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Brooke D. Simmons

Publications and source records attributed to Brooke D. Simmons.

At least 19 recordsLinked to original sources

Galaxy-SMBH co-evolution in 2,435 DESI disk galaxies and merger-free BH growth in bulgeless disks

We analyse black hole scaling relations for disk-dominated galaxies, and present evidence for secularly driven galaxy-black hole co-evolution. We do this observationally by looking at ``bulgeless'' galaxies, where the lack of a stellar bulge suggests a quiet merger history. We first compose a sample of 2,435 disk-dominated galaxies hosting optical broad line active galactic nuclei (AGN) from DESI data, and find a $M_{\mathrm{BH}}$--$M_{*}$ scaling relation of $\log(M_{\mathrm{BH}})= - 3.7^{+0.3}_{-0.3} + 1.00^{+0.03}_{-0.03} \log(M_*)$. From these, we identify 546 bulgeless galaxies hosting AGN, a factor of $\gtrsim 5$ larger than pre-existing samples, and find they follow the same $M_{\mathrm{BH}}$--$M_{*}$ relation as the general disk galaxy sample. Comparing the bulgeless galaxies to those with some bulge component, we find good agreement in the $M_{\mathrm{BH}}$--$M_{*}$ relation (within $3 σ$), but disagreement in the $M_{\mathrm{BH}}$--$M_{*, \mathrm{bulge}}$ relation (at $>7 σ$). This is the opposite of what is expected from merger-driven co-evolution, suggesting secular growth is significant in establishing observed $M_{\mathrm{BH}}$--$M_{*}$ scaling relations. Furthermore, in a control sample of early-type galaxies we find tentative evidence of increased AGN luminosity compared to the bulgeless sample, but no statistical difference in black hole mass. This suggests the assumed merger-dominated evolutionary history of early-type galaxies does not lead to significantly increased long-term BH growth. These results support numerous recent observational and theoretical studies which suggest secular processes fuel significant supermassive black hole growth and galaxy-black hole co-evolution.

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Star-forming clump detection in nearby galaxies using Faster R-CNN and $ugrizy$ imaging data from CLAUDS and HSC-SSP

Giant Star-forming Clumps (GSFCs) are kpc-scale regions of enhanced star-formation with stellar masses of $10^7$ to $10^9\,M_\odot$ that are commonly observed in high-redshift galaxies but are rarely detected in low-redshift ($z\lesssim0.5$) galaxy analogues. However, the availability of wide-field galaxy survey data makes it possible to identify potential star-forming clumps in large samples of low-redshift galaxies using object detection models that are based on Deep Learning (DL) techniques. We apply a novel DL-based object detection model to galaxies observed by the Hyper Suprime-Cam Subaru Strategic Survey (HSC-SSP) and CFHT Large Area U-band Deep Survey (CLAUDS). Our model is based on the the Faster Region-Based Convolutional Neural Network (Faster R-CNN or FRCNN) object detection framework but expanded to process the six $ugrizy$ filter band images simultaneously and identify not only clumps and their locations in the host galaxy but also additional contaminants. By adopting the \textsc{Zoobot} foundation DL-model as a feature extraction backbone, we also demonstrate one of the first applications of \textsc{Zoobot} in a downstream task for object detection. Our model achieves a detection completeness of $\gtrsim 0.9$ and purity of $\gtrsim 0.8$ which were validated on a large set of real galaxies into which simulated clumps were injected.

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Galaxy Zoo Bar Lengths: A Catalogue of Measurements from Hubble Space Telescope Images and the Evolution of Galactic Bar Structure at z < 1

Understanding the role of galactic scale bars in disk galaxy evolution requires detailed measurements of bar properties across galaxies hosting bars at many redshifts. We present measurements of bar lengths and widths in a sample of 8230 disk galaxies from Hubble Space Telescope (HST) Legacy surveys. The highest-redshift barred galaxies in the sample have $z \sim 3$; most have $z \leq 1$. Using a mass-complete sample from the COSMOS field, we examine bar properties and evolution within $0.25 < z < 1$ in galaxies with stellar mass $\log(M_{\ast}/M_{\odot}) \geq 9.5$. The lowest-mass galaxies in our sample have similar star formation rate (SFR) distributions whether or not they host bars. For galaxies with $\log(M_{\ast}/M_{\odot}) \geq 10$, barred galaxies are more likely to be quiescent or quenched, consistent with bars mainly participating in slow quenching processes. The median physical bar length increases with increasing stellar mass. Relative bar lengths and widths (as a fraction of disk radius) peak at stellar mass $\log(M_{\ast}/M_{\odot}) \sim 10.25$, and change together with mass such that the median ratio, a proxy for bar strength, does not significantly change with stellar mass. Bars in our sample tend to be slightly ($\approx 13$%) weaker at higher redshift. Quiescent and quenching galaxies have longer and wider bars than those in galaxies on or above the star-forming sequence, especially at lower redshift and higher masses; at the low-mass end of our sample, starburst galaxies host relatively longer and stronger bars. Our findings are consistent with other results from studies at both higher and lower redshift, cementing the fundamental importance of bars in disk galaxy evolution.

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The complex relationships between AGN, bars and bulges

Context. Via scaling relations, it is well-known that active galactic nuclei (AGN) and bulges are linked. This link was thought to be driven by mergers, but recent studies show that secular processes are the dominant mechanism of supermassive black hole growth. One such secular mechanism is gas inflow driven by large-scale bars. Since bulges can also grow via these bars, there is likely some common process between these three features. Aims. We investigate whether the observed correlation between AGN and bars is real or arises as a result of correlations between bars and bulges. Methods. Using a catalogue of AGN identifications and galaxy morphologies in the DESI Legacy Survey at $z\leq0.1$, we control for mass and colour and investigate the AGN fraction variation with bulge prominence and bar strength. Results. We first show that the variation in AGN fraction between strongly barred, weakly barred and unbarred galaxies does not qualitatively change if we additionally control for bulge prominence. Second, we find that in fixed bins of bulge prominence, the AGN fraction increases with increasing bar strength. In subsamples split by bar strength, the AGN fraction increases with bulge prominence, indicating that AGN presence correlates with both bar strength and bulge prominence simultaneously.

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Here Be SDRAGNs - Spiral Galaxies Hosting Large Double Radio Sources

We present a sample of large double radio sources hosted by spiral galaxies (Spiral Double Radio Active Galactic Nuclei, SDRAGNs). Candidates were selected during Radio Galaxy Zoo, and refined using Sloan Digital Sky Survey images. The most promising were targeted in the Zoo Gems Hubble Space Telescope program, yielding images for 36 candidates. We assess the likelihood of each spiral galaxy being the genuine host of the radio emission finding 15 new high-probability SDRAGNs. SDRAGN hosts are seen preferentially close to edge-on. SDRAGNs predominantly show FR II radio structures and optical pseudobulges. Accounting for sample selection effects, the radio-jet axes lie preferentially near the poles of the galaxy disks; we find a constant probability distribution for intrinsic pole-jet angles < 30 degrees, ramping to zero at 60 degrees. We have obtained optical spectra for all these new SDRAGNs. Among both previous and new SDRAGN samples, 8/25 show Seyfert 2 signatures, 6/25 show central star formation, and 5/25 show LINER emission strong enough to indicate AGN or shock ionization, broadly similar to radio galaxies in elliptical hosts with the addition of star formation (diluting or masking weak AGN signatures). SDRAGNs include FR II sources seen at unusually low radio power, and preferentially occur in significant galaxy overdensities on 1-Mpc scales. Our "false alarms" - systems where HST data show the spiral to not be the actual host galaxy - include radio sources seen through large parts of foreground spiral disks, potentially useful for Faraday-rotation studies of disk magnetic fields.

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Galaxy Zoo: Cosmic Dawn -- morphological classifications for over 41,000 galaxies in the Euclid Deep Field North from the Hawaii Two-0 Cosmic Dawn survey

We present morphological classifications of over 41,000 galaxies out to $z_{\rm phot}\sim2.5$ across six square degrees of the Euclid Deep Field North (EDFN) from the Hawaii Twenty Square Degree (H20) survey, a part of the wider Cosmic Dawn survey. Galaxy Zoo citizen scientists play a crucial role in the examination of large astronomical data sets through crowdsourced data mining of extragalactic imaging. This iteration, Galaxy Zoo: Cosmic Dawn (GZCD), saw tens of thousands of volunteers and the deep learning foundation model Zoobot collectively classify objects in ultra-deep multiband Hyper Suprime-Cam (HSC) imaging down to a depth of $m_{HSC-i} = 21.5$. Here, we present the details and general analysis of this iteration, including the use of Zoobot in an active learning cycle to improve both model performance and volunteer experience, as well as the discovery of 51 new gravitational lenses in the EDFN. We also announce the public data release of the classifications for over 45,000 subjects, including more than 41,000 galaxies (median $z_{\rm phot}$ of $0.42\pm0.23$), along with their associated image cutouts. This data set provides a valuable opportunity for follow-up imaging of objects in the EDFN as well as acting as a truth set for training deep learning models for application to ground-based surveys like that of the Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) collaboration and the newly operational Vera C. Rubin Observatory.

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Strong Bars, Strong Inflow: The Effect of Bar Strength on Gas Inflow

Stellar bars are elongated structures in disk galaxies that can torque and funnel gas inward, influencing galaxy evolution. While strong bars are known to induce rapid inflow, the impact of weaker bars remains less certain. We collected spectroscopic data using the Isaac Newton Telescope to analyze 18 nearby galaxies (strongly barred, weakly barred, and unbarred) drawn from Galaxy Zoo DESI. We obtained spatial profiles of equivalent width (EW) and ionized gas velocity dispersion by fitting Gaussian profiles to the Hα emission line. Strongly barred galaxies exhibit a distinctive three-peaked EW[Hα] structure, consistent with inward funneling of gas. Weakly barred systems lack this pattern, which suggests limited inflow. Velocity dispersion distributions further distinguish the bar types, with strongly barred galaxies showing significantly higher values than weakly barred and unbarred systems. These results suggest that strong bars drive gas inflow, while weak bars exert a limited dynamical influence.

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The La Silla Schmidt Southern Survey

We present the La Silla Schmidt Southern Survey (LS4), a new wide-field, time-domain survey to be conducted with the 1 m ESO Schmidt telescope. The 268 megapixel LS4 camera mosaics 32 2k$\times$4k fully depleted CCDs, providing a $\sim$20 deg$^2$ field of view with $1''$ pixel$^{-1}$ resolution. The LS4 camera will have excellent performance at longer wavelengths: in a standard 45 s exposure the expected 5$σ$ limiting magnitudes in $g$, $i$, $z$ are $\sim$21.5, $\sim$20.9, and $\sim$20.3 mag (AB), respectively. The telescope design requires a novel filter holder that fixes different bandpasses over each quadrant of the detector. Two quadrants will have $i$ band, while the other two will be $g$ and $z$ band and color information will be obtained by dithering targets across the different quadrants. The majority (90%) of the observing time will be used to conduct a public survey that monitors the extragalactic sky at both moderate (3 d) and high (1 d) cadence, as well as focused observations within the Galactic bulge and plane. Alerts from the public survey will be broadcast to the community via established alert brokers. LS4 will run concurrently with the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). The combination of LS4+LSST will enable detailed holistic monitoring of many nearby transients: high-cadence LS4 observations will resolve the initial rise and peak of the light curve while less-frequent but deeper observations by LSST will characterize the years before and after explosion. Here, we summarize the primary science objectives of LS4 including microlensing events in the Galaxy, extragalactic transients, the search for electromagnetic counterparts to multi-messenger events, and cosmology.

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Galaxy Zoo DESI: large-scale bars as a secular mechanism for triggering AGN

Despite the evidence that supermassive black holes (SMBHs) co-evolve with their host galaxy, and that most of the growth of these SMBHs occurs via merger-free processes, the underlying mechanisms which drive this secular co-evolution are poorly understood. We investigate the role that both strong and weak large-scale galactic bars play in mediating this relationship. Using 72,940 disc galaxies in a volume-limited sample from Galaxy Zoo DESI, we analyse the active galactic nucleus (AGN) fraction in strongly barred, weakly barred, and unbarred galaxies up to z = 0.1 over a range of stellar masses and colours. After controlling for stellar mass and colour, we find that the optically selected AGN fraction is 31.6 +/- 0.9 per cent in strongly barred galaxies, 23.3 +/- 0.8 per cent in weakly barred galaxies, and 14.2 +/- 0.6 per cent in unbarred disc galaxies. These are highly statistically robust results, strengthening the tantalising results in earlier works. Strongly barred galaxies have a higher fraction of AGNs than weakly barred galaxies, which in turn have a higher fraction than unbarred galaxies. Thus, while bars are not required in order to grow a SMBH in a disc galaxy, large-scale galactic bars appear to facilitate AGN fuelling, and the presence of a strong bar makes a disc galaxy more than twice as likely to host an AGN than an unbarred galaxy at all galaxy stellar masses and colours.

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Searching for the Role of Mergers in Fast and Early SMBH Growth: Morphological Decomposition of Quasars and Their Hosts at $z \sim 4.8$

We present rest-frame ultraviolet (UV) images of six luminous quasars at $z \sim 4.8$ obtained with the Hubble Space Telescope (HST). These quasars exhibit a wide range of star formation rates (SFRs) and lie in a wide range of environments. We carefully model and subtract the point-like quasar emission and investigate the morphology of the underlying host galaxies at kpc scales. The residual images allowed identification of potential companion sources, which enabled us to explore the role of galaxy merger scenarios in the co-evolution of the quasars and their hosts. We also search for the mechanism driving extreme SFRs in three of the quasars. We find that the rate of detection of potential companions to the host galaxies does not follow trends between high- and low-SFR sources; i.e., the HST imaging suggests that both high- and low-SFR sources are found in both dense and sparse galactic environments. The suggested role of major mergers driving extreme SFRs cannot be supported by the multiwavelength data in hand. Three of four companion sources, previously revealed by sub-millimeter observations, are not detected in the HST images of three of our quasars. An adapted high-resolution imaging strategy focused on high-SFR sources and extended to a larger quasar sample is required to determine the role of mergers in the processes of star formation and supermassive black hole growth at high redshift.

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A Candidate Dual QSO at Cosmic Noon

We report the discovery of a candidate dual QSO at z=1.889, a redshift that is in the era known as "cosmic noon" where most of the Universe's black hole and stellar mass growth occurred. The source was identified in Hubble Space Telescope WFC3/IR images of a dust-reddened QSO that showed two closely-separated point sources at a projected distance of 0.26", or 2.2 kpc. This red QSO was targeted for imaging to explore whether red QSOs are hosted by merging galaxies. We subsequently obtained a spatially-resolved STIS spectrum of the system, covering the visible spectral range, and verifying the presence of two distinct QSO components. We also obtained high-resolution radio continuum observations with the VLBA at 1.4 GHz (21-cm L band) and found two sources coincident with the optical positions. The sources have similar black hole masses, bolometric luminosities, and radio loudness parameters. However, their colors and reddenings differ significantly. The redder QSO has a higher Eddington ratio, consistent with previous findings. We consider the possibility of gravitational lensing and and find that it would require extreme and unlikely conditions. If confirmed as a bona-fide dual QSO, this system would link dust-reddening to galaxy and supermassive black hole mergers, opening up a new population in which to search for samples of dual AGN.

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

The role of large-scale bars in the fuelling of active galactic nuclei (AGN) is still debated, even as evidence mounts that black hole growth in the absence of galaxy mergers cumulatively dominated 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 characterise 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 0.024. After carefully correcting for AGN signal, we find no clear difference in SFR 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 a small sample size (n_AGN = 34). We correct for SFR and stellar mass to minimise selection biases, and compare the bar fraction in the two samples. We find that AGN are marginally (1.7$σ$) more likely to host a bar than inactive galaxies, with AGN hosts having a bar fraction, fbar = 0.59^{+0.08}_{-0.09} and inactive galaxies having a bar fraction fbar = 0.44^{+0.08}_{-0.09}. However, we find no further differences between SFR- and mass-matched AGN 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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Harnessing the Hubble Space Telescope Archives: A Catalogue of 21,926 Interacting Galaxies

Mergers play a complex role in galaxy formation and evolution. Continuing to improve our understanding of these systems require ever larger samples, which can be difficult (even impossible) to select from individual surveys. We use the new platform ESA Datalabs to assemble a catalogue of interacting galaxies from the Hubble Space Telescope science archives; this catalogue is larger than previously published catalogues 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 Catalogue. 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 catalogue publicly available for use by the community. In addition to providing a new catalogue 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.

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Galaxy Zoo: Clump Scout -- Design and first application of a two-dimensional aggregation tool for citizen science

Galaxy Zoo: Clump Scout is a web-based citizen science project designed to identify and spatially locate giant star forming clumps in galaxies that were imaged by the Sloan Digital Sky Survey Legacy Survey. We present a statistically driven software framework that is designed to aggregate two-dimensional annotations of clump locations provided by multiple independent Galaxy Zoo: Clump Scout volunteers and generate a consensus label that identifies the locations of probable clumps within each galaxy. The statistical model our framework is based on allows us to assign false-positive probabilities to each of the clumps we identify, to estimate the skill levels of each of the volunteers who contribute to Galaxy Zoo: Clump Scout and also to quantitatively assess the reliability of the consensus labels that are derived for each subject. We apply our framework to a dataset containing 3,561,454 two-dimensional points, which constitute 1,739,259 annotations of 85,286 distinct subjects provided by 20,999 volunteers. Using this dataset, we identify 128,100 potential clumps distributed among 44,126 galaxies. This dataset can be used to study the prevalence and demographics of giant star forming clumps in low-redshift galaxies. The code for our aggregation software framework is publicly available at: https://github.com/ou-astrophysics/BoxAggregator

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Signatures of Feedback in the Spectacular Extended Emission Region of NGC 5972

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 arc-second scale nuclear bubble. NGC 5972 is a faded AGN, with EELR luminosity suggesting a 2.1 dex decrease in L$_{\textrm{bol}}$ in the last $\sim5\times10^{4}$ 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 broadband (0.3-8 keV) nuclear X-ray emission coincident with the [OIII] 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 ($\sim$0.80,$\sim$0.10 keV). We find a bubble age >2.2 Myr, suggesting formation before the current variability. We find evidence for efficient feedback with L$_{\textrm{kin}}/L_{\textrm{bol}}\sim0.8\%$, which may be overestimated given the recent L$_{\textrm{bol}}$ variation. Kinematics suggest an out-flowing 300 km s$^{-1}$ high-ionization [OIII]-emitting gas which may be the line of sight component of a $\sim$780 km s$^{-1}$ thermal X-ray outflow capable of driving strong shocks that could photoionize the precursor material. We explore possibilities to explain the overall jet, radio lobe and EELR misalignment including evidence for a double SMBH which could support a complex misaligned system.

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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% 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 datasets 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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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 (ACS) 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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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 vs. 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. When measured against confident volunteer classifications, the networks are approximately 99% 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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