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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.

 

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. 

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. 

The spatial distribution of mono-abundance populations (MAPs, selected in [Fe/H] and [Mg/Fe]) reflect the chemical and structural evolution in a galaxy and impose strong constraints on galaxy formation models. In this paper, we use APOGEE data to derive the intrinsic density distribution of MAPs in the Milky Way, after carefully considering the survey selection function. We find that a single exponential profile is not a sufficient description of the Milky Way’s disc. Both the individual MAPs and the integrated disc exhibit a broken radial density distribution; densities are relatively constant with radius in the inner Galaxy and rapidly decrease beyond the break radius. We fit the intrinsic density distribution as a function of radius and vertical height with a 2D density model that considers both a broken radial profile and radial variation of scale height (i.e. flaring). There is a large variety of structural parameters between different MAPs, indicative of strong structure evolution of the Milky Way. One surprising result is that high-α MAPs show the strongest flaring. The young, solar-abundance MAPs present the shortest scale height and least flaring, suggesting recent and ongoing star formation confined to the disc plane. Finally we derive the intrinsic density distribution and corresponding structural parameters of the chemically defined thin and thick discs. The chemical thick and thin discs have local surface mass densities of 5.62 ± 0.08 and 15.69 ± 0.32 M⊙pc−2, respectively, suggesting a massive thick disc with a local surface mass density ratio between thick to thin disc of 36 per cent.

 

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. 

Bars may induce morphological features, such as rings, through their resonances. Previous studies suggested that the presence of “dark gaps,” or regions of a galaxy where the difference between the surface brightness along the bar major axis and that along the bar minor axis is maximal, can be attributed to the location of bar corotation. Here, using GALAKOS, a high-resolutionN-body simulation of a barred galaxy, we test this photometric method’s ability to identify the bar corotation resonance. Contrary to previous work, our results indicate that “dark gaps” are a clear sign of the location of the 4:1 ultraharmonic resonance instead of bar corotation. Measurements of the bar corotation can indirectly be inferred using kinematic information, e.g., by measuring the shape of the rotation curve. We demonstrate our concept on a sample of 578 face-on barred galaxies with both imaging and integral field observations and find that the sample likely consists primarily of fast bars.

 

ABSTRACT We present the second data release for the H i-MaNGA programme of H i follow-up observations for the SDSS-IV MaNGA survey. This release contains measurements for 3669 unique galaxies, combining 2108 Green Bank Telescope observations with an updated crossmatch of the MaNGA sample with the ALFALFA survey. We combine these data with MaNGA spectroscopic measurements to examine relationships between H i-to-stellar mass ratio (${\rm M_{H\, {\small I}}/{M_*}}$) and average ISM/star formation properties probed by optical emission lines. ${\rm M_{H\, {\small I}}/{M_*}}$ is very weakly correlated with the equivalent width of H α, implying a loose connection between the instantaneous star formation rate and the H i reservoir, although the link between ${\rm M_{H\, {\small I}}/{M_*}}$ and star formation strengthens when averaged even over only moderate time-scales (∼30 Myr). Galaxies with elevated H i depletion times have enhanced [O i]/H α and depressed H α surface brightness, consistent with more H i residing in a diffuse and/or shock-heated phase that is less capable of condensing into molecular clouds. Of all optical lines, ${\rm M_{H\, {\small I}}/{M_*}}$ correlates most strongly with oxygen equivalent width, EW(O), which is likely a result of the existing correlation between ${\rm M_{H\, {\small I}}/{M_*}}$ and gas-phase metallicity. Residuals in the ${\rm M_{H\, {\small I}}/{M_*}}$−EW(O) relation are again correlated with [O i]/H α and H α surface brightness, suggesting they are also driven by variations in the fraction of diffuse and/or shock-heated gas. We recover the strong anticorrelation between ${\rm M_{H\, {\small I}}/{M_*}}$ and gas-phase metallicity seen in previous studies. We also find a relationship between ${\rm M_{H\, {\small I}}/{M_*}}$ and [O i]6302/H α, suggesting that higher fractions of diffuse and/or shock-heated gas are more prevalent in gas-rich galaxies.