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  1. Abstract

    We have used the Mid-InfraRed Instrument (MIRI) on the James Webb Space Telescope (JWST) to obtain the first spatially resolved, mid-infrared images ofIIZw096, a merging luminous infrared galaxy (LIRG) atz= 0.036. Previous observations with the Spitzer Space Telescope suggested that the vast majority of the total IR luminosity (LIR) of the system originated from a small region outside of the two merging nuclei. New observations with JWST/MIRI now allow an accurate measurement of the location and luminosity density of the source that is responsible for the bulk of the IR emission. We estimate that 40%–70% of the IR bolometric luminosity, or 3–5 × 1011L, arises from a source no larger than 175 pc in radius, suggesting a luminosity density of at least 3–5 × 1012Lkpc−2. In addition, we detect 11 other star-forming sources, five of which were previously unknown. The MIRI F1500W/F560W colors of most of these sources, including the source responsible for the bulk of the far-IR emission, are much redder than the nuclei of local LIRGs. These observations reveal the power of JWST to disentangle the complex regions at the hearts of merging, dusty galaxies.

  2. Abstract

    The nearby, luminous infrared galaxy NGC 7469 hosts a Seyfert nucleus with a circumnuclear star-forming ring and is thus the ideal local laboratory for investigating the starburst–AGN (active galactic nucleus) connection in detail. We present integral-field observations of the central 1.3 kpc region in NGC 7469 obtained with the JWST Mid-InfraRed Instrument. Molecular and ionized gas distributions and kinematics at a resolution of ∼100 pc over the 4.9–7.6μm region are examined to study the gas dynamics influenced by the central AGN. The low-ionization [Feii]λ5.34μm and [Arii]λ6.99μm lines are bright on the nucleus and in the starburst ring, as opposed to H2S(5)λ6.91μm, which is strongly peaked at the center and surrounding ISM. The high-ionization [Mgv] line is resolved and shows a broad, blueshifted component associated with the outflow. It has a nearly face-on geometry that is strongly peaked on the nucleus, where it reaches a maximum velocity of −650 km s−1, and extends about 400 pc to the east. Regions of enhanced velocity dispersion in H2and [Feii] ∼ 180 pc from the AGN that also show highL(H2)/L(PAH) andL([Feii])/L(Pfα) ratios to the W and N of the nucleus pinpoint regions where the ionized outflow is depositing energy, via shocks, into themore »dense interstellar medium between the nucleus and the starburst ring. These resolved mid-infrared observations of the nuclear gas dynamics demonstrate the power of JWST and its high-sensitivity integral-field spectroscopic capability to resolve feedback processes around supermassive black holes in the dusty cores of nearby luminous infrared galaxies.

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  3. 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 ofmore »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.« less
  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
    Free, publicly-accessible full text available January 1, 2023
  5. 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 starmore »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.« less
  6. 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