Search

Recent analyses have found intriguing correlations between the colour ($c$) of type Ia supernovae (SNe Ia) and the size of their 'mass-step', the relationship between SN Ia host galaxy stellar mass ($M_\mathrm{stellar}$) and SN Ia Hubble residual, and suggest that the cause of this relationship is dust. Using 675 photometrically-classified SNe Ia from the Dark Energy Survey 5-year sample, we study the differences in Hubble residual for a variety of global host galaxy and local environmental properties for SN Ia subsamples split by their colour. We find a $3\sigma$ difference in the mass-step when comparing blue ($c0$) SNe. We observe the lowest r.m.s. scatter ($\sim0.14$ mag) in the Hubble residual for blue SNe in low mass/blue environments, suggesting that this is the most homogeneous sample for cosmological analyses. By fitting for $c$-dependent relationships between Hubble residuals and $M_\mathrm{stellar}$, approximating existing dust models, we remove the mass-step from the data and find tentative $\sim 2\sigma$ residual steps in rest-frame galaxy $U-R$ colour. This indicates that dust modelling based on $M_\mathrm{stellar}$ may not fully explain the remaining dispersion in SN Ia luminosity. Instead, accounting for a $c$-dependent relationship between Hubble residuals and global $U-R$, results in $\leq1\sigma$ residual steps in $M_\mathrm{stellar}$ and local $U-R$, suggesting that $U-R$ provides different information about the environment of SNe Ia compared to $M_\mathrm{stellar}$, and motivating the inclusion of galaxy $U-R$ colour in SN Ia distance bias correction., Comment: 19 pages, 8 figures. Published in MNRAS

DES Collaboration: et al., Strongly lensed quadruply imaged quasars (quads) are extraordinary objects. They are very rare in the sky and yet they provide unique information about a wide range of topics, including the expansion history and the composition of the Universe, the distribution of stars and dark matter in galaxies, the host galaxies of quasars, and the stellar initial mass function. Finding them in astronomical images is a classic ‘needle in a haystack’ problem, as they are outnumbered by other (contaminant) sources by many orders of magnitude. To solve this problem, we develop state-of-the-art deep learning methods and train them on realistic simulated quads based on real images of galaxies taken from the Dark Energy Survey, with realistic source and deflector models, including the chromatic effects of microlensing. The performance of the best methods on a mixture of simulated and real objects is excellent, yielding area under the receiver operating curve in the range of 0.86–0.89. Recall is close to 100 per cent down to total magnitude i ∼ 21 indicating high completeness, while precision declines from 85 per cent to 70 per cent in the range i ∼ 17–21. The methods are extremely fast: training on 2 million samples takes 20 h on a GPU machine, and 108 multiband cut-outs can be evaluated per GPU-hour. The speed and performance of the method pave the way to apply it to large samples of astronomical sources, bypassing the need for photometric pre-selection that is likely to be a major cause of incompleteness in current samples of known quads., TT acknowledges support from the National Science Foundation through grant NSF-AST-1906976, from NASA through grants HST-GO-15320and HST-GO-15652, and from the Packard Foundation through a Packard Research Fellowship. Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministério da Ciência, Tecnologia e Inovação, the Deutsche Forschungsgemeinschaft, and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciències de l’Espai (IEEC/CSIC), the Institut de Física d’Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, NSF’s NOIRLab, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, Texas A&M University, and the OzDES Membership Consortium. Based in part on observations at Cerro Tololo Inter-American Observatory at NSF’s NOIRLab (NOIRLab Prop. ID 2012B-0001; PI: J. Frieman), which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The DES data management system is supported by the National Science Foundation under grant numbers AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MICINN under grants ESP2017-89838, PGC2018-094773, PGC2018-102021, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA programme of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) do e-Universo (CNPq grant 465376/2014-2). This manuscript has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.

In this paper we present a catalogue of 11 745 brown dwarfs with spectral types rangingfrom L0 to T9, photometrically classified using data from the Dark Energy Survey (DES)year 3 release matched to the Vista Hemisphere Survey (VHS) DR3 and Wide-field InfraredSurvey Explorer (WISE) data, covering≈2400 deg2up toiAB=22. The classification methodfollows the same phototype method previously applied to SDSS-UKIDSS-WISE data. Themost significant difference comes from the use of DES data instead of SDSS, which allowus to classify almost an order of magnitude more brown dwarfs than any previous search andreaching distances beyond 400 pc for the earliest types. Next, we also present and validate theGalmodBDsimulation, which produces brown dwarf number counts as a function of structuralparameters with realistic photometric properties of a given survey. We use this simulation toestimate the completeness and purity of our photometric LT catalogue down toiAB=22, aswell as to compare to the observed number of LT types. We put constraints on the thin disc scaleheight for the early L (L0–L3) population to be around 450 pc, in agreement with previousfindings. For completeness, we also publish in a separate table a catalogue of 20 863 M dwarfsthat passed our colour cut with spectral types greater than M6. Both the LT and the late Mcatalogues are found at DES release page https://des.ncsa.illinois.edu/releases/other/y3-mlt.

Mapping the underlying density field, including non-visible dark matter, using weak gravitational lensing measurements is now a standard tool in cosmology. Due to its importance to the science results of current and upcoming surveys, the quality of the convergence reconstruction methods should be well understood. We compare three methods: Kaiser–Squires (KS), Wiener filter, and Glimpse. Kaiser–Squires is a direct inversion, not accounting for survey masks or noise. The Wiener filter is well-motivated for Gaussian density fields in a Bayesian framework. Glimpse uses sparsity, aiming to reconstruct non-linearities in the density field. We compare these methods with several tests using public Dark Energy Survey (DES) Science Verification (SV) data and realistic DES simulations. The Wiener filter and Glimpse offer substantial improvements over smoothed Kaiser–Squires with a range of metrics. Both the Wiener filter and Glimpse convergence reconstructions show a 12 per cent improvement in Pearson correlation with the underlying truth from simulations. To compare the mapping methods’ abilities to find mass peaks, we measure the difference between peak counts from simulated ΛCDM shear catalogues and catalogues with no mass fluctuations (a standard data vector when inferring cosmology from peak statistics); the maximum signal-to-noise of these peak statistics is increased by a factor of 3.5 for the Wiener filter and 9 for Glimpse. With simulations, we measure the reconstruction of the harmonic phases; the phase residuals’ concentration is improved 17 per cent by Glimpse and 18 per cent by the Wiener filter. The correlationbetween reconstructions from data and foreground redMaPPer clusters is increased 18 per cent by the Wiener filter and 32 per cent by Glimpse., Monthly Notices of the Royal Astronomical Society, 479 (3), ISSN:0035-8711, ISSN:1365-2966, ISSN:1365-8711

We present the results of the first observations of the emission line galaxies (ELG) of the extended Baryon Oscillation Spectroscopic Survey. From the total 9000 targets, 4600 have been selected from the Dark Energy Survey (DES). In this subsample, the total success rate for redshifts between 0.6 and 1.2 is 71 and 68 per cent for a bright and a faint samples, respectively, including redshifts measured from a single strong emission line. The mean redshift is 0.80 for the bright and 0.87 for the faint sample, while the percentage of unknown redshifts is 15 and 13 per cent, respectively. In both cases, the star contamination is lower than 2 per cent. We evaluate how well the ELG redshifts are measured using the target selection photometry and validating with the spectroscopic redshifts measured by eBOSS. We explore different techniques to reduce the photometric redshift outliers fraction with a comparison between the template fitting, the neural networks and the random forest methods. Finally, we study the clustering properties of the DES SVA1 ELG samples. We select only the most secure spectroscopic redshift in the redshift range 0.6 < z < 1.2, leading to a mean redshift for the bright and faint sample of 0.85 and 0.90, respectively. We measure the projected angular correlation function and obtain a galaxy bias averaging on scales from 1 to 10 Mpc h−1 of 1.58 ± 0.10 for the bright sample and 1.65 ± 0.12 for the faint sample. These values are representative of a galaxy population with MB − log(h) < −20.5, in agreement with what we measure by fitting galaxy templates to the photometric data.

We present a study of quasar selection using the supernova fields of the Dark Energy Survey (DES). 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. In all cases, we considered only objects that appear as point sources in the DES images. We examine color selection methods based on the Wide-field Infrared Survey Explorer (WISE) mid- IR W1 - W2 color, a mixture of WISE and DES colors (g − i and i - W1), and a mixture of Vista Hemisphere Survey and DES colors (g − i and i − K ). For probabilistic quasar selection, we used XDQSO, an algorithm that employs an empirical multi-wavelength flux model of quasars to assign quasar probabilities. Our variability selection uses the multi-band χ2-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, i85% 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 1263 spectroscopically confirmed quasars from three years of OzDES observation in the 30 deg2 of the DES supernova fields. The catalog includes quasars with redshifts up to z4 and brighter than i = 22 mag, although the catalog is not complete up to this magnitude limit.

We study the galaxy populations in 74 Sunyaev–Zeldovich effect selected clusters from the South Pole Telescope survey, which have been imaged in the science verification phase of the Dark Energy Survey. The sample extends up to z ∼ 1.1 with 4 × 1014M ≤ M200 ≤ 3 × 1015M . Using the band containing the 4000 Å break and its redward neighbour, we study the colour–magnitude distributions of cluster galaxies to ∼m∗ + 2, finding that: (1)The intrinsic rest frame g − r colour width of the red sequence (RS) population is ∼0.03 out to z ∼ 0.85 with a preference for an increase to ∼0.07 at z = 1, and (2) the prominence of the RS declines beyond z ∼ 0.6. The spatial distribution of cluster galaxies is well described by the NFW profile out to 4R200 with a concentration of cg = 3.59+0.20 −0.18, 5.37+0.27 −0.24 and 1.38+0.21 −0.19 for the full, the RS and the blue non-RS populations, respectively, but with ∼40 per cent to 55 per cent cluster to cluster variation and no statistically significant redshift or mass trends. The number of galaxies within the virial region N200 exhibits a mass trend indicating that the number of galaxies per unit total mass is lower in the most massive clusters, and shows no significant redshift trend. The RS fraction within R200 is (68 ± 3) per cent at z = 0.46, varies from ∼55 per cent at z = 1 to ∼80 per cent at z = 0.1 and exhibits intrinsic variation among clusters of ∼14 per cent. We discuss a model that suggests that the observed redshift trend in RS fraction favours a transformation time-scale for infalling field galaxies to become RS galaxies of 2–3 Gyr.

Chemically peculiar stars in dwarf galaxies provide a window for exploring the birth environment of stars with varying chemical enrichment. We present a chemical abundance analysis of the brightest star in the newly discovered ultra-faint dwarf galaxy candidate Tucana III. Because it is particularly bright for a star in an ultra-faint Milky Way (MW) satellite, we are able to measure the abundance of 28 elements, including 13 neutron-capture species. This star, DES J235532.66−593114.9 (DES J235532), shows a mild enhancement in neutron-capture elements associated with the r-process and can be classified as an r-I star. DES J235532 is the first r-I star to be discovered in an ultra-faint satellite, and Tuc III is the second extremely low-luminosity system found to contain rprocess enriched material, after Reticulum II. Comparison of the abundance pattern of DES J235532 with r-I and r-II stars found in other dwarf galaxies and in the MW halo suggests a common astrophysical origin for the neutron-capture elements seen in all r-process enhanced stars. We explore both internal and external scenarios for the r-process enrichment of Tuc III and show that with abundance patterns for additional stars, it should be possible to distinguish between them.

We present Magellan/IMACS spectroscopy of the recently discovered Milky Way satellite EridanusII (Eri II). We identify 28 member stars in EriII, from which we measure a systemic radial velocity of vhel = 75.6 1.3 (stat.) 2.0 (sys.) km s-1 and a velocity dispersion of - 6.9+0.9 1.2 km s-1. Assuming that EriII is a dispersion-supported system in dynamical equilibrium, we derive a mass within the half-light radius of - ´ 1.2+ 10 0.3 0.4 7 M, indicating a mass-tolight ratio of - 420+140 210 M/L and confirming that it is a dark matter-dominated dwarf galaxy. From the equivalent width measurements of the Ca triplet lines of 16 red giant member stars, we derive a mean metallicity of [Fe/ H]=−2.38±0.13 and a metallicity dispersion of s[ / ] = - 0.47+ Fe H 0.09 0.12. The velocity of EriII in the Galactic standard of rest frame is vGSR=−66.6 km s-1, indicating that either EriII is falling into the Milky Way potential for the first time or that it has passed the apocenter of its orbit on a subsequent passage. At a Galactocentric distance of 370 kpc, Eri II is one of the Milky Way’s most distant satellites known. Additionally, we show that the bright blue stars previously suggested to be a young stellar population are not associated with EriII. The lack of gas and recent star formation in EriII is surprising given its mass and distance from the Milky Way, and may place constraints on models of quenching in dwarf galaxies and on the distribution of hot gas in the Milky Way halo. Furthermore, the large velocity dispersion of Eri II can be combined with the existence of a central star cluster to constrain massive compact halo object dark matter with mass 10 M.

We present Magellan/IMACS spectroscopy of the recently discovered Milky Way satellite TucanaIII (Tuc III). We identify 26 member stars in TucIII from which we measure a mean radial velocity of vhel=−102.3±0.4 (stat.)±2.0(sys.) km s-1, a velocity dispersion of - 0.1+0.1 0.7 km s-1, and a mean metallicity of = - - [Fe/H] 2.42+0.08 0.07. The upper limit on the velocity dispersion is σ

We report the discovery of the eighth and ninth known Trojans in stable orbits around Neptune’s leading Lagrange point, L4. The objects 2014QO441 and 2014QP441 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-m Blanco telescope at Cerro Tololo Inter-American Observatory. Both are in high-inclination orbits (18°.8 and 19°.4, respectively). With an eccentricity of 0.104, 2014QO441 has the most eccentric orbit of the 11 known stable Neptune Trojans. Here we describe the search procedure and investigate the objects’ long-term dynamical stability and physical properties.

We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model-or machine learning-based photometric redshift methods-ANNZ2, BPZ calibrated against BCC-Ufig simulations, SKYNET, and TPZ-are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z's. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 +/- 0.01 over the range 0.3 < z < 1.3, we construct three tomographic bins with means of z = {0.45;0.67;1.00}. These bins each have systematic uncertainties delta z

We report the discovery of a stellar stream in the Dark Energy Survey Year 1 (Y1A1) data. The discovery was made through simple color–magnitude filters and visual inspection of the Y1A1 data. We refer to this new object as the Phoenix stream, after its resident constellation. After subtraction of the background stellar population we detect a clear signal of a simple stellar population. By fitting the ridge line of the stream in color–magnitude space, we find that a stellar population with age τ=11.5±0.5 Gyr and [Fe/H]

We use the first-year Dark Energy Survey (DES) data down to previously unprobed photometric depths to search for stellar systems in the Galactic halo, therefore complementing the previous analysis of the same data carried out by our group earlier this year. Our search is based on a matched filter algorithm that produces stellar density maps consistent with stellar population models of various ages, metallicities, and distances over the survey area. The most conspicuous density peaks in these maps have been identified automatically and ranked according to their significance and recurrence for different input models. We report the discovery of one additional stellar system besides those previously found by several authors using the same first-year DES data. The object is compact, and consistent with being dominated by an old and metal-poor population. DES 1 is found at high significance and appears in the DES images as a compact concentration of faint blue point sources. Assuming different spatial profile parameterizations, the best-fitting heliocentric distance and total absolute magnitude in the range of 77.6–87.1 kpc and −3.00 MV −2.21, respectively. The half-light radius of this object, rh ∼ 10 pc and total luminosity are consistent with it being a low-mass halo cluster. It is also found to have a very elongated shape ( ∼ 0.57). In addition, our deeper probe of DES first-year data confirms the recently reported satellite galaxy candidate Horologium II as a significant stellar overdensity. We also infer its structural properties and compare them to those reported in the literature.

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 colour cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photo-zs 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 catalogue sampling the redshift range z ∈ [0.2, 0.8]. Our fiducial sample has a comoving space density of 10−3 (h−1 Mpc)−3, and a median photo-z bias (zspec − zphoto) and scatter (σz/(1 + z)) of 0.005 and 0.017, respectively. The corresponding 5σ outlier fraction is 1.4 per cent.We also test our algorithm with Sloan Digital Sky Survey Data Release 8 and Stripe 82 data, and discuss how spectroscopic training can be used to control photo-z biases at the 0.1 per cent level.

We present Magellan/M2FS, Very Large Telescope/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-1 and a velocity dispersion of 3.3  0.7 km s-1. The mass-to-light ratio of Ret II within its half-light radius is 470  210 M L, 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-1, 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 log10 (J) 18.8 0.6 GeV cm =  2 -5 within 0 ◦. 2, indicating that the predicted gamma-ray flux from dark matter annihilation in Ret II is lower than that of several other dwarf galaxies.

Due to their proximity, high dark-matter (DM) content, and apparent absence of non-thermal processes, Milky Way dwarf spheroidal satellite galaxies (dSphs) are excellent targets for the indirect detection of DM. Recently, eight new dSph candidates were discovered using the first year of data from the Dark Energy Survey (DES). We searched for gamma-ray emission coincident with the positions of these new objects in six years of Fermi Large Area Telescope data. We found no significant excesses of gamma-ray emission. Under the assumption that the DES candidates are dSphs with DM halo properties similar to the known dSphs, we computed individual and combined limits on the velocity-averaged DM annihilation cross section for these new targets. If the estimated DM content of these dSph candidates is confirmed, they will constrain the annihilation cross section to lie below the thermal relic cross section for DM particles with masses 20 GeV annihilating via the bb¯ or τ+τ− channels.

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 lowerconfidence 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 > −4.7mag) and span a range of physical sizes (17 pc < r1/2 < 181 pc) and heliocentric distances (25 kpc < De < 214 kpc). All of the new systems have central surface brightnesses consistent with known ultrafaint dwarf galaxies (μ  27.5mag 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 < 10−3) 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.

The Dark Energy Camera has captured a large set of images as part of Science Verification (SV) for the Dark Energy Survey (DES). The SV footprint covers a large portion of the outer LargeMagellanic Cloud (LMC), providing photometry 1.5 mag fainter than the main sequence turn-off of the oldest LMC stellar population.We derive geometrical and structural parameters for various stellar populations in the LMC disc. For the distribution of all LMC stars, we find an inclination of i = −38. ◦ 14 ± 0. ◦ 08 (near side in the north) and a position angle for the line of nodes of θ0 = 129. ◦ 51 ± 0. ◦ 17. We find that stars younger than ∼4 Gyr are more centrally concentrated than older stars. Fitting a projected exponential disc shows that the scale radius of the old populations is R>4 Gyr = 1.41 ± 0.01 kpc, while the younger population has R

We present spectroscopic confirmation of two new gravitationally lensed quasars, discovered in the Dark Energy Survey (DES) and Wide-field Infrared Survey Explorer (WISE) based on their multiband photometry and extended morphology in DES images. Images of DES J0115−5244 show a red galaxy with two blue point sources at either side, which are images of the same quasar at zs = 1.64 as obtained by our long-slit spectroscopic data. The Einstein radius estimated from the DES images is 0.51 arcsec. DES J2146−0047 is in the area of overlap between DES and the Sloan Digital Sky Survey (SDSS). Two blue components are visible in the DES and SDSS images. The SDSS fibre spectrum shows a quasar component at zs = 2.38 and absorption by Mg II and Fe II at zl = 0.799, which we tentatively associate with the foreground lens galaxy. Our long-slit spectra show that the blue components are resolved images of the same quasar. The Einstein radius is 0.68 arcsec, corresponding to an enclosed mass of 1.6 × 1011M . Three other candidates were observed and rejected, two being low-redshift pairs of starburst galaxies, and one being a quasar behind a blue star. These first confirmation results provide an important empirical validation of the data mining and model-based selection that is being applied to the entire DES data set.

El descubrimiento de la materia oscura y la energía oscura en el siglo XX ha supuesto una revolución para la cosmología y nos ha permitido entender que la contribución de las estrellas y los planetas al contenido energético del Universo es despreciable. La naturaleza de estas dos componentes es completamente desconocida y entenderla es uno de los interrogantes más importantes a los que se enfrenta la física a principios del siglo XXI. Las principales técnicas de estudio de la energía oscura son el diagrama de Hubble de Supernovas tipo Ia, la tomografía de la distribución de materia usando lentes gravitacionales (Weak Lensing), la abundancia de cúmulos de galaxias y las Oscilaciones Acústicas de Bariones (BAO, siglas de Baryonic Acoustic Oscillations), en las que se centra esta tesis. Estas representan una sobreabundancia de materia a una escala característica, debido a la propagación de ondas sonoras en el Universo primitivo. Su medida se efectúa usando la distribución de materia visible. La evolución temporal de dicha escala es función de los parámetros cosmológicos. En esta tesis se presenta una nueva técnica para determinar la escala BAO que se podría aplicar en cualquier cartografiado de galaxias con suficiente estadística. Esta técnica ha sido probada en simulaciones de DES y con los datos reales de SDSS, demostrando que es viable y consiguiendo resultados competitivos. En el capítulo 2 se describirá con más detalle el modelo estándar ΛCDM, así como las medidas de distancias y la formación de estructuras en el Universo. El capítulo 3 está dedicado a las Oscilaciones Acústicas de Bariones y su uso como observable cosmológico en cartografiados de galaxias. Finalmente, en el capítulo 4 se presentará el método para la extracción de información cosmológica a partir de cartografiados fotométricos, para terminar con los resultados obtenidos con las simulaciones del Dark Energy Survey en el capítulo 5, y con los datos del Sloan Digital Sky Survey en el capítulo 6.

Chen, A., et al. DES Collaboration, We study a phenomenological class of models where dark matter converts to dark radiation in the low redshift epoch. This class of models, dubbed DMDR, characterizes the evolution of comoving dark-matter density with two extra parameters, and may be able to help alleviate the observed discrepancies between early and late-time probes of the Universe. We investigate how the conversion affects key cosmological observables such as the cosmic microwave background (CMB) temperature and matter power spectra. Combining 3x2pt data from Year 1 of the Dark Energy Survey, Planck-2018 CMB temperature and polarization data, supernovae (SN) Type Ia data from Pantheon, and baryon acoustic oscillation (BAO) data from BOSS DR12, MGS and 6dFGS, we place new constraints on the amount of dark matter that has converted to dark radiation and the rate of this conversion. The fraction of the dark matter that has converted since the beginning of the Universe in units of the current amount of dark matter, ζ, is constrained at 68% confidence level to be, he DES data management system is supported by the National Science Foundation under Grants No. AST-1138766 and No. AST-1536171. The DES participants from Spanish institutions are partially supported by MICINN under Grants No. ESP2017-89838, No. PGC2018-094773, No. PGC2018-102021, No. SEV-2016-0588, No. SEV-2016-0597, and No. MDM-2015-0509, some of which include ERDF funds from the European Union. I. F. A. E. is partially funded by the CERCA program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Program (Grant No. FP7/2007-2013) including ERC Grants Agreement No. 240672, No. 291329, and No. 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) do e-Universo (CNPq Grant No. 465376/2014-2).

En este trabajo se presenta uno de los primeros resultados cient´ıficos del proyecto Southern H-ATLAS Regions Ks-band Survey (SHARKS), centrado en el estudio de galaxias lejanas en el infrarrojo cercano. Se emplea el primer Data Release del proyecto (DR1), que se publicar´a pr´oximamente, para desarrollar un algoritmo capaz de seleccionar los Objetos Extremadamente Rojos (del ingl´es, EROs) presentes en el cat´alogo. Estos objetos se ca racterizan por ser brillantes en el infrarrojo cercano, pero muy tenues en el visible. Por lo tanto, se combinan observaciones de SHARKS, en el infrarrojo cercano, con datos en el ´optico, en este caso, proporcionados por el Dark Energy Survey (DES). Adem´as, dado que la reducci´on de im´agenes del DR1 de SHARKS todav´ıa no se ha hecho p´ublica, se dedica la primera parte de este trabajo a explicar en detalle las distintas comprobacio nes llevadas a cabo para validar los datos empleados durante el mismo. En concreto, se analiza la densidad superficial de objetos, la calidad y profundidad de la imagen con siderada, y la correcta calibraci´on fotom´etrica y astrom´etrica del cat´alogo. Una vez se verifican todos los aspectos comentados, se da paso a la b´usqueda de EROs. Finalmente, se comparan los resultados obtenidos con trabajos previos, para verificar la validez de los mismos. In this work, one of the first scientific results from the Southern H-ATLAS Regions Ks-band Survey (SHARKS) project is presented, focused on the study of distant galaxies in the near-infrared (NIR). The first Data Release of the project (DR1), which will be published very soon, is used to develop an algorithm to select Extremely Red Objects (EROs) present in the catalogue. These are defined as galaxies bright in the NIR, but very faint in the visible. To do this, SHARKS observations are combined with optical data, in this case, provided by the Dark Energy Survey (DES). In addition, as this is the first scientific analysis done on SHARKS, the first part of this work is dedicated to validate the quality of SHARKS DR1. In particular, surface density of objects, image quality and depth, and the photometric and astrometric calibration of the survey are tested. Once data is verified, the quest for EROs begins. Finally, the results obtained are compared with previous works, to verify their validity.

This project focuses on obtaining the photometric redshift (photo-z) for galaxies in the first data release (DR1) of the Southern H-ATLAS Regions Ks Band Survey (SHARKS). In particular, we will study the effect of incorporating the Ks-band in the photo-z estimates. A limiting factor in obtaining the redshift by photometric means is the lack of spectral coverage, especially when the SHARKS data are only in the Ks-band. Because of this, we will make use of an astronomical catalog that covers the same region of the sky in the optical range, the Dark Energy Survey (DES), in particular DES-DR2. Before proceeding to the photo-z calculation, we study the calibration of the SHARKS-DR1 data. For this purpose, we will proceed with a near-infrared astronomical catalog that will act as a reference, 2MASS. In this section of the project, using a linear regression between the magnitudes of both catalogs, we will measure the calibration difference between them. In this case, we expect only to measure the difference between the calibration in the Vega and AB system. As for the photometric redshift, it is noteworthy that since this is the first time that these are calculated with SHARKS data, we have focused on a subsample where we have selected only galaxies with a distinct SHARKS-DES detection. For the selection of galaxies, we will use color-color space separation that occurs when using infrared bands. The calculation of the photometric redshift has been performed using the Lephare software. Before the execution, we must define the library of galaxy model templates that we will use (SEDs, Spectral Energy Distribution), here we will use a library of 8 templates. For their subsequent convolution, we will also introduce the filters with which we took the measurements, i.e. those of the DECam and VIRCAM cameras. Then, we proceed to calculate the magnitudes as a function of the redshift for the templates, and finally, we perform a minimization of the reshift for the templates. Finally, a minimization by the 2 fitting method is carried out to obtain the redshift and the template that best fits the observed galaxy. To validate the results, we calculate statistical metrics of the bias and dispersion of the photo-z, concerning a small calibration sample with spectroscopic redshift, limited to low redshift. Next, we compare the overall redshift distributions obtained with and without using the Ks-band and look at some examples of outliers. In general, we find that using SHARKS Ks-band improves the photo-z estimates, compared to the similar estimates using only DES data, through a decrease in the number of catastrophic results (outliers).