Abstract:We present high spatial resolution (≈12 pc) Atacama Large Millimeter/sub-millimeter Array 12CO(J = 3 − 2) observations of the nearby lenticular galaxy NGC4429. We identify 217 giant molecular clouds within the 450 pc radius molecular gas disc. The clouds generally have smaller sizes and masses but higher surface densities and observed linewidths than those of Milky Way disc clouds. An unusually steep size – line width relation ($\sigma \propto R_{\rm c}^{0.8}$) and large cloud internal velocity gradients (0.05… Show more
“…Adding this term improves the model R 2 by only a small amount (from 0.70 to 0.71; see Figure 6), but it lowers the model BIC by more than 10, which means that our data clearly favor the model with an extra dependence on Σ å . This extra dependence is in line with theoretical models proposing that molecular clouds can be influenced by the external gravitational potential of the host galaxy stellar disk (e.g., Meidt et al 2018Meidt et al , 2020Sun et al 2020b;Liu et al 2021). 7.…”
Section: Molecular Cloud Surface Density For This Quantitysupporting
confidence: 88%
“…With this definition, a virialized object would have α vir,obj = 1, whereas an object in energy equipartition would have α vir,obj = 2. But we note that the virial parameter estimated in this way might not be a complete description of cloud dynamical states if there are strong magnetic field, surface pressure, or external tidal forces (see discussions in, e.g., Ballesteros-Paredes 2006;Sun et al 2020b;Kim et al 2021b;Liu et al 2021).…”
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.
“…Adding this term improves the model R 2 by only a small amount (from 0.70 to 0.71; see Figure 6), but it lowers the model BIC by more than 10, which means that our data clearly favor the model with an extra dependence on Σ å . This extra dependence is in line with theoretical models proposing that molecular clouds can be influenced by the external gravitational potential of the host galaxy stellar disk (e.g., Meidt et al 2018Meidt et al , 2020Sun et al 2020b;Liu et al 2021). 7.…”
Section: Molecular Cloud Surface Density For This Quantitysupporting
confidence: 88%
“…With this definition, a virialized object would have α vir,obj = 1, whereas an object in energy equipartition would have α vir,obj = 2. But we note that the virial parameter estimated in this way might not be a complete description of cloud dynamical states if there are strong magnetic field, surface pressure, or external tidal forces (see discussions in, e.g., Ballesteros-Paredes 2006;Sun et al 2020b;Kim et al 2021b;Liu et al 2021).…”
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.
“…The PHANGS (Leroy et al 2021) survey has carried out arcsecond CO(2-1) imaging of 70 nearby star-forming galaxies with ALMA, reaching the size of typical GMCs (∼100 pc resolution). These efforts are providing key empirical constraints on the physical link between star formation and gas near the "cloud" scale and the galaxy-scale environment (e.g., Hughes et al 2013a, Sun et al 2018, Schruba et al 2019, Chevance et al 2020, Sun et al 2020, Liu et al 2021. Further progress will require even larger samples, extending the parameter space especially towards low mass galaxies and below the main sequence.…”
The cold interstellar medium (ISM) plays a central role in the galaxy evolution process. It is the reservoir that fuels galaxy growth via star formation, the repository of material formed by these stars, and a sensitive tracer of internal and external processes that affect entire galaxies. Consequently, significant efforts have gone into systematic surveys of the cold ISM of the galaxies in the local Universe. This review discusses the resulting network of scaling relations connecting the atomic and molecular gas masses of galaxies with their other global properties (stellar masses, morphologies, metallicities, star formation activity...), and their implications for our understanding of galaxy evolution. Key take-home messages are as follows:• From a gas perspective, there are three main factors that determine the star formation rate of a galaxy: the total mass of its cold ISM, how much of that gas is molecular, and the rate at which any molecular gas is converted into stars. All three of these factors vary systematically across the local galaxy population.• The shape and scatter of both the star formation main sequence and the mass-metallicity relation are deeply linked to the availability of atomic and molecular gas.• Future progress will come from expanding our exploration of scaling relations into new parameter space (in particular the regime of dwarf galaxies), better connecting the cold ISM of large samples of galaxies with the environment that feeds them (the circumgalactic medium in particular), and understanding the impact of these large scales on the efficiency of the star formation process on molecular cloud scales.
“…Davis et al 2014;Kruijssen et al 2019;Gensior et al 2020), and pull existing molecular clouds apart (see e.g. Liu et al 2021). It should be noted that high shear environments would also be more Toomre-stable, due to the mutual dependence of these quantities on the shape of the rotation curve of the system.…”
Section: Understand the Correlations With 𝜇 *mentioning
confidence: 99%
“…The first cloud-scale investigations of the ISM of ETGs have revealed some have gas in discrete molecular clouds like spiral galaxies (Utomo et al 2015), while others have very smooth discs (Davis et al 2017), and some show an absence of large molecular clouds (Liu et al 2021). The physical mechanism(s) causing the observed diversity of ISM morphologies in ETGs have not yet been identified.…”
We use high-resolution maps of the molecular interstellar medium (ISM) in the centres of eighty-six nearby galaxies from the millimetre-Wave Interferometric Survey of Dark Object Masses (WISDOM) and Physics at High Angular Resolution in Nearby GalaxieS (PHANGS) surveys to investigate the physical mechanisms setting the morphology of the ISM at molecular cloud scales. We show that early-type galaxies tend to have smooth, regular molecular gas morphologies, while the ISM in spiral galaxy bulges is much more asymmetric and clumpy when observed at the same spatial scales. We quantify these differences using non-parametric morphology measures (Asymmetry, Smoothness and Gini), and compare these measurements with those extracted from idealised galaxy simulations. We show that the morphology of the molecular ISM changes systematically as a function of various large scale galaxy parameters, including galaxy morphological type, stellar mass, stellar velocity dispersion, effective stellar mass surface density, molecular gas surface density, star formation efficiency and the presence of a bar. We perform a statistical analysis to determine which of these correlated parameters best predicts the morphology of the ISM. We find the effective stellar mass surface (or volume) density to be the strongest predictor of the morphology of the molecular gas, while star formation and bars maybe be important secondary drivers. We find that gas self-gravity is not the dominant process shaping the morphology of the molecular gas in galaxy centres. Instead effects caused by the depth of the potential well such as shear, suppression of stellar spiral density waves and/or inflow affect the ability of the gas to fragment.
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