Molecular Cloud Populations in the Context of Their Host Galaxy Environments: A Multiwavelength Perspective

分类： 天文学 >> 天文学 提交时间： 2023-02-19

Jiayi Sun Adam K. Leroy Erik Rosolowsky Annie Hughes Eva Schinnerer Andreas Schruba Eric W. Koch Guillermo A. Blanc I-Da Chiang Brent Groves Daizhong Liu Sharon Meidt Hsi-An Pan Jerome Pety Miguel Querejeta Toshiki Saito Karin Sandstrom Amy Sardone Antonio Usero Dyas Utomo

摘要： We present a rich, multiwavelength, multiscale database built around the PHANGS-ALMA CO$\,$(2-1) survey and ancillary data. We use this database to present the distributions of molecular cloud populations and sub-galactic environments in 80 PHANGS galaxies, to characterize the relationship between population-averaged cloud properties and host galaxy properties, and to assess key timescales relevant to molecular cloud evolution and star formation. We show that PHANGS probes a wide range of kpc-scale gas, stellar, and star formation rate (SFR) surface densities, as well as orbital velocities and shear. The population-averaged cloud properties in each aperture correlate strongly with both local environmental properties and host galaxy global properties. Leveraging a variable selection analysis, we find that the kpc-scale surface densities of molecular gas and SFR tend to possess the most predictive power for the population-averaged cloud properties. Once their variations are controlled for, galaxy global properties contain little additional information, which implies that the apparent galaxy-to-galaxy variations in cloud populations are likely mediated by kpc-scale environmental conditions. We further estimate a suite of important timescales from our multiwavelength measurements. The cloud-scale free-fall time and turbulence crossing time are ${\sim}5{-}20$ Myr, comparable to previous cloud lifetime estimates. The timescales for orbital motion, shearing, and cloud-cloud collisions are longer, ${\sim}100$ Myr. The molecular gas depletion time is $1{-}3$ Gyr and shows weak to no correlations with the other timescales in our data. We publish our measurements online and expect them to have broad utility to future studies of molecular clouds and star formation.

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