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We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer votes. Our models typically predict the fraction of volunteers selecting each answer to within 5–10 per cent for every answer to every GZ question. The models are trained on newly collected votes for DESI-LS DR8 images as well as historical votes from GZ DECaLS. We also release the newly collected votes. Extending our morphology measurements outside of the previously released DECaLS/SDSS intersection increases our sky coverage by a factor of 4 (5000–19 000 deg2) and allows for full overlap with complementary surveys including ALFALFA and MaNGA.

 

Post-starburst galaxies (PSBs) are transition galaxies showing evidence of recent rapid star formation quenching. To understand the role of galaxy mergers in triggering quenching, we investigate the incidence of PSBs and resolved PSB properties in post-merger galaxies using both SDSS single-fibre spectra and MaNGA resolved IFU spectra. We find post-mergers have a PSB excess of 10–20 times that relative to their control galaxies using single-fibre PSB diagnostics. A similar excess of ∼ 19 times is also found in the fraction of central (C)PSBs and ring-like (R)PSBs in post-mergers using the resolved PSB diagnostic. However, 60 per cent of the CPSBs + RPSBs in both post-mergers and control galaxies are missed by the single-fibre data. By visually inspecting the resolved PSB distribution, we find that the fraction of outside-in quenching is seven times higher than inside-out quenching in PSBs in post-mergers while PSBs in control galaxies do not show large differences in these quenching directions. In addition, we find a marginal deficit of H i gas in PSBs relative to non-PSBs in post-mergers using the MaNGA-H i data. The excesses of PSBs in post-mergers suggest that mergers play an important role in triggering quenching. Resolved IFU spectra are important to recover the PSBs missed by single-fibre spectra. The excess of outside-in quenching relative to inside-out quenching in post-mergers suggests that AGNs are not the dominant quenching mechanism in these galaxies, but that processes from the disc (gas inflows/consumption and stellar feedback) play a more important role.

 

ABSTRACT We study the bar pattern speeds and corotation radii of 225 barred galaxies, using integral field unit data from MaNGA and the Tremaine–Weinberg method. Our sample, which is divided between strongly and weakly barred galaxies identified via Galaxy Zoo, is the largest that this method has been applied to. We find lower pattern speeds for strongly barred galaxies than for weakly barred galaxies. As simulations show that the pattern speed decreases as the bar exchanges angular momentum with its host, these results suggest that strong bars are more evolved than weak bars. Interestingly, the corotation radius is not different between weakly and strongly barred galaxies, despite being proportional to bar length. We also find that the corotation radius is significantly different between quenching and star-forming galaxies. Additionally, we find that strongly barred galaxies have significantly lower values for $\mathcal {R}$, the ratio between the corotation radius and the bar radius, than weakly barred galaxies, despite a big overlap in both distributions. This ratio classifies bars into ultrafast bars ($\mathcal {R} \lt $ 1.0; 11 per cent of our sample), fast bars (1.0 $\lt \mathcal {R} \lt $ 1.4; 27 per cent), and slow bars ($\mathcal {R} \gt $ 1.4; 62 per cent). Simulations show that $\mathcal {R}$ is correlated with the bar formation mechanism, so our results suggest that strong bars are more likely to be formed by different mechanisms than weak bars. Finally, we find a lower fraction of ultrafast bars than most other studies, which decreases the recently claimed tension with Lambda cold dark matter. However, the median value of $\mathcal {R}$ is still lower than what is predicted by simulations. 

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. 

Red geysers are a specific type of quiescent galaxy, denoted by twin jets emerging from their galactic centres. These bisymmetric jets possibly inject energy and heat into the surrounding material, effectively suppressing star formation by stabilizing cool gas. In order to confirm the presence and evolutionary consequences of these jets, this paper discusses the scaling, stacking, and conversion of 21-cm H i flux data sourced from the H i-MaNGA survey into H i gas-to-stellar mass (G/S) spectra. Our samples were dominated by non-detections, or galaxies with weak H i signals, and consequently by H i upper limits. The stacking technique discussed successfully resolved emission features in both the red geyser G/S spectrum and the control sample G/S spectrum. From these stacked spectra, we find that on average, red geyser galaxies have G/S of 0.086 ± 0.011 (random) + 0.029 (systematic), while non-red geyser galaxies of similar stellar mass have a G/S ratio of 0.039 ± 0.018 (random) + 0.013 (systematic). Therefore, we find no statistically significant evidence that the H i content of red geysers is different from the general quiescent population.

 

We investigate the role of galaxy mergers in triggering active galactic nuclei (AGN) in the nearby universe. Our analysis is based on a sample of 79 post-merger remnant galaxies with deep X-ray observations from Chandra/XMM-Newton capable of detecting a low-luminosity AGN of ≥10^40.5erg s⁻¹. This sample is derived from a visually classified, volume-limited sample of 807 post-mergers identified in the Sloan Digital Sky Survey Data Release 14 with logM_*/M_⊙≥ 10.5 and 0.02 ≤z≤ 0.06. We find that the X-ray AGN fraction in this sample is 55.7% ± 5.6% compared to 23.6% ± 2.8% for a mass- and redshift-matched noninteracting control sample. The multiwavelength AGN fraction (identified as an AGN in one of X-ray, IR, radio or optical diagnostics) for post-mergers is 76.6% ± 4.8% compared to 39.1% ± 3.2% for controls. Thus post-mergers exhibit a high overall AGN fraction with an excess between 2 and 4 depending on the AGN diagnostics used. In addition, we find most optical, IR, and radio AGN are also identified as X-ray AGN while a large fraction of X-ray AGN are not identified in any other diagnostic. This highlights the importance of deep X-ray imaging to identify AGN. We find that the X-ray AGN fraction of post-mergers is independent of the stellar mass above logM_*/M_⊙≥ 10.5 unlike the trend seen in control galaxies. Overall, our results show that post-merger galaxies are a good tracer of the merger–AGN connection and strongly support the theoretical expectations that mergers trigger AGN.

 

ABSTRACT Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning. 

The Sloan Digital Sky Survey MaNGA program has now obtained integral field spectroscopy for over 10,000 galaxies in the nearby universe. We use the final MaNGA data release DR17 to study the correlation between ionized gas velocity dispersion and galactic star formation rate, finding a tight correlation in whichσ_Hαfrom galactic Hiiregions increases significantly from ∼18–30 km s⁻¹, broadly in keeping with previous studies. In contrast,σ_Hαfrom diffuse ionized gas increases more rapidly from 20–60 km s⁻¹. Using the statistical power of MaNGA, we investigate these correlations in greater detail using multiple emission lines and determine that the observed correlation ofσ_Hαwith local star formation rate surface density is driven primarily by the global relation of increasing velocity dispersion at higher total star formation rate, as are apparent correlations with stellar mass. Assuming Hiiregion models consistent with our finding thatσ_[OIII]<σ_Hα<σ_{[O I]}, we estimate the velocity dispersion of the molecular gas in which the individual Hiiregions are embedded, finding valuesσ_Mol= 5–30 km s⁻¹consistent with ALMA observations in a similar mass range. Finally, we use variations in the relation with inclination and disk azimuthal angle to constrain the velocity dispersion ellipsoid of the ionized gasσ_z/σ_r= 0.84 ± 0.03 andσ_ϕ/σ_r= 0.91 ± 0.03, similar to that of young stars in the Galactic disk. Our results are most consistent with the theoretical models in which turbulence in modern galactic disks is driven primarily by star formation feedback.

 

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 We present 150 MHz, 1.4 GHz, and 3 GHz radio imaging (LoTSS, FIRST, and VLASS) and spatially resolved ionized gas characteristics (SDSS IV-MaNGA) for 140 local ( z < 0.1) early-type red geyser galaxies. These galaxies have a low star formation activity (with a star formation rate, SFR, ∼ 0.01 M ⊙ yr −1 ), but show unique extended patterns in spatially resolved emission-line maps that have been interpreted as large-scale ionized winds driven by active galactic nuclei (AGN). In this work, we confirm that red geysers host low-luminosity radio sources ( L 1.4GHz ∼ 10 22 WHz −1 ). Out of 42 radio-detected red geysers, 32 are spatially resolved in LoTSS and FIRST, with radio sizes varying between ∼5–25 kpc. Three sources have radio sizes exceeding 40 kpc. A majority display a compact radio morphology and are consistent with either low-power compact radio sources (FR0 galaxies) or radio-quiet quasars. They may be powered by small-scale AGN-driven jets that remain unresolved at the current 5″ resolution of radio data. The extended radio sources, not belonging to the “compact” morphological class, exhibit steeper spectra with a median spectral index of −0.67, indicating the dominance of lobed components. The red geysers hosting extended radio sources also have the lowest specific SFRs, suggesting they either have a greater impact on the surrounding interstellar medium or are found in more massive halos on average. The degree of alignment of the ionized wind cone and the extended radio features are either 0° or 90°, indicating possible interaction between the interstellar medium and the central radio AGN.