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We use PHANGS–James Webb Space Telescope (JWST) data to identify and classify 1271 compact 21μm sources in four nearby galaxies using MIRI F2100W data. We identify sources using a dendrogram-based algorithm, and we measure the background-subtracted flux densities for JWST bands from 2 to 21μm. Using the spectral energy distribution (SED) in JWST and HST bands plus ALMA and MUSE/VLT observations, we classify the sources by eye. Then we use this classification to define regions in color–color space and so establish a quantitative framework for classifying sources. We identify 1085 sources as belonging to the ISM of the target galaxies with the remainder being dusty stars or background galaxies. These 21μm sources are strongly spatially associated with Hiiregions (>92% of sources), while 74% of the sources are coincident with a stellar association defined in the HST data. Using SED fitting, we find that the stellar masses of the 21μm sources span a range of 10²–10⁴M_⊙with mass-weighted ages down to 2 Myr. There is a tight correlation between attenuation-corrected Hαand 21μm luminosity forL_ν,F2100W> 10¹⁹W Hz⁻¹. Young embedded source candidates selected at 21μm are found below this threshold and haveM_⋆< 10³M_⊙.

 

In the hierarchical view of star formation, giant molecular clouds (GMCs) undergo fragmentation to form small-scale structures made up of stars and star clusters. Here we study the connection between young star clusters and cold gas across a range of extragalactic environments by combining the high resolution (1″) PHANGS–ALMA catalogue of GMCs with the star cluster catalogues from PHANGS–HST. The star clusters are spatially matched with the GMCs across a sample of 11 nearby star-forming galaxies with a range of galactic environments (centres, bars, spiral arms, etc.). We find that after 4 − 6 Myr the star clusters are no longer associated with any gas clouds. Additionally, we measure the autocorrelation of the star clusters and GMCs as well as their cross-correlation to quantify the fractal nature of hierarchical star formation. Young (≤10 Myr) star clusters are more strongly autocorrelated on kpc and smaller spatial scales than the $\gt \, 10$ Myr stellar populations, indicating that the hierarchical structure dissolves over time.

 

Connecting the gas in H ii regions to the underlying source of the ionizing radiation can help us constrain the physical processes of stellar feedback and how H ii regions evolve over time. With PHANGS–MUSE, we detect nearly 24 000 H ii regions across 19 galaxies and measure the physical properties of the ionized gas (e.g. metallicity, ionization parameter, and density). We use catalogues of multiscale stellar associations from PHANGS–HST to obtain constraints on the age of the ionizing sources. We construct a matched catalogue of 4177 H ii regions that are clearly linked to a single ionizing association. A weak anticorrelation is observed between the association ages and the $\mathrm{H}\, \alpha$ equivalent width $\mathrm{EW}(\mathrm{H}\, \alpha)$, the $\mathrm{H}\, \alpha/\mathrm{FUV}$ flux ratio, and the ionization parameter, log q. As all three are expected to decrease as the stellar population ages, this could indicate that we observe an evolutionary sequence. This interpretation is further supported by correlations between all three properties. Interpreting these as evolutionary tracers, we find younger nebulae to be more attenuated by dust and closer to giant molecular clouds, in line with recent models of feedback-regulated star formation. We also observe strong correlations with the local metallicity variations and all three proposed age tracers, suggestive of star formation preferentially occurring in locations of locally enhanced metallicity. Overall, $\mathrm{EW}(\mathrm{H}\, \alpha)$ and log q show the most consistent trends and appear to be most reliable tracers for the age of an H ii region.

 

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. 

We compare embedded young massive star clusters (YMCs) to (sub-)millimeter line observations tracing the excitation and dissociation of molecular gas in the starburst ring of NGC 1365. This galaxy hosts one of the strongest nuclear starbursts and richest populations of YMCs within 20 Mpc. Here we combine near-/mid-IR PHANGS–JWST imaging with new Atacama Large Millimeter/submillimeter Array multi-JCO (1–0, 2–1 and 4–3) and [Ci] (1–0) mapping, which we use to trace CO excitation viaR₄₂=I_CO(4−3)/I_CO(2−1)andR₂₁=I_CO(2−1)/I_CO(1−0)and dissociation viaR_CICO=I_[CI](1−0)/I_CO(2−1)at 330 pc resolution. We find that the gas flowing into the starburst ring from northeast to southwest appears strongly affected by stellar feedback, showing decreased excitation (lowerR₄₂) and increased signatures of dissociation (higherR_CICO) in the downstream regions. There, radiative-transfer modeling suggests that the molecular gas density decreases and temperature and [CI/CO] abundance ratio increase. We compareR₄₂andR_CICOwith local conditions across the regions and find that both correlate with near-IR 2μm emission tracing the YMCs and with both polycyclic aromatic hydrocarbon (11.3μm) and dust continuum (21μm) emission. In general,R_CICOexhibits ∼0.1 dex tighter correlations thanR₄₂, suggestingCito be a more sensitive tracer of changing physical conditions in the NGC 1365 starburst than CO (4–3). Our results are consistent with a scenario where gas flows into the two arm regions along the bar, becomes condensed/shocked, forms YMCs, and then these YMCs heat and dissociate the gas.

 

Large-scale bars can fuel galaxy centers with molecular gas, often leading to the development of dense ringlike structures where intense star formation occurs, forming a very different environment compared to galactic disks. We pair ∼0.″3 (30 pc) resolution new JWST/MIRI imaging with archival ALMA CO(2–1) mapping of the central ∼5 kpc of the nearby barred spiral galaxy NGC 1365 to investigate the physical mechanisms responsible for this extreme star formation. The molecular gas morphology is resolved into two well-known bright bar lanes that surround a smooth dynamically cold gas disk (R_gal∼ 475 pc) reminiscent of non-star-forming disks in early-type galaxies and likely fed by gas inflow triggered by stellar feedback in the lanes. The lanes host a large number of JWST-identified massive young star clusters. We find some evidence for temporal star formation evolution along the ring. The complex kinematics in the gas lanes reveal strong streaming motions and may be consistent with convergence of gas streamlines expected there. Indeed, the extreme line widths are found to be the result of inter-“cloud” motion between gas peaks;ScousePydecomposition reveals multiple components with line widths of 〈σ_CO,scouse〉 ≈ 19 km s⁻¹and surface densities of$〈{\mathrm{\Sigma }}_{{\mathrm{H}}_2,\mathrm{scouse}}〉\approx 800M_{\odot }{\mathrm{pc}}^{-2}$, similar to the properties observed throughout the rest of the central molecular gas structure. Tailored hydrodynamical simulations exhibit many of the observed properties and imply that the observed structures are transient and highly time-variable. From our study of NGC 1365, we conclude that it is predominantly the high gas inflow triggered by the bar that is setting the star formation in its CMZ.

 

We combine JWST observations with Atacama Large Millimeter/submillimeter Array CO and Very Large Telescope MUSE Hαdata to examine off-spiral arm star formation in the face-on, grand-design spiral galaxy NGC 628. We focus on the northern spiral arm, around a galactocentric radius of 3–4 kpc, and study two spurs. These form an interesting contrast, as one is CO-rich and one CO-poor, and they have a maximum azimuthal offset in MIRI 21μm and MUSE Hαof around 40° (CO-rich) and 55° (CO-poor) from the spiral arm. The star formation rate is higher in the regions of the spurs near spiral arms, but the star formation efficiency appears relatively constant. Given the spiral pattern speed and rotation curve of this galaxy and assuming material exiting the arms undergoes purely circular motion, these offsets would be reached in 100–150 Myr, significantly longer than the 21μm and Hαstar formation timescales (both < 10 Myr). The invariance of the star formation efficiency in the spurs versus the spiral arms indicates massive star formation is not only triggered in spiral arms, and cannot simply occur in the arms and then drift away from the wave pattern. These early JWST results show that in situ star formation likely occurs in the spurs, and that the observed young stars are not simply the “leftovers” of stellar birth in the spiral arms. The excellent physical resolution and sensitivity that JWST can attain in nearby galaxies will well resolve individual star-forming regions and help us to better understand the earliest phases of star formation.

 

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. 

We present a high-resolution view of bubbles within the Phantom Galaxy (NGC 628), a nearby (∼10 Mpc), star-forming (∼2M_⊙yr⁻¹), face-on (i∼ 9°) grand-design spiral galaxy. With new data obtained as part of the Physics at High Angular resolution in Nearby GalaxieS (PHANGS)-JWST treasury program, we perform a detailed case study of two regions of interest, one of which contains the largest and most prominent bubble in the galaxy (the Phantom Void, over 1 kpc in diameter), and the other being a smaller region that may be the precursor to such a large bubble (the Precursor Phantom Void). When comparing to matched-resolution Hαobservations from the Hubble Space Telescope, we see that the ionized gas is brightest in the shells of both bubbles, and is coincident with the youngest (∼1 Myr) and most massive (∼10⁵M_⊙) stellar associations. We also find an older generation (∼20 Myr) of stellar associations is present within the bubble of the Phantom Void. From our kinematic analysis of the HI, H₂(CO), and Hiigas across the Phantom Void, we infer a high expansion speed of around 15 to 50 km s⁻¹. The large size and high expansion speed of the Phantom Void suggest that the driving mechanism is sustained stellar feedback due to multiple mechanisms, where early feedback first cleared a bubble (as we observe now in the Precursor Phantom Void), and since then supernovae have been exploding within the cavity and have accelerated the shell. Finally, comparison to simulations shows a striking resemblance to our JWST observations, and suggests that such large-scale, stellar-feedback-driven bubbles should be common within other galaxies.