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Abstract VV 191 is a nearby (z∼ 0.05), overlapping (occulting) galaxy pair, where a multiple-armed spiral galaxy is backlit by an elliptical galaxy. The overlap is used to derive and map dust attenuation in two James Webb Space Telescope NIRCam filters (F090W and F150W) and one visible-band Hubble Space Telescope Wide Field Camera 3 filter (F606W). We present maps of the attenuation in each filter, the ratio of total to selective attenuation with a near-infrared (NIR) color excess, $R_{\widetilde{VI}}$, and the NIR attenuation curve power-law index,α, approximated via Monte Carlo resampling methods. The maps trace the optically thin outer disk of foreground galaxy VV 191b at ∼100 pc physical resolution. We find the distributions of attenuation and $R_{\widetilde{VI}}$to be close to log-normal, and the distribution ofαto be close to Gaussian throughout the disk and in high signal-to-noise ratio areas of VV191b. We analyze three spatially resolved handpicked regions in the far outer disk that are well backlit by the background galaxy. 

In the era of rapidly growing astronomical data, the gap between data collection and analysis is a significant barrier, especially for teams searching for rare scientific objects. Although machine learning (ML) can quickly parse large data sets, it struggles to robustly identify scientifically interesting objects, a task at which humans excel. Human-in-the-loop (HITL) strategies that combine the strengths of citizen science (CS) and ML offer a promising solution, but first, we need to better understand the relationship between human- and machine-identified samples. In this work, we present a case study from the Galaxy Zoo: Weird & Wonderful project, where volunteers inspected ~200,000 astronomical images—processed by an ML-based anomaly detection model—to identify those with unusual or interesting characteristics. Volunteer-selected images with common astrophysical characteristics had higher consensus, while rarer or more complex ones had lower consensus. This suggests low-consensus choices shouldn’t be dismissed in further explorations. Additionally, volunteers were better at filtering out uninteresting anomalies, such as image artifacts, which the machine struggled with. We also found that a higher ML-generated anomaly score that indicates images’ low-level feature anomalousness was a better predictor of the volunteers’ consensus choice. Combining a locus of high volunteer-consensus images within the ML learnt feature space and anomaly score, we demonstrated a decision boundary that can effectively isolate images with unusual and potentially scientifically interesting characteristics. Using this case study, we lay important guidelines for future research studies looking to adapt and operationalize human-machine collaborative frameworks for efficient anomaly detection in big data. 

ABSTRACT We present Chandra X-ray Observatory observations and Space Telescope Imaging Spectrograph spectra of NGC 5972, one of the 19 ‘Voorwerpjes’ galaxies. This galaxy contains an extended emission-line region (EELR) and an arcsecond scale nuclear bubble. NGC 5972 is a faded active galactic nucleus (AGN), with EELR luminosity suggesting a 2.1 dex decrease in Lbol in the last ∼5 × 104 yr. We investigate the role of AGN feedback in exciting the EELR and bubble given the long-term variability and potential accretion state changes. We detect broad-band (0.3–8 keV) X-ray emission in the near-nuclear regions, coincident with the [O iii] bubble, as well as diffuse soft X-ray emission coincident with the EELR. The soft nuclear (0.5–1.5 keV) emission is spatially extended and the spectra are consistent with two apec thermal populations (∼0.80 and ∼0.10 keV). We find a bubble age >2.2 Myr, suggesting formation before the current variability. We find evidence for efficient feedback with $$P_{\textrm {kin}}/L_{\textrm {bol}}\sim 0.8~{{\ \rm per\ cent}}$$, which may be overestimated given the recent Lbol variation. [O iii] kinematics show a 300 km s−1 high-ionization velocity consistent with disturbed rotation or potentially the line-of-sight component of a ∼780 km s−1 thermal X-ray outflow capable of driving strong shocks to photoionize the precursor material. We explore possibilities to explain the overall jet, radio lobe and EELR misalignment including evidence for a double supermassive black hole which could support a complex misaligned system. 

Abstract Mergers play a complex role in galaxy formation and evolution. Continuing to improve our understanding of these systems requires ever larger samples, which can be difficult (even impossible) to select from individual surveys. We use the new platform ESA Datalabs to assemble a catalog of interacting galaxies from the Hubble Space Telescope science archives; this catalog is larger than previously published catalogs by nearly an order of magnitude. In particular, we apply the Zoobot convolutional neural network directly to the entire public archive of HST F814W images and make probabilistic interaction predictions for 126 million sources from the Hubble Source Catalog. We employ a combination of automated visual representation and visual analysis to identify a clean sample of 21,926 interacting galaxy systems, mostly with z < 1. Sixty-five percent of these systems have no previous references in either the NASA Extragalactic Database or Simbad. In the process of removing contamination, we also discover many other objects of interest, such as gravitational lenses, edge-on protoplanetary disks, and “backlit” overlapping galaxies. We briefly investigate the basic properties of this sample, and we make our catalog publicly available for use by the community. In addition to providing a new catalog of scientifically interesting objects imaged by HST, this work also demonstrates the power of the ESA Datalabs tool to facilitate substantial archival analysis without placing a high computational or storage burden on the end user. 

Abstract We present a new parametric lens model for the G165.7+67.0 galaxy cluster, which was discovered with Planck through its bright submillimeter flux, originating from a pair of extraordinary dusty star-forming galaxies (DSFGs) atz≈ 2.2. Using JWST and interferometric mm/radio observations, we characterize the intrinsic physical properties of the DSFGs, which are separated by only ∼1″ (8 kpc) and a velocity difference ΔV≲ 600 km s⁻¹in the source plane, and thus are likely undergoing a major merger. Boasting intrinsic star formation rates SFR_IR= 320 ± 70 and 400 ± 80M_⊙yr⁻¹, stellar masses of $\log \left[M_{\star }/M_{\odot }\right]=10.2\pm 0.1$and 10.3 ± 0.1, and dust attenuations ofA_V= 1.5 ± 0.3 and 1.2 ± 0.3, they are remarkably similar objects. We perform spatially resolved pixel-by-pixel spectral energy distribution (SED) fitting using rest-frame near-UV to near-IR imaging from JWST/NIRCam for both galaxies, resolving some stellar structures down to 100 pc scales. Based on their resolved specific star formation rates (SFRs) andUVJcolors, both DSFGs are experiencing significant galaxy-scale star formation events. If they are indeed interacting gravitationally, this strong starburst could be the hallmark of gas that has been disrupted by an initial close passage. In contrast, the host galaxy of SN H0pe has a much lower SFR than the DSFGs, and we present evidence for the onset of inside-out quenching and large column densities of dust even in regions of low specific SFR. Based on the intrinsic SFRs of the DSFGs inferred from UV through far-infrared SED modeling, this pair of objects alone is predicted to yield an observable 1.1 ± 0.2 core-collapse supernovae per year, making this cluster field ripe for continued monitoring. 

Abstract We describe the Gems of the Galaxy Zoos (Zoo Gems) project, a gap-filler project using short windows in the Hubble Space Telescope's schedule. As with previous snapshot programs, targets are taken from a pool based on position; we combine objects selected by volunteers in both the Galaxy Zoo and Radio Galaxy Zoo citizen-science projects. Zoo Gems uses exposures with the Advanced Camera for Surveys to address a broad range of topics in galaxy morphology, interstellar-medium content, host galaxies of active galactic nuclei, and galaxy evolution. Science cases include studying galaxy interactions, backlit dust in galaxies, post-starburst systems, rings and peculiar spiral patterns, outliers from the usual color–morphology relation, Green Pea compact starburst systems, double radio sources with spiral host galaxies, and extended emission-line regions around active galactic nuclei. For many of these science categories, final selection of targets from a larger list used public input via a voting process. Highlights to date include the prevalence of tightly wound spiral structure in blue, apparently early-type galaxies, a nearly complete Einstein ring from a group lens, redder components at lower surface brightness surrounding compact Green Pea starbursts, and high-probability examples of spiral galaxies hosting large double radio sources. 

ABSTRACT Motivated by the discovery of large ionized clouds around AGN, and particularly the large fraction of those that are consistent with photoionized gaseous tidal debris, we searched for [O iii] emission around Seyfert galaxies previously mapped in H i, many with extended gas features. Of 26 Seyfert galaxies, we find one spatially extended emission feature, a discrete cloud projected ≈12 kpc SW from the centre of Mkn 1 and spanning a transverse extent of 8 kpc. Optical spectroscopy (Kast/Lick and SCORPIO/BTA) of this cloud confirms its association with the Mkn 1–NGC 451 galaxy pair, closely matching the kinematics of nearby H i structures, and reveals emission-line ratios requiring photoionization by the AGN at roughly the direct observed luminosity of the nucleus. For the entire sample, the full opening angle of the ionization cones (bicones) must be <20° if the AGNs are continuously bright for scales longer than the light-traveltimes to the H i structures. Since typical AGN ionization cones are observed to be much broader than this, our low detection fraction may add to evidence for the ubiquity of strong variations in AGN luminosity on scales 104–105 yr. 

ABSTRACT We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r = 23.6 versus r = 22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314 000 galaxies. 140 000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314 000 galaxies. We use active learning to focus our volunteer effort on the galaxies which, if labelled, would be most informative for training our ensemble. When measured against confident volunteer classifications, the trained networks are approximately 99 per cent accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve. 

Abstract We derive the spatial and wavelength behavior of dust attenuation in the multiple-armed spiral galaxy VV 191b using backlighting by the superimposed elliptical system VV 191a in a pair with an exceptionally favorable geometry for this measurement. Imaging using the James Webb Space Telescope and Hubble Space Telescope spans the wavelength range 0.3–4.5μm with high angular resolution, tracing the dust in detail from 0.6–1.5μm. Distinct dust lanes continue well beyond the bright spiral arms, and trace a complex web, with a very sharp radial cutoff near 1.7 Petrosian radii. We present attenuation profiles and coverage statistics in each band at radii 14–21 kpc. We derive the attenuation law with wavelength; the data both within and between the dust lanes clearly favor a stronger reddening behavior (R=A_V/E_B−V≈ 2.0 between 0.6 and 0.9μm, approaching unity by 1.5μm) than found for starbursts and star-forming regions of galaxies. Power-law extinction behavior ∝λ^−βgivesβ= 2.1 from 0.6–0.9μm.Rdecreases at increasing wavelengths (R≈ 1.1 between 0.9 and 1.5μm), whileβsteepens to 2.5. Mixing regions of different column density flattens the wavelength behavior, so these results suggest a different grain population than in our vicinity. The NIRCam images reveal a lens arc and counterimage from a background galaxy atz≈ 1, spanning 90° azimuthally at 2.″8 from the foreground elliptical-galaxy nucleus, and an additional weakly lensed galaxy. The lens model and imaging data give a mass/light ratioM/L_B= 7.6 in solar units within the Einstein radius 2.0 kpc.