分类： 天文学 >> 天文学 提交时间： 2023-02-19
Jiayi Sun
Adam K. Leroy
Eve C. Ostriker
Sharon Meidt
Erik Rosolowsky
Eva Schinnerer
Christine D. Wilson
Dyas Utomo
Francesco Belfiore
Guillermo A. Blanc
Eric Emsellem
Christopher Faesi
Brent Groves
Annie Hughes
Eric W. Koch
Kathryn Kreckel
Daizhong Liu
Hsi-An Pan
Jerome Pety
Miguel Querejeta
摘要： We measure empirical relationships between the local star formation rate (SFR) and properties of the star-forming molecular gas on 1.5 kpc scales across 80 nearby galaxies. These relationships, commonly referred to as "star formation laws," aim at predicting the local SFR surface density from various combinations of molecular gas surface density, galactic orbital time, molecular cloud free-fall time, and the interstellar medium dynamical equilibrium pressure. Leveraging a multiwavelength database built for the PHANGS survey, we measure these quantities consistently across all galaxies and quantify systematic uncertainties stemming from choices of SFR calibrations and the CO-to-H$_2$ conversion factors. The star formation laws we examine show 0.3-0.4 dex of intrinsic scatter, among which the molecular Kennicutt-Schmidt relation shows a $\sim$10% larger scatter than the other three. The slope of this relation ranges $\beta\approx0.9{-}1.2$, implying that the molecular gas depletion time remains roughly constant across the environments probed in our sample. The other relations have shallower slopes ($\beta\approx0.6{-}1.0$), suggesting that the star formation efficiency (SFE) per orbital time, the SFE per free-fall time, and the pressure-to-SFR surface density ratio (i.e., the feedback yield) may vary systematically with local molecular gas and SFR surface densities. Last but not least, the shapes of the star formation laws depend sensitively on methodological choices. Different choices of SFR calibrations can introduce systematic uncertainties of at least 10-15% in the star formation law slopes and 0.15-0.25 dex in their normalization, while the CO-to-H$_2$ conversion factors can additionally produce uncertainties of 20-25% for the slope and 0.10-0.20 dex for the normalization.
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.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Ness Mayker Chen
Adam K. Leroy
Laura A. Lopez
Samantha Benincasa
Mélanie Chevance
Simon C. O. Glover
Annie Hughes
Kathryn Kreckel
Sumit Sarbadhicary
Jiayi Sun
Todd A. Thompson
Dyas Utomo
Frank Bigiel
Guillermo A. Blanc
Daniel A. Dale
Kathryn Grasha
J. M. Diederik Kruijssen
Hsi-An Pan
Miguel Querejeta
Eva Schinnerer
摘要： We measure the molecular gas environment near recent ($< 100$ yr old) supernovae (SNe) using $\sim1''$ or $\leq 150$pc resolution CO (2-1) maps from the PHANGS-ALMA survey of nearby star-forming galaxies. This is arguably the first such study to approach the scales of individual massive molecular clouds ($M_{\rm mol} \gtrsim 10^{5.3}$ M$_{\odot}$). Using the Open Supernova Catalog (OSC), we identify 63 SNe within the PHANGS-ALMA footprint. We detect CO (2-1) emission near $\sim60\%$ of the sample at 150pc resolution, compared to $\sim35\%$ of map pixels with CO (2-1) emission, and up to $\sim95\%$ of the SNe at 1kpc resolution compared to $\sim80\%$ of map pixels with CO (2-1) emission. We expect the $\sim60\%$ of SNe within the same 150pc beam as a GMC will likely interact with these clouds in the future, consistent with the observation of widespread SN-molecular gas interaction in the Milky Way, while the other $\sim40\%$ of SNe without strong CO (2-1) detections will deposit their energy in the diffuse interstellar medium (ISM), perhaps helping drive large-scale turbulence or galactic outflows. Broken down by type, we detect CO (2-1) emission at the sites of $\sim85\%$ of our 9 stripped-envelope SNe (SESNe), $\sim40\%$ of our 34 Type II SNe, and $\sim35\%$ of our 13 Type Ia SNe, indicating that SESNe are most closely associated with the brightest CO (2-1) emitting regions in our sample. Our results confirm that SN explosions are not restricted to only the densest gas, and instead exert feedback across a wide range of molecular gas densities.
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