
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. The distributions of cloud mass for the outer Milky Way and M33 show significantly steeper indices (
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and
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, respectively), with no evidence of a cutoff. The mass distribution of clouds in the Large Magellanic Cloud has a marginally steeper distribution than the inner disk of the Milky Way (
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) and also shows evidence of a truncation, with a maximum mass of
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. The mass distributions of molecular clouds vary dramatically across the Local Group, even after accounting for the systematic errors that arise in comparing heterogeneous data and catalogs. These differences should be accounted for in studies that aim to reproduce the molecular cloud mass distributions, or in studies that use the mass spectrum as a parameter in a model.
We present a generalization of the giant molecular cloud identification problem based on cluster analysis. The method we designed, SCIMES (Spectral Clustering for Interstellar Molecular Emission ...Segmentation) considers the dendrogram of emission in the broader framework of graph theory and utilizes spectral clustering to find discrete regions with similar emission properties. For Galactic molecular cloud structures, we show that the characteristic volume and/or integrated CO luminosity are useful criteria to define the clustering, yielding emission structures that closely reproduce 'by-eye' identification results. SCIMES performs best on well-resolved, high-resolution data, making it complementary to other available algorithms. Using ...CO(1-0) data for the Orion-Monoceros complex, we demonstrate that SCIMES provides robust results against changes of the dendrogram-construction parameters, noise realizations and degraded resolution. By comparing SCIMES with other cloud decomposition approaches, we show that our method is able to identify all canonical clouds of the Orion-Monoceros region, avoiding the overdivision within high-resolution survey data that represents a common limitation of several decomposition algorithms. The Orion-Monoceros objects exhibit hierarchies and size-line width relationships typical to the turbulent gas in molecular clouds, although 'the Scissors' region deviates from this common description. SCIMES represents a significant step forward in moving away from pixel-based cloud segmentation towards a more physical-oriented approach, where virtually all properties of the ISM can be used for the segmentation of discrete objects. (ProQuest: ... denotes formulae/symbols omitted.)
We demonstrate the utility of dendrograms at representing the essential features of the hierarchical structure of the isosurfaces for molecular line data cubes. The dendrogram of a data cube is an ...abstraction of the changing topology of the isosurfaces as a function of contour level. The ability to track hierarchical structure over a range of scales makes this analysis philosophically different from local segmentation algorithms like CLUMPFIND. Points in the dendrogram structure correspond to specific volumes in data cubes defined by their bounding isosurfaces. We further refine the technique by measuring the properties associated with each isosurface in the analysis allowing for a multiscale calculation of molecular gas properties. Using COMPLETE super( 13)CO image data from the L1448 region in Perseus and mock observations of a simulated data cube, we identify regions that have a significant contribution by self-gravity to their energetics on a range of scales. We find evidence for self-gravitation on all spatial scales in L1448, although not in all regions. In the simulated observations, nearly all of the emission is found in objects that would be self-gravitating if gravity were included in the simulation. We reconstruct the size-line-width relationship within the data cube using the dendrogram-derived properties and find it follows the standard relation: image. Finally, we show that constructing the dendrogram of CO image emission from the Orion-Monoceros region allows for the identification of giant molecular clouds in a blended molecular line data set using only a physically motivated definition (self-gravitating clouds with masses >image M sub(image)).
The sample of 566 molecular clouds identified in the CO(2–1) IRAM survey covering the disk of M 33 is explored in detail. The clouds were found using CPROPS and were subsequently catalogued in terms ...of their star-forming properties as non-star-forming (A), with embedded star formation (B), or with exposed star formation (C, e.g., presence of Hα emission). We find that the size-linewidth relation among the M 33 clouds is quite weak but, when comparing with clouds in other nearby galaxies, the linewidth scales with average metallicity. The linewidth and particularly the line brightness decrease with galactocentric distance. The large number of clouds makes it possible to calculate well-sampled cloud mass spectra and mass spectra of subsamples. As noted earlier, but considerably better defined here, the mass spectrum steepens (i.e., higher fraction of small clouds) with galactocentric distance. A new finding is that the mass spectrum of A clouds is much steeper than that of the star-forming clouds. Further dividing the sample, this difference is strong at both large and small galactocentric distances and the A vs. C difference is a stronger effect than the inner vs. outer disk difference in mass spectra. Velocity gradients are identified in the clouds using standard techniques. The gradients are weak and are dominated by prograde rotation; the effect is stronger for the high signal-to-noise clouds. A discussion of the uncertainties is presented. The angular momenta are low but compatible with at least some simulations. Finally, the cloud velocity gradients are compared with the gradient of disk rotation. The cloud and galactic gradients are similar; the cloud rotation periods are much longer than cloud lifetimes and comparable to the galactic rotation period. The rotational kinetic energy is 1–2% of the gravitational potential energy and the cloud edge velocity is well below the escape velocity, such that cloud-scale rotation probably has little influence on the evolution of molecular clouds.
Rotation of molecular clouds in M 51 Braine, J.; Hughes, A.; Rosolowsky, E. ...
Astronomy and astrophysics (Berlin),
01/2020, Letnik:
633
Journal Article
Recenzirano
Odprti dostop
The grand-design spiral galaxy M 51 was observed at 40 pc resolution in CO(1–0) by the PAWS project. A large number of molecular clouds were identified and we search for velocity gradients in two ...high signal-to-noise subsamples, containing 682 and 376 clouds. The velocity gradients are found to be systematically prograde oriented, as was previously found for the rather flocculent spiral M 33. This strongly supports the idea that the velocity gradients reflect cloud rotation, rather than more random dynamical forces, such as turbulence. Not only are the gradients prograde, but their
∂v
/
∂x
and
∂v
/
∂y
coefficients follow galactic shear in sign, although with a lower amplitude. No link is found between the orientation of the gradient and the orientation of the cloud. The values of the cloud angular momenta appear to be an extension of the values noted for galactic clouds despite the orders of magnitude difference in cloud mass. Roughly 30% of the clouds show retrograde velocity gradients. For a strictly rising rotation curve, as in M 51, gravitational contraction would be expected to yield strictly prograde rotators within an axisymmetric potential. In M 51, the fraction of retrograde rotators is found to be higher in the spiral arms than in the disk as a whole. Along the leading edge of the spiral arms, a majority of the clouds are retrograde rotators. While this work should be continued on other nearby galaxies, the M 33 and M 51 studies have shown that clouds rotate and that they rotate mostly prograde, although the amplitudes are not such that rotational energy is a significant support mechanism against gravitation. In this work, we show that retrograde rotation is linked to the presence of a spiral gravitational potential.
Star formation is a multi-scale process that requires tracing cloud formation and stellar feedback within the local ( kpc) and global galaxy environment. We present first results from two large ...observing programs on the Atacama Large Millimeter/submillimeter Array (ALMA)and the Very Large Telescope/Multi Unit Spectroscopic Explorer(VLT/MUSE), mapping cloud scales (1″ = 47 pc) in both molecular gas and star-forming tracers across 90 kpc2 of the central disk of NGC 628 to probe the physics of star formation. Systematic spatial offsets between molecular clouds and H ii regions illustrate the time evolution of star-forming regions. Using uniform sampling of both maps on 50-500 pc scales, we infer molecular gas depletion times of 1-3 Gyr, but also find that the increase of scatter in the star formation relation on small scales is consistent with gas and H ii regions being only weakly correlated at the cloud (50 pc) scale. This implies a short overlap phase for molecular clouds and H ii regions, which we test by directly matching our catalog of 1502 H ii regions and 738 GMCs. We uncover only 74 objects in the overlap phase, and we find depletion times >1 Gyr, significantly longer than previously reported for individual star-forming clouds in the Milky Way. Finally, we find no clear trends that relate variations in the depletion time observed on 500 pc scales to physical drivers (metallicity, molecular and stellar-mass surface density, molecular gas boundedness) on 50 pc scales.
Abstract
We compare the properties of clouds in simulated M33 galaxies to those observed in the real M33. We apply a friends of friends algorithm and CPROPS to identify clouds, as well as a ...pixel-by-pixel analysis. We obtain very good agreement between the number of clouds, and maximum mass of clouds. Both are lower than occurs for a Milky Way-type galaxy and thus are a function of the surface density, size, and galactic potential of M33. We reproduce the observed dependence of molecular cloud properties on radius in the simulations, and find this is due to the variation in gas surface density with radius. The cloud spectra also show good agreement between the simulations and observations, but the exact slope and shape of the spectra depend on the algorithm used to find clouds, and the range of cloud masses included when fitting the slope. Properties such as cloud angular momentum, velocity dispersions, and virial relation are also in good agreement between the simulations and observations, but do not necessarily distinguish between simulations of M33 and other galaxy simulations. Our results are not strongly dependent on the level of feedback used here (10 and 20 per cent) although they suggest that 15 per cent feedback efficiency may be optimal. Overall our results suggest that the molecular cloud properties are primarily dependent on the gas and mass surface density, and less dependent on the localized physics such as the details of stellar feedback, or the numerical code used.
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