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Register a new userImproved Measurements of Molecular Cloud Distances Based on Global Search
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The principle of the background-eliminated extinction-parallax (BEEP) method is examining the extinction difference between on- and off-cloud regions to reveal the extinction jump caused by molecular clouds, thereby revealing the distance in complex dust environments. The BEEP method requires high-quality images of molecular clouds and high-precision stellar parallaxes and extinction data, which can be provided by the Milky Way Imaging Scroll Painting (MWISP) CO survey and the Gaia DR2 catalog, as well as supplementary AV extinction data. In this work, the BEEP method is further improved (BEEP-II) to measure molecular cloud distances in a global search manner. Applying the BEEP-II method to three regions mapped by the MWISP CO survey, we collectively measured 238 distances for 234 molecular clouds. Compared with previous BEEP results, the BEEP-II method measures distances efficiently, particularly for those molecular clouds with large angular size or in complicated environments, making it suitable for distance measurements of molecular clouds in large samples.
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The fragmentation of filaments in molecular clouds has attracted a lot of attention as there seems to be a relation between the evolution of filaments and star formation. The study of the fragmentation process has been motivated by simple analytical models. However, only a few comprehensive studies have analysed the evolution of filaments using numerical simulations where the filaments form self-consistently as part of molecular clouds. We address the early evolution of pc-scale filaments that form within individual clouds. We focus on three questions: How do the line masses of filaments evolve? How and when do the filaments fragment? How does the fragmentation relate to the line masses of the filaments? We examine three simulated molecular clouds formed in kpc-scale numerical simulations performed with the FLASH code. We compare the properties of the identified filaments with the predictions of analytic filament stability models. The line masses and mass fraction enclosed in the identified filaments increase continuously after the onset of self-gravity. The first fragments appear early when the line masses lie well below the critical line mass of Ostrikers hydrostatic equilibrium solution. The average line masses of filaments identified in 3D density cubes increases far more quickly than those identified in 2D column density maps. Our results suggest that hydrostatic or dynamic compression from the surrounding cloud has a significant impact on the early dynamical evolution of filaments. A simple model of an isolated, isothermal cylinder may not provide a good approach for fragmentation analysis. Caution must be exercised in interpreting distributions of properties of filaments identified in column density maps, especially in the case of low-mass filaments. Comparing or combining results from studies that use different filament finding techniques is strongly discouraged.
We analyze hydrodynamic simulations of turbulent, star-forming molecular clouds that are post-processed with the photo-dissociation region astrochemistry code 3D-PDR. We investigate the sensitivity of 15 commonly applied turbulence statistics to post-processing assumptions, namely variations in gas temperature, abundance and external radiation field. We produce synthetic $^{12}$CO(1-0) and CI($^{3}$P$_{1}$-$^{3}$P$_{0}$) observations and examine how the variations influence the resulting emission distributions. To characterize differences between the datasets, we perform statistical measurements, identify diagnostics sensitive to our chemistry parameters, and quantify the statistic responses by using a variety of distance metrics. We find that multiple turbulent statistics are sensitive not only to the chemical complexity but also to the strength of the background radiation field. The statistics with meaningful responses include principal component analysis, spatial power spectrum and bicoherence. A few of the statistics, such as the velocity coordinate spectrum, are primarily sensitive to the type of tracer being utilized, while others, like the delta-variance, strongly respond to the background radiation field. Collectively, these findings indicate that more realistic chemistry impacts the responses of turbulent statistics and is necessary for accurate statistical comparisons between models and observed molecular clouds.
In previous contributions, we have presented an analytical model describing the evolution of molecular clouds (MCs) undergoing hierarchical gravitational contraction. The clouds evolution is characterized by an initial increase in its mass, density, and star formation rate (SFR) and efficiency (SFE) as it contracts, followed by a decrease of these quantities as newly formed massive stars begin to disrupt the cloud. The main parameter of the model is the maximum mass reached by the cloud during its evolution. Thus, specifying the instantaneous mass and some other variable completely determines the clouds evolutionary stage. We apply the model to interpret the observed scatter in SFEs of the cloud sample compiled by Lada et al. as an evolutionary effect so that, although clouds such as California and Orion A have similar masses, they are in very different evolutionary stages, causing their very different observed SFRs and SFEs. The model predicts that the California cloud will eventually reach a significantly larger total mass than the Orion A cloud. Next, we apply the model to derive estimated ages of the clouds since the time when approximately 25% of their mass had become molecular. We find ages from $sim 1.5$ to 27 Myr, with the most inactive clouds being the youngest. Further predictions of the model are that clouds with very low SFEs should have massive atomic envelopes constituting the majority of their gravitational mass, and that low-mass clouds ($M sim 10^3$-$10^4 , M_odot$) end their lives with a mini-burst of star formation, reaching SFRs $sim 300$-$500, M_odot$ Myr$^{-1}$. By this time, they have contracted to become compact ($sim 1$ pc) massive star-forming clumps, in general embedded within larger GMCs.
The distance to the Large Magellanic Cloud (LMC) represents a key local rung of the extragalactic distance ladder. Yet, the galaxys distance modulus has long been an issue of contention, in particular in view of claims that most newly determined distance moduli cluster tightly - and with a small spread - around the canonical distance modulus, (m-M)_0 = 18.50 mag. We compiled 233 separate LMC distance determinations published between 1990 and 2013. Our analysis of the individual distance moduli, as well as of their two-year means and standard deviations resulting from this largest data set of LMC distance moduli available to date, focuses specifically on Cepheid and RR Lyrae variable-star tracer populations, as well as on distance estimates based on features in the observational Hertzsprung-Russell diagram. We conclude that strong publication bias is unlikely to have been the main driver of the majority of published LMC distance moduli. However, for a given distance tracer, the body of publications leading to the tightly clustered distances is based on highly non-independent tracer samples and analysis methods, hence leading to significant correlations among the LMC distances reported in subsequent articles. Based on a careful, weighted combination, in a statistical sense, of the main stellar population tracers, we recommend that a slightly adjusted canonical distance modulus of (m-M)_0 = 18.49 +- 0.09 mag be used for all practical purposes that require a general distance scale without the need for accuracies of better than a few percent.
Distance measurements to molecular clouds are essential and important. We present directly measured distances to 169 molecular clouds in the fourth quadrant of the Milky Way. Based on the near-infrared photometry from the Two Micron All Sky Survey and the Vista Variables in the Via Lactea Survey, we select red clump stars in the overlapping directions of the individual molecular clouds and infer the bin averaged extinction values and distances to these stars. We track the extinction versus distance profiles of the sightlines toward the clouds and fit them with Gaussian dust distribution models to find the distances to the clouds. We have obtained distances to 169 molecular clouds selected from Rice et al. The clouds range in distances between 2 and 11 kpc from the Sun. The typical internal uncertainties in the distances are less than 5 per cent and the systematic uncertainty is about 7 per cent. The catalogue presented in this work is one of the largest homogeneous catalogues of distant molecular clouds with the direct measurement of distances. Based on the catalogue, we have tested different spiral arm models from the literature.
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