arXiv subjects

W. Wester

Publications and source records attributed to W. Wester.

At least 73 records · Page 4Linked to original sources

arXiv2017

Eight new luminous z > 6 quasars selected via SED model fitting of VISTA, WISE and Dark Energy Survey Year 1 Observations

We present the discovery and spectroscopic confirmation with the ESO NTT and Gemini South telescopes of eight new 6.0 < z < 6.5 quasars with z$_{AB}$ < 21.0. These quasars were photometrically selected without any star-galaxy morphological criteria from 1533 deg$^{2}$ using SED model fitting to photometric data from the Dark Energy Survey (g, r, i, z, Y), the VISTA Hemisphere Survey (J, H, K) and the Wide-Field Infrared Survey Explorer (W1, W2). The photometric data was fitted with a grid of quasar model SEDs with redshift dependent Lyman-α forest absorption and a range of intrinsic reddening as well as a series of low mass cool star models. Candidates were ranked using on a SED-model based $χ^{2}$-statistic, which is extendable to other future imaging surveys (e.g. LSST, Euclid). Our spectral confirmation success rate is 100% without the need for follow-up photometric observations as used in other studies of this type. Combined with automatic removal of the main types of non-astrophysical contaminants the method allows large data sets to be processed without human intervention and without being over run by spurious false candidates. We also present a robust parametric redshift estimating technique that gives comparable accuracy to MgII and CO based redshift estimators. We find two z $\sim$ 6.2 quasars with HII near zone sizes < 3 proper Mpc which could indicate that these quasars may be young with ages < 10$^6$ - 10$^7$ years or lie in over dense regions of the IGM. The z = 6.5 quasar VDESJ0224-4711 has J$_{AB}$ = 19.75 is the second most luminous quasar known with z > 6.5.

astro-ph.GA↗

arXiv2016

A Study of Quasar Selection in the Dark Energy Survey Supernova fields

We present a study of quasar selection using the DES supernova fields. We used a quasar catalog from an overlapping portion of the SDSS Stripe 82 region to quantify the completeness and efficiency of selection methods involving color, probabilistic modeling, variability, and combinations of color/probabilistic modeling with variability. We only considered objects that appear as point sources in the DES images. We examine color selection methods based on the WISE mid-IR W1-W2 color, a mixture of WISE and DES colors (g-i and i-W1) and a mixture of VHS and DES colors (g-i and i-K). For probabilistic quasar selection, we used XDQSOz, an algorithm that employs an empirical multi-wavelength flux model of quasars to assign quasar probabilities. Our variability selection uses the multi-band chi2-probability that sources are constant in the DES Year 1 griz-band light curves. The completeness and efficiency are calculated relative to an underlying sample of point sources that are detected in the required selection bands and pass our data quality and photometric error cuts. We conduct our analyses at two magnitude limits, i<19.8 mag and i<22 mag. For sources with W1 and W2 detections, the W1-W2 color or XDQSOz method combined with variability gives the highest completenesses of >85% for both i-band magnitude limits and efficiencies of >80% to the bright limit and >60% to the faint limit; however, the giW1 and giW1+variability methods give the highest quasar surface densities. The XDQSOz method and combinations of W1W2/giW1/XDQSOz with variability are among the better selection methods when both high completeness and high efficiency are desired. We also present the OzDES Quasar Catalog of 1,263 spectroscopically-confirmed quasars taken by the OzDES survey. The catalog includes quasars with redshifts up to z~4 and brighter than i=22 mag, although the catalog is not complete up this magnitude limit.

astro-ph.GA↗

arXiv2016

A DECam Search for an Optical Counterpart to the LIGO Gravitational Wave Event GW151226

We report the results of a Dark Energy Camera (DECam) optical follow-up of the gravitational wave (GW) event GW151226, discovered by the Advanced LIGO detectors. Our observations cover 28.8 deg$^2$ of the localization region in the $i$ and $z$ bands (containing 3% of the BAYESTAR localization probability), starting 10 hours after the event was announced and spanning four epochs at $2-24$ days after the GW detection. We achieve $5σ$ point-source limiting magnitudes of $i\approx21.7$ and $z\approx21.5$, with a scatter of $0.4$ mag, in our difference images. Given the two day delay, we search this area for a rapidly declining optical counterpart with $\gtrsim 3σ$ significance steady decline between the first and final observations. We recover four sources that pass our selection criteria, of which three are cataloged AGN. The fourth source is offset by $5.8$ arcsec from the center of a galaxy at a distance of 187 Mpc, exhibits a rapid decline by $0.5$ mag over $4$ days, and has a red color of $i-z\approx 0.3$ mag. These properties roughly match the expectations for a kilonova. However, this source was detected several times, starting $94$ days prior to GW151226, in the Pan-STARRS Survey for Transients (dubbed as PS15cdi) and is therefore unrelated to the GW event. Given its long-term behavior, PS15cdi is likely a Type IIP supernova that transitioned out of its plateau phase during our observations, mimicking a kilonova-like behavior. We comment on the implications of this detection for contamination in future optical follow-up observations.

astro-ph.HE↗

arXiv2016

DESAlert: Enabling Real-Time Transient Follow-Up with Dark Energy Survey Data

The Dark Energy Survey (DES) is currently undertaking an observational program imaging $1/4$ of the southern hemisphere sky with unprecedented photometric accuracy. In the process of observing millions of faint stars and galaxies to constrain the parameters of the dark energy equation of state, the DES will obtain pre-discovery images of the regions surrounding an estimated 100 gamma-ray bursts (GRBs) over five years. Once GRBs are detected by, e.g., the Swift satellite, the DES data will be extremely useful for follow-up observations by the transient astronomy community. We describe a recently-commissioned suite of software that listens continuously for automated notices of GRB activity, collates useful information from archival DES data, and disseminates relevant data products back to the community in near-real-time. Of particular importance are the opportunities that non-public DES data provide for relative photometry of the optical counterparts of GRBs, as well as for identifying key characteristics (e.g., photometric redshifts) of potential GRB host galaxies. We provide the functional details of the DESAlert software as it presently operates, as well as the data products that it produces, and we show sample results from the application of DESAlert to several previously-detected GRBs.

astro-ph.HE↗

arXiv2016

Crowdsourcing quality control for Dark Energy Survey images

We have developed a crowdsourcing web application for image quality control employed by the Dark Energy Survey. Dubbed the "DES exposure checker", it renders science-grade images directly to a web browser and allows users to mark problematic features from a set of predefined classes. Users can also generate custom labels and thus help identify previously unknown problem classes. User reports are fed back to hardware and software experts to help mitigate and eliminate recognized issues. We report on the implementation of the application and our experience with its over 100 users, the majority of which are professional or prospective astronomers but not data management experts. We discuss aspects of user training and engagement, and demonstrate how problem reports have been pivotal to rapidly correct artifacts which would likely have been too subtle or infrequent to be recognized otherwise. We conclude with a number of important lessons learned, suggest possible improvements, and recommend this collective exploratory approach for future astronomical surveys or other extensive data sets with a sufficiently large user base. We also release open-source code of the web application and host an online demo version at http://des-exp-checker.pmelchior.net

astro-ph.IM↗

arXiv2016

Assessment of Systematic Chromatic Errors that Impact Sub-1% Photometric Precision in Large-Area Sky Surveys

Meeting the science goals for many current and future ground-based optical large-area sky surveys requires that the calibrated broadband photometry is stable in time and uniform over the sky to 1% precision or better. Past surveys have achieved photometric precision of 1-2% by calibrating the survey's stellar photometry with repeated measurements of a large number of stars observed in multiple epochs. The calibration techniques employed by these surveys only consider the relative frame-by-frame photometric zeropoint offset and the focal plane position-dependent illumination corrections, which are independent of the source color. However, variations in the wavelength dependence of the atmospheric transmission and the instrumental throughput induce source color-dependent systematic errors. These systematic errors must also be considered to achieve the most precise photometric measurements. In this paper, we examine such systematic chromatic errors using photometry from the Dark Energy Survey (DES) as an example. We define a natural magnitude system for DES and calculate the systematic errors on stellar magnitudes, when the atmospheric transmission and instrumental throughput deviate from the natural system. We conclude that the systematic chromatic errors caused by the change of airmass in each exposure, the change of the precipitable water vapor and aerosol in the atmosphere over time, and the non-uniformity of instrumental throughput over the focal plane, can be up to 2% in some bandpasses. We compare the calculated systematic chromatic errors with the observed DES data. For the test sample data, we correct these errors using measurements of the atmospheric transmission and instrumental throughput. The residual after correction is less than 0.3%. We also find that the errors for non-stellar objects are redshift-dependent and can be larger than those for stars at certain redshifts.

astro-ph.IM↗

arXiv2016

A Dark Energy Camera Search for an Optical Counterpart to the First Advanced LIGO Gravitational Wave Event GW150914

We report initial results of a deep search for an optical counterpart to the gravitational wave event GW150914, the first trigger from the Advanced LIGO gravitational wave detectors. We used the Dark Energy Camera (DECam) to image a 102 deg$^2$ area, corresponding to 38% of the initial trigger high-probability sky region and to 11% of the revised high-probability region. We observed in i and z bands at 4-5, 7, and 24 days after the trigger. The median $5σ$ point-source limiting magnitudes of our search images are i=22.5 and z=21.8 mag. We processed the images through a difference-imaging pipeline using templates from pre-existing Dark Energy Survey data and publicly available DECam data. Due to missing template observations and other losses, our effective search area subtends 40 deg$^{2}$, corresponding to 12% total probability in the initial map and 3% of the final map. In this area, we search for objects that decline significantly between days 4-5 and day 7, and are undetectable by day 24, finding none to typical magnitude limits of i= 21.5,21.1,20.1 for object colors (i-z)=1,0,-1, respectively. Our search demonstrates the feasibility of a dedicated search program with DECam and bodes well for future research in this emerging field.

astro-ph.CO↗

arXiv2016

DES14X3taz: A Type I Superluminous Supernova Showing a Luminous, Rapidly Cooling Initial Pre-Peak Bump

We present DES14X3taz, a new hydrogen-poor super luminous supernova (SLSN-I) discovered by the Dark Energy Survey (DES) supernova program, with additional photometric data provided by the Survey Using DECam for Superluminous Supernovae (SUDSS). Spectra obtained using OSIRIS on the Gran Telescopio CANARIAS (GTC) show DES14X3taz is a SLSN-I at z=0.608. Multi-color photometry reveals a double-peaked light curve: a blue and relatively bright initial peak that fades rapidly prior to the slower rise of the main light curve. Our multi-color photometry allows us, for the first time, to show that the initial peak cools from 22,000K to 8,000K over 15 rest-frame days, and is faster and brighter than any published core-collapse supernova, reaching 30% of the bolometric luminosity of the main peak. No physical Nickel powered model can fit this initial peak. We show that a shock-cooling model followed by a magnetar driving the second phase of the light curve can adequately explain the entire light curve of DES14X3taz. Models involving the shock-cooling of extended circumstellar material at a distance of ~400 solar radii are preferred over the cooling of shock-heated surface layers of a stellar envelope. We compare DES14X3taz to the few double-peaked SLSN-I events in the literature. Although the rise-times and characteristics of these initial peaks differ, there exists the tantalizing possibility that they can be explained by one physical interpretation.

astro-ph.SR↗

arXiv2015

Automated Transient Identification in the Dark Energy Survey

We describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning technique known as Random Forest. We present results from its use in the Dark Energy Survey Supernova program (DES-SN), where it was trained using a sample of 898,963 signal and background events generated by the transient detection pipeline. After reprocessing the data collected during the first DES-SN observing season (Sep. 2013 through Feb. 2014) using the algorithm, the number of transient candidates eligible for human scanning decreased by a factor of 13.4, while only 1 percent of the artificial Type Ia supernovae (SNe) injected into search images to monitor survey efficiency were lost, most of which were very faint events. Here we characterize the algorithm's performance in detail, and we discuss how it can inform pipeline design decisions for future time-domain imaging surveys, such as the Large Synoptic Survey Telescope and the Zwicky Transient Facility. An implementation of the algorithm and the training data used in this paper are available at http://portal.nersc.gov/project/dessn/autoscan.

astro-ph.IM↗

arXiv2015

Observation and Confirmation of Six Strong Lensing Systems in The Dark Energy Survey Science Verification Data

We report the observation and confirmation of the first group- and cluster-scale strong gravitational lensing systems found in Dark Energy Survey (DES) data. Through visual inspection of data from the Science Verification (SV) season, we identified 53 candidate systems. We then obtained spectroscopic follow-up of 21 candidates using the Gemini Multi-Object Spectrograph (GMOS) at the Gemini South telescope and the Inamori-Magellan Areal Camera and Spectrograph (IMACS) at the Magellan/Baade telescope. With this follow-up, we confirmed six candidates as gravitational lenses: Three of the systems are newly discovered, and the remaining three were previously known. Of the 21 observed candidates, the remaining 15 were either not detected in spectroscopic observations, were observed and did not exhibit continuum emission (or spectral features), or were ruled out as lensing systems. The confirmed sample consists of one group-scale and five galaxy cluster-scale lenses. The lensed sources range in redshift z ~ 0.80-3.2, and in i-band surface brightness i_{SB} ~ 23-25 mag/sq.-arcsec. (2" aperture). For each of the six systems, we estimate the Einstein radius and the enclosed mass, which have ranges ~ 5.0 - 8.6" and ~ 7.5 x 10^{12} - 6.4 x 10^{13} solar masses, respectively.

astro-ph.CO↗

arXiv2015

Eight Ultra-faint Galaxy Candidates Discovered in Year Two of the Dark Energy Survey

We report the discovery of eight new ultra-faint dwarf galaxy candidates in the second year of optical imaging data from the Dark Energy Survey (DES). Six of these candidates are detected at high confidence, while two lower-confidence candidates are identified in regions of non-uniform survey coverage. The new stellar systems are found by three independent automated search techniques and are identified as overdensities of stars, consistent with the isochrone and luminosity function of an old and metal-poor simple stellar population. The new systems are faint (Mv > -4.7 mag) and span a range of physical sizes (17 pc < $r_{1/2}$ < 181 pc) and heliocentric distances (25 kpc < D < 214 kpc). All of the new systems have central surface brightnesses consistent with known ultra-faint dwarf galaxies (μ< 27.5 mag arcsec$^{-2}$). Roughly half of the DES candidates are more distant, less luminous, and/or have lower surface brightnesses than previously known Milky Way satellite galaxies. Most of the candidates are found in the southern part of the DES footprint close to the Magellanic Clouds. We find that the DES data alone exclude (p < 0.001) a spatially isotropic distribution of Milky Way satellites and that the observed distribution can be well, though not uniquely, described by an association between several of the DES satellites and the Magellanic system. Our model predicts that the full sky may hold ~100 ultra-faint galaxies with physical properties comparable to the DES satellites and that 20-30% of these would be spatially associated with the Magellanic Clouds.

astro-ph.GA↗

arXiv2015

The Difference Imaging Pipeline for the Transient Search in the Dark Energy Survey

We describe the difference imaging pipeline (DiffImg) used to detect transients in deep images from the Dark Energy Survey Supernova program (DES-SN) in its first observing season from Aug 2013 through Feb 2014. DES-SN is a search for transients in which ten 3-deg^2 fields are repeatedly observed in the g,r,i,z passbands with a cadence of about 1 week. The observing strategy has been optimized to measure high-quality light curves and redshifts for thousands of Type Ia supernova (SN Ia) with the goal of measuring dark energy parameters. The essential DiffImg functions are to align each search image to a deep reference image, do a pixel-by-pixel subtraction, and then examine the subtracted image for significant positive detections of point-source objects. The vast majority of detections are subtraction artifacts, but after selection requirements and image filtering with an automated scanning program, there are 130 detections per deg^2 per observation in each band, of which only 25% are artifacts. Of the 7500 transients discovered by DES-SN in its first observing season, each requiring a detection on at least 2 separate nights, Monte Carlo simulations predict that 27% are expected to be supernova. Another 30% of the transients are artifacts, and most of the remaining transients are AGN and variable stars. Fake SNe Ia are overlaid onto the images to rigorously evaluate detection efficiencies, and to understand the DiffImg performance. The DiffImg efficiency measured with fake SNe agrees well with expectations from a Monte Carlo simulation that uses analytical calculations of the fluxes and their uncertainties. In our 8 "shallow" fields with single-epoch 50% completeness depth 23.5, the SN Ia efficiency falls to 1/2 at redshift z 0.7, in our 2 "deep" fields with mag-depth 24.5, the efficiency falls to 1/2 at z 1.1.

astro-ph.IM↗

arXiv2015

redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data

We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the color-cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photozs are very nearly as accurate as the best machine-learning based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalog sampling the redshift range $z\in[0.2,0.8]$. Our fiducial sample has a comoving space density of $10^{-3}\ (h^{-1} Mpc)^{-3}$, and a median photoz bias ($z_{spec}-z_{photo}$) and scatter $(σ_z/(1+z))$ of 0.005 and 0.017 respectively. The corresponding $5σ$ outlier fraction is 1.4%. We also test our algorithm with Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8) and Stripe 82 data, and discuss how spectroscopic training can be used to control photoz biases at the 0.1% level.

astro-ph.IM↗

arXiv2015

Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.

astro-ph.CO↗

arXiv2015

Observation of Two New L4 Neptune Trojans in the Dark Energy Survey Supernova Fields

We report the discovery of the eighth and ninth known Trojans in stable orbits around Neptune's leading Lagrange point, L4. The objects 2014 QO$_{441}$ and 2014 QP$_{441}$ were detected in data obtained during the 2013-14 and 2014-15 observing seasons by the Dark Energy Survey, using the Dark Energy Camera (DECam) on the 4-meter Blanco telescope at Cerro Tololo Inter-American Observatory. Both are in high-inclination orbits (18.8$^{\circ}$ and 19.4$^{\circ}$ respectively). With an eccentricity of 0.104, 2014 QO$_{441}$ has the most eccentric orbit of the eleven known stable Neptune Trojans. Here we describe the search procedure and investigate the objects' long-term dynamical stability and physical properties.

astro-ph.EP↗

arXiv2015

Constraints on the Richness-Mass Relation and the Optical-SZE Positional Offset Distribution for SZE-Selected Clusters

We cross-match galaxy cluster candidates selected via their Sunyaev-Zel'dovich effect (SZE) signatures in 129.1 deg$^2$ of the South Pole Telescope 2500d SPT-SZ survey with optically identified clusters selected from the Dark Energy Survey (DES) science verification data. We identify 25 clusters between $0.1\lesssim z\lesssim 0.8$ in the union of the SPT-SZ and redMaPPer (RM) samples. RM is an optical cluster finding algorithm that also returns a richness estimate for each cluster. We model the richness $λ$-mass relation with the following function $\langle\lnλ|M_{500}\rangle\propto B_λ\ln M_{500}+C_λ\ln E(z)$ and use SPT-SZ cluster masses and RM richnesses $λ$ to constrain the parameters. We find $B_λ= 1.14^{+0.21}_{-0.18}$ and $C_λ=0.73^{+0.77}_{-0.75}$. The associated scatter in mass at fixed richness is $σ_{\ln M|λ} = 0.18^{+0.08}_{-0.05}$ at a characteristic richness $λ=70$. We demonstrate that our model provides an adequate description of the matched sample, showing that the fraction of SPT-SZ selected clusters with RM counterparts is consistent with expectations and that the fraction of RM selected clusters with SPT-SZ counterparts is in mild tension with expectation. We model the optical-SZE cluster positional offset distribution with the sum of two Gaussians, showing that it is consistent with a dominant, centrally peaked population and a sub-dominant population characterized by larger offsets. We also cross-match the RM catalog with SPT-SZ candidates below the official catalog threshold significance $ξ=4.5$, using the RM catalog to provide optical confirmation and redshifts for additional low-$ξ$ SPT-SZ candidates.In this way, we identify 15 additional clusters with $ξ\in [4,4.5]$ over the redshift regime explored by RM in the overlapping region between DES science verification data and the SPT-SZ survey.

astro-ph.CO↗

arXiv2015

Stellar Kinematics and Metallicities in the Ultra-Faint Dwarf Galaxy Reticulum II

We present Magellan/M2FS, VLT/GIRAFFE, and Gemini South/GMOS spectroscopy of the newly discovered Milky Way satellite Reticulum II. Based on the spectra of 25 Ret II member stars selected from Dark Energy Survey imaging, we measure a mean heliocentric velocity of 62.8 +/- 0.5 km/s and a velocity dispersion of 3.3 +/- 0.7 km/s. The mass-to-light ratio of Ret II within its half-light radius is 470 +/- 210 Msun/Lsun, demonstrating that it is a strongly dark matter-dominated system. Despite its spatial proximity to the Magellanic Clouds, the radial velocity of Ret II differs from that of the LMC and SMC by 199 and 83 km/s, respectively, suggesting that it is not gravitationally bound to the Magellanic system. The likely member stars of Ret II span 1.3 dex in metallicity, with a dispersion of 0.28 +/- 0.09 dex, and we identify several extremely metal-poor stars with [Fe/H] < -3. In combination with its luminosity, size, and ellipticity, these results confirm that Ret II is an ultra-faint dwarf galaxy. With a mean metallicity of [Fe/H] = -2.65 +/- 0.07, Ret II matches Segue~1 as the most metal-poor galaxy known. Although Ret II is the third-closest dwarf galaxy to the Milky Way, the line-of-sight integral of the dark matter density squared is log J = 18.8 +/- 0.6 Gev^2/cm^5 within 0.2 degrees, indicating that the predicted gamma-ray flux from dark matter annihilation in Ret II is lower than that of several other dwarf galaxies.

astro-ph.GA↗

arXiv2015

Eight New Milky Way Companions Discovered in First-Year Dark Energy Survey Data

We report the discovery of eight new Milky Way companions in ~1,800 deg^2 of optical imaging data collected during the first year of the Dark Energy Survey (DES). Each system is identified as a statistically significant over-density of individual stars consistent with the expected isochrone and luminosity function of an old and metal-poor stellar population. The objects span a wide range of absolute magnitudes (M_V from -2.2 mag to -7.4 mag), physical sizes (10 pc to 170 pc), and heliocentric distances (30 kpc to 330 kpc). Based on the low surface brightnesses, large physical sizes, and/or large Galactocentric distances of these objects, several are likely to be new ultra-faint satellite galaxies of the Milky Way and/or Magellanic Clouds. We introduce a likelihood-based algorithm to search for and characterize stellar over-densities, as well as identify stars with high satellite membership probabilities. We also present completeness estimates for detecting ultra-faint galaxies of varying luminosities, sizes, and heliocentric distances in the first-year DES data.

astro-ph.GA↗