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Abstract We present 0.6–3.2 pc resolution mid-infrared (MIR) JWST images at 7.7μm (F770W) and 21μm (F2100W) covering the main star-forming regions of two of the closest star-forming low-metallicity dwarf galaxies, NGC 6822 and Wolf–Lundmark–Melotte (WLM). The images of NGC 6822 reveal filaments, edge-brightened bubbles, diffuse emission, and a plethora of point sources. By contrast, most of the MIR emission in WLM is pointlike, with a small amount of extended emission. Compared to solar-metallicity galaxies, the ratio of 7.7μm intensity ( $I_{\nu }^{\mathrm{F770W}}$), tracing polycyclic aromatic hydrocarbons (PAHs), to 21μm intensity ( $I_{\nu }^{\mathrm{F2100W}}$), tracing small, warm dust grain emission, is suppressed in these low-metallicity dwarfs. Using Atacama Large Millimeter/submillimeter Array CO(2–1) observations, we find that detected CO intensity versus $I_{\nu }^{\mathrm{F770W}}$at ≈2 pc resolution in dwarfs follows a similar relationship to that at solar metallicity and lower resolution, while the CO versus $I_{\nu }^{\mathrm{F2100W}}$relationship in dwarfs lies significantly below that derived from solar-metallicity galaxies at lower resolution, suggesting more pronounced destruction of CO molecules at low metallicity. Finally, adding in Local Group L-Band Survey 21 cm Hiobservations from the Very Large Array, we find that $I_{\nu }^{\mathrm{F2100W}}$and $I_{\nu }^{\mathrm{F770W}}$versus total gas ratios are suppressed in NGC 6822 and WLM compared to solar-metallicity galaxies. In agreement with dust models, the level of suppression appears to be at least partly accounted for by the reduced galaxy-averaged dust-to-gas and PAH-to-dust mass ratios in the dwarfs. Remaining differences are likely due to spatial variations in dust model parameters, which should be an exciting direction for future work in local dwarf galaxies. 

The property of star formation rate (SFR) is tightly connected to the amount of dense gas in molecular clouds. However, it is not fully understood how the relationship between dense molecular gas and star formation varies within galaxies and in different morphological environments. Most previous studies have typically been limited to kiloparsec-scale resolution such that different environments could not be resolved. In this work, we present new ALMA observations of HCN(1−0) at 260 pc scale to test how the amount of dense gas and its ability to form stars varies with environmental properties. Combined with existing CO(2−1) observations from ALMA and Hαfrom MUSE, we measured the HCN/CO line ratio, a proxy for the dense gas fraction, and SFR/HCN, a proxy for the star formation efficiency of the dense gas. We find a systematic > 1 dex increase (decreases) of HCN/CO (SFR/HCN) towards the centre of the galaxy, and roughly flat trends of these ratios (average variations < 0.3 dex) throughout the disc. While spiral arms, interarm regions, and bar ends show similar HCN/CO and SFR/HCN, on the bar, there is a significantly lower SFR/HCN at a similar HCN/CO. The strong environmental influence on dense gas and star formation in the centre of NGC 4321, suggests either that clouds couple strongly to the surrounding pressure or that HCN emission traces more of the bulk molecular gas that is less efficiently converted into stars. Across the disc, where the ISM pressure is typically low, SFR/HCN is more constant, indicating a decoupling of the clouds from their surrounding environment. The low SFR/HCN on the bar suggests that gas dynamics (e.g. shear and streaming motions) can have a large effect on the efficiency with which dense gas is converted into stars. In addition, we show that HCN/CO is a good predictor of the mean molecular gas surface density at 260 pc scales across environments and physical conditions. 

Abstract We present the largest catalog to date of star clusters and compact associations in nearby galaxies. We have performed aV-band-selected census of clusters across the 38 spiral galaxies of the PHANGS–Hubble Space Telescope (HST) Treasury Survey, and measured integrated, aperture-corrected near-ultraviolet-U-B-V-Iphotometry. This work has resulted in uniform catalogs that contain ∼20,000 clusters and compact associations, which have passed human inspection and morphological classification, and a larger sample of ∼100,000 classified by neural network models. Here, we report on the observed properties of these samples, and demonstrate that tremendous insight can be gained from just the observed properties of clusters, even in the absence of their transformation into physical quantities. In particular, we show the utility of the UBVI color–color diagram, and the three principal features revealed by the PHANGS-HST cluster sample: the young cluster locus, the middle-age plume, and the old globular cluster clump. We present an atlas of maps of the 2D spatial distribution of clusters and compact associations in the context of the molecular clouds from PHANGS–Atacama Large Millimeter/submillimeter Array. We explore new ways of understanding this large data set in a multiscale context by bringing together once-separate techniques for the characterization of clusters (color–color diagrams and spatial distributions) and their parent galaxies (galaxy morphology and location relative to the galaxy main sequence). A companion paper presents the physical properties: ages, masses, and dust reddenings derived using improved spectral energy distribution fitting techniques. 

Abstract Recent studies have revealed a strong relation between the sample-averaged black hole (BH) accretion rate (BHAR) and star formation rate (SFR) among bulge-dominated galaxies—i.e., “lockstep” BH–bulge growth—in the distant universe. This relation might be closely connected to the BH–bulge mass correlation observed in the local universe. To further understand BH–bulge coevolution, we present Atacama Large Millimeter/submillimeter Array (ALMA) CO(2–1) or CO(3–2) observations of seven star-forming bulge-dominated galaxies at z = 0.5–2.5. Using the ALMA data, we detect significant (>3 σ ) CO emission from four objects. For our sample of seven galaxies, we measure (or constrain with upper limits) their CO line fluxes and estimate their molecular gas masses ( M gas ). We also estimate their stellar masses ( M star ) and SFRs, by modeling their spectral energy distributions. Using these physical properties, we derive the gas depletion timescales ( τ dep ≡ M gas /SFR) and compare them with the bulge/BH growth timescales ( τ grow ≡ M star /SFR ∼ M BH /BHAR). Our sample generally has τ dep shorter than τ grow by a median factor of ≳4, indicating that the cold gas will be depleted before significant bulge/BH growth takes place. This result suggests that BH–bulge lockstep growth is mainly responsible for maintaining the mass relation, not creating it. We note that our sample is small and limited to z < 2.5; JWST and ALMA will be able to probe to higher redshifts in the near future. 

Abstract Modern and future surveys effectively provide a panchromatic view for large numbers of extragalactic objects. Consistently modeling these multiwavelength survey data is a critical but challenging task for extragalactic studies. The Code Investigating GALaxy Emission ( cigale ) is an efficient python code for spectral energy distribution (SED) fitting of galaxies and active galactic nuclei (AGNs). Recently, a major extension of cigale (named x-cigale ) has been developed to account for AGN/galaxy X-ray emission and improve AGN modeling at UV-to-IR wavelengths. Here, we apply x-cigale to different samples, including Cosmological Evolution Survey (COSMOS) spectroscopic type 2 AGNs, Chandra Deep Field-South X-ray detected normal galaxies, Sloan Digital Sky Survey quasars, and COSMOS radio objects. From these tests, we identify several weaknesses of x-cigale and improve the code accordingly. These improvements are mainly related to AGN intrinsic X-ray anisotropy, X-ray binary emission, AGN accretion-disk SED shape, and AGN radio emission. These updates improve the fit quality and allow for new interpretation of the results, based on which we discuss physical implications. For example, we find that AGN intrinsic X-ray anisotropy is moderate, and can be modeled as L X ( θ ) ∝ 1 + cos θ , where θ is the viewing angle measured from the AGN axis. We merge the new code into the major branch of cigale , and publicly release this new version as cigale v2022.0 on https://cigale.lam.fr . 

Abstract Determining how the galactic environment, especially the high gas densities and complex dynamics in bar-fed galaxy centers, alters the star formation efficiency (SFE) of molecular gas is critical to understanding galaxy evolution. However, these same physical or dynamical effects also alter the emissivity properties of CO, leading to variations in the CO-to-H₂conversion factor (α_CO) that impact the assessment of the gas column densities and thus of the SFE. To address such issues, we investigate the dependence ofα_COon the local CO velocity dispersion at 150 pc scales using a new set of dust-basedα_COmeasurements and propose a newα_COprescription that accounts for CO emissivity variations across galaxies. Based on this prescription, we estimate the SFE in a sample of 65 galaxies from the PHANGS–Atacama Large Millimeter/submillimeter Array survey. We find increasing SFE toward high-surface-density regions like galaxy centers, while using a constant or metallicity-basedα_COresults in a more homogeneous SFE throughout the centers and disks. Our prescription further reveals a mean molecular gas depletion time of 700 Myr in the centers of barred galaxies, which is overall three to four times shorter than in nonbarred galaxy centers or the disks. Across the galaxy disks, the depletion time is consistently around 2–3 Gyr, regardless of the choice ofα_COprescription. All together, our results suggest that the high level of star formation activity in barred centers is not simply due to an increased amount of molecular gas, but also to an enhanced SFE compared to nonbarred centers or disk regions. 

ABSTRACT When completed, the PHANGS–HST project will provide a census of roughly 50 000 compact star clusters and associations, as well as human morphological classifications for roughly 20 000 of those objects. These large numbers motivated the development of a more objective and repeatable method to help perform source classifications. In this paper, we consider the results for five PHANGS–HST galaxies (NGC 628, NGC 1433, NGC 1566, NGC 3351, NGC 3627) using classifications from two convolutional neural network architectures (RESNET and VGG) trained using deep transfer learning techniques. The results are compared to classifications performed by humans. The primary result is that the neural network classifications are comparable in quality to the human classifications with typical agreement around 70 to 80 per cent for Class 1 clusters (symmetric, centrally concentrated) and 40 to 70 per cent for Class 2 clusters (asymmetric, centrally concentrated). If Class 1 and 2 are considered together the agreement is 82 ± 3 per cent. Dependencies on magnitudes, crowding, and background surface brightness are examined. A detailed description of the criteria and methodology used for the human classifications is included along with an examination of systematic differences between PHANGS–HST and LEGUS. The distribution of data points in a colour–colour diagram is used as a ‘figure of merit’ to further test the relative performances of the different methods. The effects on science results (e.g. determinations of mass and age functions) of using different cluster classification methods are examined and found to be minimal. 

ABSTRACT Understanding the spatial distribution of metals within galaxies allows us to study the processes of chemical enrichment and mixing in the interstellar medium. In this work, we map the 2D distribution of metals using a Gaussian Process Regression (GPR) for 19 star-forming galaxies observed with the Very Large Telescope/Multi Unit Spectroscopic Explorer (VLT–MUSE) as a part of the PHANGS–MUSE survey. We find that 12 of our 19 galaxies show significant 2D metallicity variation. Those without significant variations typically have fewer metallicity measurements, indicating this is due to the dearth of $${\rm H\, {\small II}}$$ regions in these galaxies, rather than a lack of higher-order variation. After subtracting a linear radial gradient, we see no enrichment in the spiral arms versus the disc. We measure the 50 per cent correlation scale from the two-point correlation function of these radially subtracted maps, finding it to typically be an order of magnitude smaller than the fitted GPR kernel scale length. We study the dependence of the two-point correlation scale length with a number of global galaxy properties. We find no relationship between the 50 per cent correlation scale and the overall gas turbulence, in tension with existing theoretical models. We also find more actively star-forming galaxies, and earlier type galaxies have a larger 50 per cent correlation scale. The size and stellar mass surface density do not appear to correlate with the 50 per cent correlation scale, indicating that perhaps the evolutionary state of the galaxy and its current star formation activity is the strongest indicator of the homogeneity of the metal distribution. 

ABSTRACT We present the results of a proof-of-concept experiment that demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in Hubble Space Telescope(HST) ultraviolet-optical imaging of nearby spiral galaxies ($$D\lesssim 20\, \textrm{Mpc}$$) in the Physics at High Angular Resolution in Nearby GalaxieS (PHANGS)–HST survey. Given the relatively small nature of existing, human-labelled star cluster samples, we transfer the knowledge of state-of-the-art neural network models for real-object recognition to classify star clusters candidates into four morphological classes. We perform a series of experiments to determine the dependence of classification performance on neural network architecture (ResNet18 and VGG19-BN), training data sets curated by either a single expert or three astronomers, and the size of the images used for training. We find that the overall classification accuracies are not significantly affected by these choices. The networks are used to classify star cluster candidates in the PHANGS–HST galaxy NGC 1559, which was not included in the training samples. The resulting prediction accuracies are 70 per cent, 40 per cent, 40–50 per cent, and 50–70 per cent for class 1, 2, 3 star clusters, and class 4 non-clusters, respectively. This performance is competitive with consistency achieved in previously published human and automated quantitative classification of star cluster candidate samples (70–80 per cent, 40–50 per cent, 40–50 per cent, and 60–70 per cent). The methods introduced herein lay the foundations to automate classification for star clusters at scale, and exhibit the need to prepare a standardized data set of human-labelled star cluster classifications, agreed upon by a full range of experts in the field, to further improve the performance of the networks introduced in this study. 

Abstract We present the radio properties of 66 spectroscopically confirmed normal star-forming galaxies (SFGs) at 4.4 <z< 5.9 in the COSMOS field that were [Cii]-detected in the Atacama Large Millimeter/submillimeter Array Large Program to INvestigate [Cii] at Early times (ALPINE). We separate these galaxies (“Cii-detected-all”) into lower-redshift (“Cii-detected-lz”; 〈z〉 = 4.5) and higher-redshift (“Cii-detected-hz”; 〈z〉 = 5.6) subsamples, and stack multiwavelength imaging for each subsample from X-ray to radio bands. A radio signal is detected in the stacked 3 GHz images of the Cii-detected-all and lz samples at ≳3σ. We find that the infrared–radio correlation of our sample, quantified byq_TIR, is lower than the local relation for normal SFGs at a ∼3σsignificance level, and is instead broadly consistent with that of bright submillimeter galaxies at 2 <z< 5. Neither of these samples show evidence of dominant active galactic nucleus activity in their stacked spectral energy distributions (SEDs), UV spectra, or stacked X-ray images. Although we cannot rule out the possible effects of the assumed spectral index and applied infrared SED templates in causing these differences, at least partially, the lower obscured fraction of star formation than at lower redshift can alleviate the tension between our stackedq_TIRs and those of local normal SFGs. It is possible that the dust buildup, which primarily governs the infrared emission, in addition to older stellar populations, has not had enough time to occur fully in these galaxies, whereas the radio emission can respond on a more rapid timescale. Therefore, we might expect a lowerq_TIRto be a general property of high-redshift SFGs.