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Photometric surveys produce large-area maps of the galaxy distribution, but with less accurate redshift information than is obtained from spectroscopic methods. Modern photometric redshift (photo-z) algorithms use galaxy magnitudes, or colours, that are obtained through multiband imaging to produce a probability density function (PDF) for each galaxy in the map. We used simulated data to study the effect of using different photo-z estimators to assign galaxies to redshift bins in order to compare their effects on angular clustering and galaxy bias measurements. We found that if we use the entire PDF, rather than a single-point (mean or mode) estimate, the deviations are less biased, especially when using narrow redshift bins. When the redshift bin widths are Δz = 0.1, the use of the entire PDF reduces the typical measurement bias from 5 per cent, when using single point estimates, to 3 per cent. [ABSTRACT FROM AUTHOR]

We present results from a study of the photometric redshift performance of the Dark Energy Survey (DES), using the early data from a Science Verification period of observations in late 2012 and early 2013 that provided science-quality images for almost 200 sq. deg. at the nominal depth of the survey. We assess the photometric redshift (photo-z) performance using about 15 000 galaxies with spectroscopic redshifts available from other surveys. These galaxies are used, in different configurations, as a calibration sample, and photo-z's are obtained and studied using most of the existing photo-z codes. A weighting method in a multidimensional colour-magnitude space is applied to the spectroscopic sample in order to evaluate the photo-z performance with sets that mimic the full DES photometric sample, which is on average significantly deeper than the calibration sample due to the limited depth of spectroscopic surveys. Empirical photo-z methods using, for instance, artificial neural networks or random forests, yield the best performance in the tests, achieving core photo-z resolutions σ68 ∼ 0.08. Moreover, the results from most of the codes, including template-fitting methods, comfortably meet the DES requirements on photo-z performance, therefore, providing an excellent precedent for future DES data sets. [ABSTRACT FROM AUTHOR]

Widefield surveys probe clustered scalar fields – such as galaxy counts, lensing potential, etc. – which are sensitive to different cosmological and astrophysical processes. Constraining such processes depends on the statistics that summarize the field. We explore the cumulative distribution function (CDF) as a summary of the galaxy lensing convergence field. Using a suite of N -body light-cone simulations, we show the CDFs' constraining power is modestly better than the second and third moments, as CDFs approximately capture information from all moments. We study the practical aspects of applying CDFs to data, using the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the point spread function and reduced shear approximation are |$\lesssim 1~{{\ \rm per\ cent}}$| of the total signal. Source clustering effects and baryon imprints contribute 1–10 per cent. Enforcing scale cuts to limit systematics-driven biases in parameter constraints degrade these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We detect correlations between the observed convergence field and the shape noise field at 13σ. The non-Gaussian correlations in the noise field must be modelled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool. [ABSTRACT FROM AUTHOR]

We present direct constraints on galaxy intrinsic alignments (IAs) using the Dark Energy Survey Year 3 (DES Y3), the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and its precursor, the Baryon Oscillation Spectroscopic Survey (BOSS). Our measurements incorporate photometric red sequence (redMaGiC) galaxies from DES with median redshift z ∼ 0.2–1.0, luminous red galaxies from eBOSS at z ∼ 0.8, and also an SDSS-III BOSS CMASS sample at z ∼ 0.5. We measure two-point IA correlations, which we fit using a model that includes lensing, magnification, and photometric redshift error. Fitting on scales 6 Mpc  h −1 < r p < 70 Mpc  h −1, we make a detection of IAs in each sample, at 5σ–22σ (assuming a simple one-parameter model for IAs). Using these red samples, we measure the IA–luminosity relation. Our results are statistically consistent with previous results, but offer a significant improvement in constraining power, particularly at low luminosity. With this improved precision, we see detectable dependence on colour between broadly defined red samples. It is likely that a more sophisticated approach than a binary red/blue split, which jointly considers colour and luminosity dependence in the IA signal, will be needed in future. We also compare the various signal components at the best-fitting point in parameter space for each sample, and find that magnification and lensing contribute |$\sim 2\!-\!18~{{\ \rm per\ cent}}$| of the total signal. As precision continues to improve, it will certainly be necessary to account for these effects in future direct IA measurements. Finally, we make equivalent measurements on a sample of emission-line galaxies from eBOSS at z ∼ 0.8. We constrain the non-linear alignment amplitude to be |$A_1=0.07^{+0.32}_{-0.42}$| (| A 1| < 0.78 at 95 per cent CL). [ABSTRACT FROM AUTHOR]

We present a sample of 19 583 ultracool dwarf candidates brighter than z ≤23 selected from the Dark Energy Survey DR2 coadd data matched to VHS DR6, VIKING DR5, and AllWISE covering ∼ 480 deg2. The ultracool candidates were first pre-selected based on their (i–z), (z–Y), and (Y–J) colours. They were further classified using a method that compares their optical, near-infrared, and mid-infrared colours against templates of M, L, and T dwarfs. 14 099 objects are presented as new L and T candidates and the remaining objects are from the literature, including 5342 candidates from our previous work. Using this new and deeper sample of ultracool dwarf candidates we also present: 20 new candidate members to nearby young moving groups and associations, variable candidate sources and four new wide binary systems composed of two ultracool dwarfs. Finally, we also show the spectra of 12 new ultracool dwarfs discovered by our group and presented here for the first time. These spectroscopically confirmed objects are a sanity check of our selection of ultracool dwarfs and photometric classification method. [ABSTRACT FROM AUTHOR]

We present deep g- and r-band Magellan/Megacam photometry of two dwarf galaxy candidates discovered in the Dark Energy Survey (DES), Grus i and Indus ii (DES J2038–4609). For the case of Grus i , we resolved the main sequence turn-off (MSTO) and ∼2 mags below it. The MSTO can be seen at g0 ∼ 24 with a photometric uncertainty of 0.03 mag. We show Grus i to be consistent with an old, metal-poor (∼13.3 Gyr, [Fe/H] ∼ −1.9) dwarf galaxy. We derive updated distance and structural parameters for Grus i using this deep, uniform, wide-field data set. We find an azimuthally-averaged halflight radius more than two times larger (∼151+21−31 pc; ∼) and an absolute V-band magnitude ∼−4.1 that is ∼1 magnitude brighter than previous studies. We obtain updated distance, ellipticity, and centroid parameters that are in agreement with other studies within uncertainties. Although our photometry of Indus ii is ∼2–3 magnitudes deeper than the DES Y1 public release, we find no coherent stellar population at its reported location. The original detection was located in an incomplete region of sky in the DES Y2Q1 data set and was flagged due to potential blue horizontal branch member stars. The best-fit isochrone parameters are physically inconsistent with both dwarf galaxies and globular clusters. We conclude that Indus ii is likely a false positive, flagged due to a chance alignment of stars along the line of sight. [ABSTRACT FROM AUTHOR]

In this paper we investigate how implementing machine learning could improve the efficiency of the search for Trans-Neptunian Objects (TNOs) within Dark Energy Survey (DES) data when used alongside orbit fitting. The discovery of multiple TNOs that appear to show a similarity in their orbital parameters has led to the suggestion that one or more undetected planets, an as yet undiscovered "Planet 9", may be present in the outer solar system. DES is well placed to detect such a planet and has already been used to discover many other TNOs. Here, we perform tests on eight different supervised machine learning algorithms, using a data set consisting of simulated TNOs buried within real DES noise data. We found that the best performing classifier was the Random Forest which, when optimized, performed well at detecting the rare objects. We achieve an area under the receiver operating characteristic (ROC) curve, (AUC) = 0.996 ± 0.001. After optimizing the decision threshold of the Random Forest, we achieve a recall of 0.96 while maintaining a precision of 0.80. Finally, by using the optimized classifier to pre-select objects, we are able to run the orbit-fitting stage of our detection pipeline five times faster. [ABSTRACT FROM AUTHOR]

We present the discovery of 255 binary and 6 multiple system candidates with wide (> 5 arcsec) separation composed by ultracool dwarfs (UCDs) companions to stars, plus nine double ultracool dwarf systems. These systems were selected based on common distance criteria. About 90 per cent of the total sample has proper motions available and 73 per cent of the systems also satisfy a common proper motion criterion. The sample of ultracool candidates was taken from the Dark Energy Survey (DES) and the candidate stellar primaries are from Gaia DR2 and DES data. We compute chance alignment probabilities in order to assess the physical nature of each pair. We find that 174 candidate pairs with Gaia DR2 primaries and 81 pairs with a DES star as a primary have chance alignment probabilities |$\lt 5{{\ \rm per\ cent}}$|⁠. Only nine candidate systems composed of two UCDs were identified. The sample of candidate multiple systems is made up of five triple systems and one quadruple system. The majority of the UCDs found in binaries and multiples are of early L type and the typical wide binary fraction over the L spectral types is |$2\!-\!4{{\ \rm per\ cent}}$|⁠. Our sample of candidate wide binaries with UCDs as secondaries constitutes a substantial increase over the known number of such systems, which are very useful to constrain the formation and evolution of UCDs. [ABSTRACT FROM AUTHOR]

We present the MARD-Y3 catalogue of between 1086 and 2171 galaxy clusters (52 per cent and 65 per cent new) produced using multicomponent matched filter (MCMF) follow-up in 5000 deg2 of DES-Y3 optical data of the ∼20 000 overlapping ROSAT All-Sky Survey source catalogue (2RXS) X-ray sources. Optical counterparts are identified as peaks in galaxy richness as a function of redshift along the line of sight towards each 2RXS source within a search region informed by an X-ray prior. All peaks are assigned a probability f cont of being a random superposition. The clusters lie at 0.02 < z < 1.1 with more than 100 clusters at z > 0.5. Residual contamination is 2.6 per cent and 9.6 per cent for the cuts adopted here. For each cluster we present the optical centre, redshift, rest frame X-ray luminosity, M 500 mass, coincidence with NWAY infrared sources, and estimators of dynamical state. About 2 per cent of MARD-Y3 clusters have multiple possible counterparts, the photo- z 's are high quality with σΔ z /(1 + z) = 0.0046, and ∼1 per cent of clusters exhibit evidence of X-ray luminosity boosting from emission by cluster active galactic nuclei. Comparison with other catalogues (MCXC, RM, SPT-SZ, Planck) is performed to test consistency of richness, luminosity, and mass estimates. We measure the MARD-Y3 X-ray luminosity function and compare it to the expectation from a fiducial cosmology and externally calibrated luminosity- and richness–mass relations. Agreement is good, providing evidence that MARD-Y3 has low contamination and can be understood as a simple two step selection – X-ray and then optical – of an underlying cluster population described by the halo mass function. [ABSTRACT FROM AUTHOR]

The correlation between active galactic nuclei (AGNs) and environment provides important clues to AGN fuelling and the relationship of black hole growth to galaxy evolution. In this paper, we analyse the fraction of galaxies in clusters hosting AGN as a function of redshift and cluster richness for X-ray-detected AGN associated with clusters of galaxies in Dark Energy Survey (DES) Science Verification data. The present sample includes 33 AGNs with LX >1043 erg s-1 in non-central, host galaxies with luminosity greater than 0.5L* from a total sample of 432 clusters in the redshift range of 0.1 < z < 0.95. Analysis of the present sample reveals that the AGN fraction in red-sequence cluster members has a strong positive correlation with redshift such that the AGN fraction increases by a factor of ~8 from low to high redshift, and the fraction of cluster galaxies hosting AGN at high redshifts is greater than the low-redshift fraction at 3.6σ. In particular, the AGN fraction increases steeply at the highest redshifts in our sample at z > 0.7. This result is in good agreement with previous work and parallels the increase in star formation in cluster galaxies over the same redshift range. However, the AGN fraction in clusters is observed to have no significant correlation with cluster mass. Future analyses with DES Year 1 through Year 3 data will be able to clarify whether AGN activity is correlated to cluster mass and will tightly constrain the relationship between cluster AGN populations and redshift. [ABSTRACT FROM AUTHOR]

The Large Magellanic Cloud (LMC) harbours a rich and diverse system of star clusters, whose ages, chemical abundances and positions provide information about the LMC history of star formation. We use Science Verification imaging data from the Dark Energy Survey (DES) to increase the census of known star clusters in the outer LMC and to derive physical parameters for a large sample of such objects using a spatially and photometrically homogeneous data set. Our sample contains 255 visually identified cluster candidates, of which 109 were not listed in any previous catalogue. We quantify the crowding effect for the stellar sample produced by the DES Data Management pipeline and conclude that the stellar completeness is <10 per cent inside typical LMC cluster cores. We therefore reanalysed the DES co-add images around each candidate cluster and remeasured positions and magnitudes for their stars. We also implement a maximum-likelihood method to fit individual density profiles and colour-magnitude diagrams. For 117 (from a total of 255) of the cluster candidates (28 uncatalogued clusters), we obtain reliable ages, metallicities, distance moduli and structural parameters, confirming their nature as physical systems. The distribution of cluster metallicities shows a radial dependence, with no clusters more metal rich than [Fe/H]≃-0.7 beyond 8 kpc from the LMC centre. The age distribution has two peaks at ≃1.2 and ≃2.7 Gyr. [ABSTRACT FROM AUTHOR]