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

Creators: Sun, Jiayi; Leroy, Adam K.; Rosolowsky, Erik; Hughes, Annie; Schinnerer, Eva; Schruba, Andreas; Koch, Eric W.; Blanc, Guillermo A.; Chiang, I-Da; Groves, Brent; Liu, Daizhong; Meidt, Sharon; Pan, Hsi-An; Pety, Jérôme; Querejeta, Miguel; Saito, Toshiki; Sandstrom, Karin; Sardone, Amy; Usero, Antonio; Utomo, Dyas; Williams, Thomas G.; Barnes, Ashley T.; Benincasa, Samantha M.; Bigiel, Frank; Bolatto, Alberto D.; Boquien, Médéric; Chevance, Mélanie; Dale, Daniel A.; Deger, Sinan; Emsellem, Eric; Glover, Simon C. O.; Grasha, Kathryn; Henshaw, Jonathan D.; Klessen, Ralf S.; Kreckel, Kathryn; Kruijssen, J. M. Diederik; Ostriker, Eve C.; Thilker, David A.

Abstract

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 subgalactic 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 freefall time and turbulence crossing time are ∼5–20 Myr, comparable to previous cloud lifetime estimates. The timescales for orbital motion, shearing, and cloud–cloud collisions are longer, ∼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.

Additional Information

© 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2022 March 18; revised 2022 May 23; accepted 2022 May 23; published 2022 July 11. This work was carried out as part of the PHANGS collaboration. The work of J.S. is partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Canadian Institute for Theoretical Astrophysics (CITA) National Fellowship. The work of J.S., A.K.L., and D.U. is partially supported by the National Science Foundation (NSF) under grants No. 1615105, 1615109, and 1653300. The work of J.S. and A.K.L. is partially supported by the National Aeronautics and Space Administration (NASA) under ADAP grants NNX16AF48G and NNX17AF39G. E.W.R. acknowledges the support of the NSERC, funding reference number RGPIN-2017-03987. E.W.K. acknowledges support from the Smithsonian Institution as a Submillimeter Array Fellow. G.A.B. gratefully acknowledges support by the ANID BASAL project FB210003. H.A.P. acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No. 694343) and the Ministry of Science and Technology of Taiwan under grant 110-2112-M-032-020-MY3. J.P. acknowledges support by the Programme National "Physique et Chimie du Milieu Interstellaire" (PCMI) of CNRS/INSU with INC/INP, co-funded by CEA and CNES. M.Q. acknowledges support from the Spanish grant PID2019-106027GA-C44, funded by MCIN/AEI/10.13039/501100011033. A.S. is supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-1903834. T.G.W. acknowledges funding from the ERC under the European Unions Horizon 2020 research and innovation program (grant agreement No. 694343). A.T.B. and F.B. would like to acknowledge funding from the ERC under the European Union's Horizon 2020 research and innovation program (grant agreement No. 726384/Empire). M.B. gratefully acknowledges support by the ANID BASAL project FB210003. M.C. gratefully acknowledges funding from the Deutsche Forschungsgemeinschaft (DFG) in the form of an Emmy Noether Research Group (grant No. CH2137/1-1). M.C. and J.M.D.K. gratefully acknowledge funding from the DFG in the form of an Emmy Noether Research Group (grant No. KR4801/1-1) and the DFG Sachbeihilfe (grant No. KR4801/2-1), and from the ERC under the European Union's Horizon 2020 research and innovation program via the ERC Starting Grant MUSTANG (grant agreement No. 714907). S.C.O.G. and R.S.K. acknowledge financial support from the DFG via the collaborative research center (SFB 881, Project-ID 138713538) "The Milky Way System" (subprojects A1, B1, B2, and B8). They also acknowledge funding from the Heidelberg Cluster of Excellence "STRUCTURES" in the framework of Germanys Excellence Strategy (grant EXC-2181/1, Project-ID 390900948) and from the European Research Council via the ERC Synergy Grant "ECOGAL" (grant 855130). K.G. is supported by the Australian Research Council through the Discovery Early Career Researcher Award (DECRA) Fellowship DE220100766 funded by the Australian Government. K.K. gratefully acknowledges funding from the DFG in the form of an Emmy Noether Research Group (grant No. KR4598/2-1, PI Kreckel). The work of E.C.O. is partially supported by NASA under ATP grant No. NNX17AG26G. This paper makes use of the following ALMA data, which have been processed as part of the PHANGS–ALMA CO (2-1) survey: ADS/JAO.ALMA#2012.1.00650.S, ADS/JAO.ALMA#2013.1.00803.S, ADS/JAO.ALMA#2013.1.01161.S, ADS/JAO.ALMA#2015.1.00121.S, ADS/JAO.ALMA#2015.1.00782.S, ADS/JAO.ALMA#2015.1.00925.S, ADS/JAO.ALMA#2015.1.00956.S, ADS/JAO.ALMA#2016.1.00386.S, ADS/JAO.ALMA#2017.1.00392.S, ADS/JAO.ALMA#2017.1.00766.S, ADS/JAO.ALMA#2017.1.00886.L, ADS/JAO.ALMA#2018.1.01321.S, ADS/JAO.ALMA#2018.1.01651.S, ADS/JAO.ALMA#2018.A.00062.S. ALMA is a partnership of ESO (representing its member states), NSF (USA), and NINS (Japan), together with NRC (Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. The National Radio Astronomy Observatory (NRAO) is a facility of NSF operated under cooperative agreement by Associated Universities, Inc (AUI). This work is based in part on observations made with NSF's Karl G. Jansky Very Large Array (VLA; project code: 14A-468, 14B-396, 16A-275, 17A-073, 18B-184). VLA is also operated by NRAO. This work is based in part on observations made with the Australia Telescope Compact Array (ATCA). ATCA is part of the Australia Telescope National Facility, which is funded by the Australian Government for operation as a National Facility managed by CSIRO. This work is based in part on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. This work makes use of data products from the Wide-field Infrared Survey Explorer (WISE), which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by NASA. This work is based in part on observations made with the Galaxy Evolution Explorer (GALEX). GALEX is a NASA Small Explorer, whose mission was developed in cooperation with the Centre National d'Etudes Spatiales (CNES) of France and the Korean Ministry of Science and Technology. GALEX is operated for NASA by the California Institute of Technology under NASA contract NAS5-98034. This work is based in part on data gathered with the CIS 2.5 m Irénée du Pont Telescope and the ESO/MPG 2.2 m Telescope at Las Campanas Observatory, Chile. This work has made use of the NASA/IPAC Infrared Science Archive (IRSA) and the NASA/IPAC Extragalactic Database (NED), which are funded by NASA and operated by the California Institute of Technology. Relevant data sets to this work include S4G team (2010) and Sandstrom (2019). We acknowledge the usage of the HyperLeda database 50 (Makarov et al. 2014) and the SAO/NASA Astrophysics Data System. Facilities: ALMA, VLA, ATCA, Spitzer, WISE, GALEX, Max Planck:2.2 m, Du Pont, IRSA. Software: NumPy (Harris et al. 2020), SciPy (Virtanen et al. 2020), Astropy (Astropy Collaboration et al. 2013, 2018), pandas (The pandas development team 2021), scikit-learn (Pedregosa et al. 2011), Matplotlib (Hunter 2007), APLpy (Robitaille & Bressert 2012), MegaTable (Sun 2022), adstex (https://github.com/yymao/adstex).

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