ترغب بنشر مسار تعليمي؟ اضغط هنا

Giant Molecular Cloud Catalogues for PHANGS-ALMA: Methods and Initial Results

315   0   0.0 ( 0 )
 نشر من قبل Erik Rosolowsky
 تاريخ النشر 2021
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We present improved methods for segmenting CO emission from galaxies into individual molecular clouds, providing an update to the CPROPS algorithms presented by Rosolowsky & Leroy (2006; arXiv:astro-ph/0601706 ). The new code enables both homogenization of the noise and spatial resolution among data, which allows for rigorous comparative analysis. The code also models the completeness of the data via false source injection and includes an updated segmentation approach to better deal with blended emission. These improved algorithms are implemented in a publicly available python package, PYCPROPS. We apply these methods to ten of the nearest galaxies in the PHANGS-ALMA survey, cataloguing CO emission at a common 90 pc resolution and a matched noise level. We measure the properties of 4986 individual clouds identified in these targets. We investigate the scaling relations among cloud properties and the cloud mass distributions in each galaxy. The physical properties of clouds vary among galaxies, both as a function of galactocentric radius and as a function of dynamical environment. Overall, the clouds in our target galaxies are well-described by approximate energy equipartition, although clouds in stellar bars and galaxy centres show elevated line widths and virial parameters. The mass distribution of clouds in spiral arms has a typical mass scale that is 2.5x larger than interarm clouds and spiral arms clouds show slightly lower median virial parameters compared to interarm clouds (1.2 versus 1.4).


قيم البحث

اقرأ أيضاً

We report the first evidence for high-mass star formation triggered by collisions of molecular clouds in M33. Using the Atacama Large Millimeter/submillimeter Array, we spatially resolved filamentary structures of giant molecular cloud 37 in M33 usin g $^{12}$CO($J$ = 2-1), $^{13}$CO($J$ = 2-1), and C$^{18}$O($J$ = 2-1) line emission at a spatial resolution of $sim$2 pc. There are two individual molecular clouds with a systematic velocity difference of $sim$6 km s$^{-1}$. Three continuum sources representing up to $sim$10 high-mass stars with the spectral types of B0V-O7.5V are embedded within the densest parts of molecular clouds bright in the C$^{18}$O($J$ = 2-1) line emission. The two molecular clouds show a complementary spatial distribution with a spatial displacement of $sim$6.2 pc, and show a V-shaped structure in the position-velocity diagram. These observational features traced by CO and its isotopes are consistent with those in high-mass star-forming regions created by cloud-cloud collisions in the Galactic and Magellanic Cloud HII regions. Our new finding in M33 indicates that the cloud-cloud collision is a promising process to trigger high-mass star formation in the Local Group.
We describe the processing of the PHANGS-ALMA survey and present the PHANGS-ALMA pipeline, a public software package that processes calibrated interferometric and total power data into science-ready data products. PHANGS-ALMA is a large, high-resolut ion survey of CO J=2-1 emission from nearby galaxies. The observations combine ALMAs main 12-m array, the 7-m array, and total power observations and use mosaics of dozens to hundreds of individual pointings. We describe the processing of the u-v data, imaging and deconvolution, linear mosaicking, combining interferometer and total power data, noise estimation, masking, data product creation, and quality assurance. Our pipeline has a general design and can also be applied to VLA and ALMA observations of other spectral lines and continuum emission. We highlight our recipe for deconvolution of complex spectral line observations, which combines multiscale clean, single scale clean, and automatic mask generation in a way that appears robust and effective. We also emphasize our two-track approach to masking and data product creation. We construct one set of broadly masked data products, which have high completeness but significant contamination by noise, and another set of strictly masked data products, which have high confidence but exclude faint, low signal-to-noise emission. Our quality assurance tests, supported by simulations, demonstrate that 12-m+7-m deconvolved data recover a total flux that is significantly closer to the total power flux than the 7-m deconvolved data alone. In the appendices, we measure the stability of the ALMA total power calibration in PHANGS--ALMA and test the performance of popular short-spacing correction algorithms.
We present high-resolution (sub-parsec) observations of a giant molecular cloud in the nearest star-forming galaxy, the Large Magellanic Cloud. ALMA Band 6 observations trace the bulk of the molecular gas in $^{12}$CO(2-1) and high column density reg ions in $^{13}$CO(2-1). Our target is a quiescent cloud (PGCC G282.98-32.40, which we refer to as the Planck cold cloud or PCC) in the southern outskirts of the galaxy where star-formation activity is very low and largely confined to one location. We decompose the cloud into structures using a dendrogram and apply an identical analysis to matched-resolution cubes of the 30 Doradus molecular cloud (located near intense star formation) for comparison. Structures in the PCC exhibit roughly 10 times lower surface density and 5 times lower velocity dispersion than comparably sized structures in 30 Dor, underscoring the non-universality of molecular cloud properties. In both clouds, structures with relatively higher surface density lie closer to simple virial equilibrium, whereas lower surface density structures tend to exhibit super-virial line widths. In the PCC, relatively high line widths are found in the vicinity of an infrared source whose properties are consistent with a luminous young stellar object. More generally, we find that the smallest resolved structures (leaves) of the dendrogram span close to the full range of line widths observed across all scales. As a result, while the bulk of the kinetic energy is found on the largest scales, the small-scale energetics tend to be dominated by only a few structures, leading to substantial scatter in observed size-linewidth relationships.
We present an innovative and widely applicable approach for the detection and classification of stellar clusters, developed for the PHANGS-HST Treasury Program, an $NUV$-to-$I$ band imaging campaign of 38 spiral galaxies. Our pipeline first generates a unified master source list for stars and candidate clusters, to enable a self-consistent inventory of all star formation products. To distinguish cluster candidates from stars, we introduce the Multiple Concentration Index (MCI) parameter, and measure inner and outer MCIs to probe morphology in more detail than with a single, standard concentration index (CI). We improve upon cluster candidate selection, jointly basing our criteria on expectations for MCI derived from synthetic cluster populations and published cluster catalogues, yielding model and empirical selection regions (respectively). Selection purity (confirmed clusters versus candidates, assessed via human-based classification) is high (up to 70%) for moderately luminous sources in the empirical selection region, and somewhat lower overall (outside the region or fainter). The number of candidates rises steeply with decreasing luminosity, but pipeline-integrated Machine Learning (ML) classification prevents this from being problematic. We quantify the performance of our PHANGS-HST methods in comparison to LEGUS for a sample of four galaxies in common to both surveys, finding overall agreement with 50-75% of human verified star clusters appearing in both catalogues, but also subtle differences attributable to specific choices adopted by each project. The PHANGS-HST ML-classified Class 1 or 2 catalogues reach $sim1$ magnitude fainter, $sim2times$ lower stellar mass, and are $2{-}5times$ larger in number, than attained in the human classified samples.
Tidal dwarf galaxies (TDGs) are gravitationally bound condensations of gas and stars formed during galaxy interactions. Here we present multi-configuration ALMA observations of J1023+1952, a TDG in the interacting system Arp 94, where we resolve CO(2 -1) emission down to giant molecular clouds (GMCs) at 0.64 ~ 45pc resolution. We find a remarkably high fraction of extended molecular emission (~80-90%), which is filtered out by the interferometer and likely traces diffuse gas. We detect 111 GMCs that give a similar mass spectrum as those in the Milky Way and other nearby galaxies (a truncated power law with slope of -1.76+/-0.13). We also study Larsons laws over the available dynamic range of GMC properties (~2 dex in mass and ~1 dex in size): GMCs follow the size-mass relation of the Milky Way, but their velocity dispersion is higher such that the size-linewidth and virial relations appear super-linear, deviating from the canonical values. The global molecular-to-atomic gas ratio is very high (~1) while the CO(2-1)/CO(1-0) ratio is quite low (~0.5), and both quantities vary from north to south. Star formation is predominantly taking place in the south of the TDG, where we observe projected offsets between GMCs and young stellar clusters ranging from ~50pc to ~200pc; the largest offsets correspond to the oldest knots, as seen in other galaxies. In the quiescent north, we find more molecular clouds and a higher molecular-to-atomic gas ratio (~1.5); atomic and diffuse molecular gas also have a higher velocity dispersion there. Overall, the organisation of the molecular ISM in this TDG is quite different from other types of galaxies on large scales, but the properties of GMCs seem fairly similar, pointing to near universality of the star-formation process on small scales.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا