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Abstract:

Light reprocessed by dust grains emitting in the infrared enables the study of the physics at play in dusty embedded regions, where ultraviolet and optical wavelengths are attenuated. Infrared telescopes such as JWST have made it possible to study the earliest feedback phases, when stars are shielded by cocoons of gas and dust. Comprehending this phase is crucial for unravelling the effects of feedback from young stars that leads to their emergence and the dispersal of their host molecular clouds. Here we show that the transition from the embedded to the exposed phase of star formation is short (< 4 Myr) and sometimes almost absent (< 1 Myr) across a sample of 37 nearby star-forming galaxies covering a wide range of morphologies, from massive barred spirals to irregular dwarfs. The short duration of the dust-clearing timescales suggests a predominant role of pre-supernova feedback mechanisms in revealing newborn stars, confirming previous results on smaller samples and allowing, for the first time, a statistical analysis of their dependencies. We find that the timescales associated with mid-infrared emission at 21 μm, tracing a dust-embedded feedback phase, are controlled by a complex interplay between giant molecular cloud properties (masses and velocity dispersions) and galaxy morphology. We report relatively longer durations of the embedded phase of star formation in barred spiral galaxies, while this phase is significantly reduced in low-mass irregular dwarf galaxies. We discuss tentative trends with gas-phase metallicity, which may favor faster cloud dispersal at low metallicities.

Abstract:

Abstract Recent work revealed the existence of a galaxy ‘millimetre fundamental plane of black hole accretion’, a tight correlation between nuclear 1 mm luminosity, intrinsic 2 – 10 keV X-ray luminosity and supermassive black hole mass, originally discovered for nearby low- and high-luminosity active galactic nuclei. Here we use mm and X-ray data of 5 X-ray binaries (XRBs) to demonstrate that these stellar-mass black holes also lie on the mm fundamental plane, as they do at radio wavelengths. One source for which we have multi-epoch observations shows evidence of deviations from the plane after a state change, suggesting that the plane only applies to XRBs in the hard state, as is true again at radio wavelengths. We show that both advection-dominated accretion flows and compact jet models predict the existence of the plane across the entire range of black hole masses, although these models vary in their ability to accurately predict the XRB black hole masses.

Abstract:

High-resolution JWST images of nearby spiral galaxies reveal polycyclic aromatic hydrocarbon (PAH) structures that potentially trace molecular clouds, even CO-dark regions. For this paper, we identified ISM cloud structures in PHANGS-JWST 7.7μm PAH emission maps for 66 galaxies, smoothed to a common physical resolution of 30 pc and at native resolution. We extracted 108,466 cloud structures in the 30 pc sample and 146,040 clouds in the native resolution sample. We then calculated their molecular properties following a linear conversion from PAH to CO. Given the tendency for clouds in galaxy centers to overlap in velocity space, we opted to flag these clouds and omit them from the analysis in this work. The remaining clouds correspond to giant molecular clouds, such as those detected in CO(2-1) emission by ALMA, or lower surface density clouds that either fall below the ALMA detection limits of existing maps or genuinely have no molecular counterpart. We specifically used the homogenized sample for our analysis. Upon cross-matching the PAH clouds to the ALMA CO clouds at a homogenized resolution of 90 pc in 27 galaxies, we find that 41 $%$ of the PAH clouds are associated with a CO counterpart. We also show that the converted molecular cloud properties of the PAH clouds do not differ much when compared in different galactic environments. However, outside the central environment, the highest molecular mass surface density clouds are preferentially found in spiral arms. We further apply a lognormal fit to the mass spectra to an unprecedented extragalactic completeness limit of 2 , 10^ 3 , and find that spiral arms contain the most massive clouds compared to other galactic environments. Our findings 91̽�� the idea that spiral arm gravitational potentials foster the formation of high surface density clouds, and that lower surface density clouds form in the interarm regions. The cloud values show a decline of a factor of ∼ 1.5-2 toward the outer 2-3 R_e. However, the trend largely varies in individual galaxies, with flat, decreasing, and even no trend as a function of R_̊m gal. Factors such as large-scale processes, galaxy types, and morphologies might influence the observed trends. We note that combining homogenized molecular properties of individual galaxies leads to the loss of information about the physical processes that are driving deviations in trends of those properties across different galactic environments. We published two catalogs at the CDS, one at the common resolution of 30 pc and another at the native resolution. We expect them to have broad utility for future studies of PAH clouds, molecular clouds, and star formation.

Abstract:

We present radial profiles of surface brightness in UV and IR bands, estimate stellar mass surface density (Σ⋆) and star formation rate surface density (ΣSFR), and predict the CO-to-H2 conversion factor (αCO) for over 5000 local galaxies with stellar mass M⋆ ≥ 109.3 M⊙. We build these profiles and measure galaxy half-light radii using GALEX and WISE images from the z0MGS program, with special care given to highly inclined galaxies. From the UV and IR surface brightness profiles, we estimate Σ⋆ and ΣSFR and use them to predict αCO with state-of-the-art empirical prescriptions. We validate our (kpc-scale) αCO predictions against observational estimates, finding the best agreement when accounting for CO-dark gas as well as CO emissivity and excitation effects. The CO-dark correction plays a primary role in lower-mass galaxies, whereas CO emissivity and excitation effects become more important in higher-mass and more actively star-forming galaxies, respectively. We compare our estimated αCO to observed galaxy-integrated SFR to CO luminosity ratio as a function of M⋆. A large compilation of literature data suggests that star-forming galaxies with M⋆ = 109.5–11 M⊙ show strong anticorrelations of SFR/ L′CO(1–0)∝M⋆−0.29 and SFR/ L′CO(2–1)∝M⋆−0.40 . The estimated αCO trends, when combined with a constant molecular gas depletion time tdep, can only explain ≈1/3 of these SFR/ L′CO trends. This suggests that tdep being systematically shorter in lower-mass star-forming galaxies is the main cause of the observed SFR/ L′CO variations. We publish all data products from this work, including galaxy sizes, UV and IR surface brightness profiles, Σ⋆, ΣSFR, and αCO estimates.

Abstract:

The joint capabilities of the Hubble Space Telescope (HST) and JWST allow for an unparalleled look at the early lives of star clusters at near- and mid-infrared wavelengths. We present here a multiband analysis of embedded young stellar clusters in 11 nearby, star-forming galaxies, using the PHANGS-JWST and PHANGS-HST data sets. We use the Zooniverse citizen science platform to conduct an initial by-eye search for embedded clusters in near-UV/optical/near-infrared images that trace stellar continuum emission, the Paschenα and Hα recombination lines, and the 3.3 μm polycyclic aromatic hydrocarbon feature and its underlying continuum. With this approach, we identify 292 embedded cluster candidates for which we characterize their ages, masses, and levels of line-of-sight extinction by comparing the photometric data to predictions from stellar population models. The embedded cluster candidates have a median age of 4.5 Myr and an average line-of-sight extinction 〈AV〉 = 6.0 mag. We determine lower limits on source stellar masses, resulting in a median stellar mass of 103 M⊙. We use this sample of embedded cluster candidates to train multiple convolutional neural network models to carry out deep transfer learning-based searches for embedded clusters. With the aim of optimizing models for future catalog production, we compare results for four variations of training data using two neural networks. Confusion matrices for all eight model configurations, as well as inter-model identification trends, are presented. With refinement of the training sample, we determine that optimized models could serve as a pathway for future embedded cluster identification beyond our 11 galaxy sample.