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  1. Abstract Physical and chemical properties of the interstellar medium (ISM) at subgalactic (∼kiloparsec) scales play an indispensable role in controlling the ability of gas to form stars. In this paper, we use the TNG50 cosmological simulation to explore the physical parameter space of eight resolved ISM properties in star-forming regions to constrain the areas of this hyperspace where most star-forming environments exist. We deconstruct our simulated galaxies spanning a wide range of mass ( M ⋆ = 10 7 –10 11 M ⊙ ) and redshift (0 ≤ z ≤ 3) into kiloparsec-sized regions and statistically analyze the gas/stellar surface densities, gas metallicity, vertical stellar velocity dispersion, epicyclic frequency, and dark-matter volumetric density representative of each region in the context of their star formation activity and environment (radial galactocentric location). By examining the star formation rate (SFR) weighted distributions of these properties, we show that stars primarily form in two distinct environmental regimes, which are brought about by an underlying bicomponent radial SFR profile in galaxies. We examine how the relative prominence of these regimes depends on galaxy mass and cosmic time. We also compare our findings with those from integral field spectroscopy observations and find similarities as well asmore »departures. Further, using dimensionality reduction, we characterize the aforementioned hyperspace to reveal a high degree of multicollinearity in relationships among ISM properties that drive the distribution of star formation at kiloparsec scales. Based on this, we show that a reduced 3D representation underpinned by a multivariate radius relationship is sufficient to capture most of the variance in the original 8D space.« less
  2. ABSTRACT

    We investigate the nature of the scaling relations between the surface density of star formation rate (ΣSFR), stellar mass (Σ*), and molecular gas mass ($\Sigma _{\rm H_2}$), aiming at distinguishing between the relations that are primary, i.e. more fundamental, and those which are instead an indirect by-product of the other relations. We use the ALMA-MaNGA QUEnching and STar formation survey and analyse the data by using both partial correlations and random forest regression techniques. We unambiguously find that the strongest intrinsic correlation is between ΣSFR and $\Sigma _{\rm H_2}$ (i.e. the resolved Schmidt–Kennicutt relation), followed by the correlation between $\Sigma _{\rm H_2}$ and Σ* (resolved molecular gas main sequence, rMGMS). Once these two correlations are taken into account, we find that there is no evidence for any intrinsic correlation between ΣSFR and Σ*, implying that star formation rate (SFR) is entirely driven by the amount of molecular gas, while its dependence on stellar mass (i.e. the resolved star forming main sequence, rSFMS) simply emerges as a consequence of the relationship between molecular gas and stellar mass.

  3. Abstract We measure the low- J CO line ratios R 21 ≡ CO (2–1)/CO (1–0), R 32 ≡ CO (3–2)/CO (2–1), and R 31 ≡CO (3–2)/CO (1–0) using whole-disk CO maps of nearby galaxies. We draw CO (2–1) from PHANGS-ALMA, HERACLES, and follow-up IRAM surveys; CO (1–0) from COMING and the Nobeyama CO Atlas of Nearby Spiral Galaxies; and CO (3–2) from the James Clerk Maxwell Telescope Nearby Galaxy Legacy Survey and Atacama Pathfinder Experiment Large APEX Sub-Millimetre Array mapping. All together, this yields 76, 47, and 29 maps of R 21 , R 32 , and R 31 at 20″ ∼ 1.3 kpc resolution, covering 43, 34, and 20 galaxies. Disk galaxies with high stellar mass, log ( M ⋆ / M ⊙ ) = 10.25 – 11 , and star formation rate (SFR) = 1–5 M ⊙ yr −1 , dominate the sample. We find galaxy-integrated mean values and a 16%–84% range of R 21 = 0.65 (0.50–0.83), R 32 = 0.50 (0.23–0.59), and R 31 = 0.31 (0.20–0.42). We identify weak trends relating galaxy-integrated line ratios to properties expected to correlate with excitation, including SFR/ M ⋆ and SFR/ L CO . Within galaxies, we measure centralmore »enhancements with respect to the galaxy-averaged value of ∼ 0.18 − 0.14 + 0.09 dex for R 21 , 0.27 − 0.15 + 0.13 dex for R 31 , and 0.08 − 0.09 + 0.11 dex for R 32 . All three line ratios anticorrelate with galactocentric radius and positively correlate with the local SFR surface density and specific SFR, and we provide approximate fits to these relations. The observed ratios can be reasonably reproduced by models with low temperature, moderate opacity, and moderate densities, in good agreement with expectations for the cold interstellar medium. Because the line ratios are expected to anticorrelate with the CO (1–0)-to-H 2 conversion factor, α CO 1 − 0 , these results have general implications for the interpretation of CO emission from galaxies.« less
    Free, publicly-accessible full text available March 1, 2023
  4. Abstract The PHANGS program is building the first data set to enable the multiphase, multiscale study of star formation across the nearby spiral galaxy population. This effort is enabled by large survey programs with the Atacama Large Millimeter/submillimeter Array (ALMA), MUSE on the Very Large Telescope, and the Hubble Space Telescope (HST), with which we have obtained CO(2–1) imaging, optical spectroscopic mapping, and high-resolution UV–optical imaging, respectively. Here, we present PHANGS-HST, which has obtained NUV– U – B – V – I imaging of the disks of 38 spiral galaxies at distances of 4–23 Mpc, and parallel V - and I -band imaging of their halos, to provide a census of tens of thousands of compact star clusters and multiscale stellar associations. The combination of HST, ALMA, and VLT/MUSE observations will yield an unprecedented joint catalog of the observed and physical properties of ∼100,000 star clusters, associations, H ii regions, and molecular clouds. With these basic units of star formation, PHANGS will systematically chart the evolutionary cycling between gas and stars across a diversity of galactic environments found in nearby galaxies. We discuss the design of the PHANGS-HST survey and provide an overview of the HST data processing pipeline andmore »first results. We highlight new methods for selecting star cluster candidates, morphological classification of candidates with convolutional neural networks, and identification of stellar associations over a range of physical scales with a watershed algorithm. We describe the cross-observatory imaging, catalogs, and software products to be released. The PHANGS high-level science products will seed a broad range of investigations, in particular, the study of embedded stellar populations and dust with the James Webb Space Telescope, for which a PHANGS Cycle 1 Treasury program to obtain eight-band 2–21 μ m imaging has been approved.« less
  5. Abstract We present PHANGS–ALMA, the first survey to map CO J = 2 → 1 line emission at ∼1″ ∼100 pc spatial resolution from a representative sample of 90 nearby ( d ≲ 20 Mpc) galaxies that lie on or near the z = 0 “main sequence” of star-forming galaxies. CO line emission traces the bulk distribution of molecular gas, which is the cold, star-forming phase of the interstellar medium. At the resolution achieved by PHANGS–ALMA, each beam reaches the size of a typical individual giant molecular cloud, so that these data can be used to measure the demographics, life cycle, and physical state of molecular clouds across the population of galaxies where the majority of stars form at z = 0. This paper describes the scientific motivation and background for the survey, sample selection, global properties of the targets, Atacama Large Millimeter/submillimeter Array (ALMA) observations, and characteristics of the delivered data and derived data products. As the ALMA sample serves as the parent sample for parallel surveys with MUSE on the Very Large Telescope, the Hubble Space Telescope, AstroSat, the Very Large Array, and other facilities, we include a detailed discussion of the sample selection. We detail the estimationmore »of galaxy mass, size, star formation rate, CO luminosity, and other properties, compare estimates using different systems and provide best-estimate integrated measurements for each target. We also report the design and execution of the ALMA observations, which combine a Cycle 5 Large Program, a series of smaller programs, and archival observations. Finally, we present the first 1″ resolution atlas of CO emission from nearby galaxies and describe the properties and contents of the first PHANGS–ALMA public data release.« less
  6. ABSTRACT

    We investigate which physical properties are most predictive of the position of local star forming galaxies on the BPT diagrams, by means of different Machine Learning (ML) algorithms. Exploiting the large statistics from the Sloan Digital Sky Survey (SDSS), we define a framework in which the deviation of star-forming galaxies from their median sequence can be described in terms of the relative variations in a variety of observational parameters. We train artificial neural networks (ANN) and random forest (RF) trees to predict whether galaxies are offset above or below the sequence (via classification), and to estimate the exact magnitude of the offset itself (via regression). We find, with high significance, that parameters primarily associated to variations in the nitrogen-over-oxygen abundance ratio (N/O) are the most predictive for the [N ii]-BPT diagram, whereas properties related to star formation (like variations in SFR or EW(H α)) perform better in the [S ii]-BPT diagram. We interpret the former as a reflection of the N/O–O/H relationship for local galaxies, while the latter as primarily tracing the variation in the effective size of the S+ emitting region, which directly impacts the [S ii] emission lines. This analysis paves the way to assess to what extent the physics shapingmore »local BPT diagrams is also responsible for the offsets seen in high redshift galaxies or, instead, whether a different framework or even different mechanisms need to be invoked.

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