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At the peak of cosmic star formation (1 ≲ z ≲ 2), the majority of star-forming galaxies hosted compact, star-forming clumps, which were responsible for a large fraction of cosmic star formation. By comparison, ≲5% of local star-forming galaxies host comparable clumps. In this work, we investigate the link between the environmental conditions surrounding local ( z < 0.04) galaxies and the prevalence of clumps in these galaxies. To obtain our clump sample, we use a Faster R-CNN object detection network trained on the catalog of clump labels provided by the Galaxy Zoo: Clump Scout project, then apply this network to detect clumps in approximately 240,000 Sloan Digital Sky Survey galaxies (originally selected for Galaxy Zoo 2). The resulting sample of 41,445 u -band bright clumps in 34,246 galaxies is the largest sample of clumps yet assembled. We then select a volume-limited sample of 9964 galaxies and estimate the density of their local environment using the distance to their projected fifth nearest neighbor. We find a robust correlation between environment and the clumpy fraction ( f _clumpy ) for star-forming galaxies (specific star formation rate, sSFR > 10 ^−2 Gyr ^−1 ) but find little to no relationship when controlling for galaxies’ sSFR or color. Further, f _clumpy increases significantly with sSFR in local galaxies, particularly above sSFR > 10 ^−1 Gyr ^−1 . We posit that a galaxy’s gas fraction primarily controls the formation and lifetime of its clumps, and that environmental interactions play a smaller role.

Citizen science has become a valuable and reliable method for interpreting and processing big datasets, and is vital in the era of ever-growing data volumes. However, there are inherent difficulties in the generating labels from citizen scientists, due to the inherent variability between the members of the crowd, leading to variability in the results. Sometimes, this is useful — such as with serendipitous discoveries, which corresponds to rare/unknown classes in the data — but it might also be due to ambiguity between classes. The primary issue is then to distinguish between the intrinsic variability in the dataset and the uncertainty in the citizen scientists’ responses, and leveraging that to extract scientifically useful relationships. In this paper, we explore using a neural network to interpret volunteer confusion across the dataset, to increase the purity of the downstream analysis. We focus on the use of learned features from the network to disentangle feature similarity across the classes, and the ability of the machines’ “attention” in identifying features that lead to confusion. We use data from Jovian Vortex Hunter, a citizen science project to study vortices in Jupiter’s atmosphere, and find that the latent space from the model helps effectively identify different sources of image-level features that lead to low volunteer consensus. Furthermore, the machine’s attention highlights features corresponding to specific classes. This provides meaningful image-level feature-class relationships, which is useful in our analysis for identifying vortex-specific features to better understand vortex evolution mechanisms. Finally, we discuss the applicability of this method to other citizen science projects.

The Jovian atmosphere contains a wide diversity of vortices, which have a large range of sizes, colors, and forms in different dynamical regimes. The formation processes for these vortices are poorly understood, and aside from a few known, long-lived ovals, such as the Great Red Spot and Oval BA, vortex stability and their temporal evolution are currently largely unknown. In this study, we use JunoCam data and a citizen science project on Zooniverse to derive a catalog of vortices, some with repeated observations, from 2018 May to 2021 September, and we analyze their associated properties, such as size, location, and color. We find that different-colored vortices (binned as white, red, brown, and dark) follow vastly different distributions in terms of their sizes and where they are found on the planet. We employ a simplified stability criterion using these vortices as a proxy, to derive a minimum Rossby deformation length for the planet of ∼1800 km. We find that this value of L _d is largely constant throughout the atmosphere and does not have an appreciable meridional gradient.

The UltraViolet imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) program provides Hubble Space Telescope (HST)/UVIS F275W imaging for four CANDELS fields. We combine this UV imaging with existing HST/near-IR grism spectroscopy from 3D-HST+AGHAST to directly compare the resolved rest-frame UV and H α emission for a sample of 979 galaxies at 0.7 < z < 1.5, spanning a range in stellar mass of 10 ^8−11.5 M _⊙ . Using a stacking analysis, we perform a resolved comparison between homogenized maps of rest-UV and H α to compute the average UV-to-H α luminosity ratio (an indicator of burstiness in star formation) as a function of galactocentric radius. We find that galaxies below stellar mass of ∼10 ^9.5 M _⊙ , at all radii, have a UV-to-H α ratio higher than the equilibrium value expected from constant star formation, indicating a significant contribution from bursty star formation. Even for galaxies with stellar mass ≳10 ^9.5 M _⊙ , the UV-to-H α ratio is elevated toward their outskirts ( R / R _eff > 1.5), suggesting that bursty star formation is likely prevalent in the outskirts of even the most massive galaxies, but is likely overshadowed by their brighter cores. Furthermore, we present the UV-to-H α ratio as a function of galaxy surface brightness, a proxy for stellar mass surface density, and find that regions below ∼10 ^7.5 M _⊙ kpc ^−2 are consistent with bursty star formation, regardless of their galaxy stellar mass, potentially suggesting that local star formation is independent of global galaxy properties at the smallest scales. Last, we find galaxies at z > 1.1 to have bursty star formation, regardless of radius or surface brightness.

We explore how the fraction of quenched galaxies changes in groups of galaxies with respect to the distance to the center of the group, redshift, and stellar mass to determine the dominant process of environmental quenching in 0.2 < z < 0.8 groups. We use new UV data from the UVCANDELS project in addition to existing multiband photometry to derive new galaxy physical properties of the group galaxies from the zCOSMOS 20 k group catalog. Limiting our analysis to a complete sample of log ( M _* / M _⊙ ) > 10.56 group galaxies, we find that the probability of being quenched increases slowly with decreasing redshift, diverging from the stagnant field galaxy population. A corresponding analysis on how the probability of being quenched increases with time within groups suggests that the dominant environmental quenching process is characterized by slow (∼Gyr) timescales. We find a quenching time of approximately ${4.91}_{-1.47}^{+0.91}$ Gyr, consistent with the slow processes of strangulation and delayed-then-rapid quenching although more data are needed to confirm this result.