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Masters, Karen L.

Publications and source records attributed to Masters, Karen L..

The most luminous, merger-free AGNs show only marginal correlation with bar presence

The role of large-scale bars in the fuelling of active galactic nuclei (AGNs) is still debated, even as evidence mounts that black hole growth in the absence of galaxy mergers cumulatively dominates and may substantially influence disc (i.e. merger-free) galaxy evolution. We investigate whether large-scale galactic bars are a good candidate for merger-free AGN fuelling. Specifically, we combine slit spectroscopy and Hubble Space Telescope imagery to characterize star formation rates (SFRs) and stellar masses of the unambiguously disc-dominated host galaxies of a sample of luminous, Type-1 AGN with 0.02 < z < 0.24. After carefully correcting for AGN signal, we find no clear difference in SFRs between AGN hosts and a stellar mass-matched sample of galaxies lacking an AGN (0.013 < z < 0.19), although this could be due to small sample size (nAGN = 34). We correct for SFR and stellar mass to minimize selection biases, and compare the bar fraction in the two samples. We find that AGNs are marginally (~1.7σ) more likely to host a bar than inactive galaxies, with AGN hosts having a bar fraction, $f_{\mathrm{bar}}=0.59^{+0.08}_{-0.09}$ and inactive galaxies having a bar fraction, $f_{\mathrm{bar}}=0.44^{+0.08}_{-0.09}$. However, we find no further differences between SFR- and mass-matched AGNs and inactive samples. While bars could potentially trigger AGN activity, they appear to have no further, unique effect on a galaxy’s stellar mass or SFR.

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A comparison of the baryonic Tully–Fisher relation in MaNGA and IllustrisTNG

We compare an observed baryonic Tully–Fisher relation (BTFR) from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) and HI-MaNGA surveys to a simulated BTFR from the cosmological magnetohydrodynamical simulation, IllustrisTNG. To do so, we calibrate the BTFR of the local universe using 377 galaxies from the MaNGA and HI-MaNGA surveys, and perform mock 21 cm observations of matching galaxies from IllustrisTNG. The mock observations are used to ensure that the comparison with the observed galaxies is fair since it has identical measurement algorithms, observational limitations, biases, and uncertainties. For comparison, we also calculate the BTFR for the simulation without mock observations and demonstrate how mock observations are necessary to fairly and consistently compare between observational and theoretical data. We report a MaNGA BTFR of log$_{10} (M_{ \rm Bary}/M_\odot)= (2.97 \pm 0.18)$ log$_{10} V_{ \rm Rot} + (4.04 \pm 0.41)\, \log _{10}{M_{\odot }}$ and an IllustrisTNG BTFR of log$_{10} (M_{ \rm Bary}/M_\odot) = (2.94 \pm 0.23$) log$_{10} V_{ \rm Rot} + (4.15 \pm 0.44)\, \log _{10}{M_{\odot }}$. Thus, MaNGA and IllustrisTNG produce BTFRs that agree within uncertainties, demonstrating that IllustrisTNG has created a galaxy population that obeys the observed relationship between mass and rotation velocity in the observed universe.

79 ASTRONOMY AND ASTROPHYSICS↗

The Velocity Map Asymmetry of Ionized Gas in MaNGA. I. The Catalog and General Properties

The SDSS-IV MaNGA survey has measured two-dimensional maps of emission-line velocities for a statistically powerful sample of nearby galaxies. The asymmetric features of these kinematics maps reflect the nonrotational component of a galaxy’s internal motion of ionized gas. In this study, we present a catalog of kinematic asymmetry measurements of the H α velocity map of a sample of 5353 MaNGA galaxies. Based on this catalog, we find that “special” galaxies (e.g., merging galaxies, barred galaxies, and active galactic nucleus host galaxies) contain more galaxies with highly asymmetric velocity maps. However, we notice that more than half of galaxies with high kinematic asymmetry in our sample are quite “regular.” For those “regular” galaxies, kinematic asymmetry shows a significant anticorrelation with stellar mass at log M * < 9.7 , while such a trend becomes very weak at log M * > 9.7 . Moreover, at a given stellar mass, the kinematic asymmetry shows weak correlations with photometric morphology, star formation rate, and environment, while it is independent of H i gas content. We also have quantified the observational effects in the kinematic asymmetry measurement. We find that both the signal-to-noise ratio of H α flux and disk inclination angle contribute to the measures of kinematic asymmetry, while the physical spatial resolution is an irrelevant factor inside the MaNGA redshift coverage.

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SDSS-IV MaNGA: How the Stellar Populations of Passive Central Galaxies Depend on Stellar and Halo Mass

We analyze spatially resolved and co-added SDSS-IV MaNGA spectra with signal-to-noise ratio ~100 from 2200 passive central galaxies (z ~ 0.05) to understand how central galaxy assembly depends on stellar mass (M*) and halo mass (M h ). We control for systematic errors in M h by employing a new group catalog from Tinker and the widely used Yang et al. catalog. At fixed M*, the strengths of several stellar absorption features vary systematically with M h . Completely model-free, this is one of the first indications that the stellar populations of centrals with identical M* are affected by the properties of their host halos. To interpret these variations, we applied full spectral fitting with the code alf. At fixed M*, centrals in more massive halos are older, show lower [Fe/H], and have higher [Mg/Fe] with 3.5σ confidence. We conclude that halos not only dictate how much M* galaxies assemble but also modulate their chemical enrichment histories. Turning to our analysis at fixed M h , high-M* centrals are older, show lower [Fe/H], and have higher [Mg/Fe] for M h > 10 12 h –1 M⊙ with confidence >4σ. While massive passive galaxies are thought to form early and rapidly, our results are among the first to distinguish these trends at fixed M h . They suggest that high-M* centrals experienced unique early formation histories, either through enhanced collapse and gas fueling or because their halos were early forming and highly concentrated, a possible signal of galaxy assembly bias.

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Photometric Signature of Ultraharmonic Resonances in Barred Galaxies

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-resolution N-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.

79 ASTRONOMY AND ASTROPHYSICS↗

SDSS-IV MaNGA: Understanding Ionized Gas Turbulence Using Integral Field Spectroscopy of 4500 Star-forming Disk Galaxies

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 which σ Hα from galactic H ιι regions increases significantly from ~18–30 km s –1 , broadly in keeping with previous studies. In contrast, σ Hα from 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 of σ Hα with 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 H ιι region models consistent with our finding that σ [O III] < σ Hα < σ [O I] , we estimate the velocity dispersion of the molecular gas in which the individual H ιι regions are embedded, finding values σ Mol = 5–30 km s –1 consistent 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 gas σ z /σ r = 0.84 ± 0.03 and σ 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.

79 ASTRONOMY AND ASTROPHYSICS↗

Gems of the Galaxy Zoos—A Wide-ranging Hubble Space Telescope Gap-filler Program*

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.

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Practical galaxy morphology tools from deep supervised representation learning

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.

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Quantifying the poor purity and completeness of morphological samples selected by galaxy colour

The galaxy population is strongly bimodal in both colour and morphology, and the two measures correlate strongly, with most blue galaxies being late-types (spirals) and most early-types, typically ellipticals, being red. This observation has led to the use of colour as a convenient selection criterion to make samples that are then labelled by morphology. Such use of colour as a proxy for morphology results in necessarily impure and incomplete samples. In this paper, we make use of the morphological labels produced by Galaxy Zoo to measure how incomplete and impure such samples are, considering optical (ugriz), near-ultraviolet (NUV), and near-infrared (NIR; JHK) bands. The best single colour optical selection is found using a threshold of g - r = 0.742, but this still results in a sample where only 56 per cent of red galaxies are smooth and 56 per cent of smooth galaxies are red. Use of the NUV gives some improvement over purely optical bands, particularly for late-types, but still results in low purity/completeness for early-types. No significant improvement is found by adding NIR bands. With any two bands, including NUV, a sample of early-types with greater than two-thirds purity cannot be constructed. In conclusion, advances in quantitative galaxy morphologies have made colour–morphology proxy selections largely unnecessary going forward; where such assumptions are still required, we recommend studies carefully consider the implications of sample incompleteness/impurity.

79 ASTRONOMY AND ASTROPHYSICS↗

Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314,000 galaxies

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.

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Galaxy zoo: stronger bars facilitate quenching in star-forming galaxies

ABSTRACT We have used Galaxy Zoo DECaLS (GZD) to study strong and weak bars in disc galaxies. Out of the 314 000 galaxies in GZD, we created a volume-limited sample (0.01 < z < 0.05, Mr < − 18.96) which contains 1867 galaxies with reliable volunteer bar classifications in the ALFALFA footprint. In keeping with previous Galaxy Zoo surveys (such as GZ2), the morphological classifications from GZD agree well with previous morphological surveys. GZD considers galaxies to either have a strong bar (15.5 per cent), a weak bar (28.1 per cent) or no bar (56.4 per cent), based on volunteer classifications on images obtained from the DECaLS survey. This places GZD in a unique position to assess differences between strong and weak bars. We find that the strong bar fraction is typically higher in quiescent galaxies than in star-forming galaxies, while the weak bar fraction is similar. Moreover, we have found that strong bars facilitate the quenching process in star-forming galaxies, finding higher fibre star formation rates (SFRs), lower gas masses, and shorter depletion time-scales in these galaxies compared to unbarred galaxies. However, we also found that any differences between strong and weak bars disappear when controlling for bar length. Based on this, we conclude that weak and strong bars are not fundamentally different phenomena. Instead, we propose that there is a continuum of bar types, which varies from ‘weakest’ to ‘strongest’.

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