Suchergebnisse

With the dramatic rise in high-quality galaxy data expected from Euclid and Vera C. Rubin Observatory, there will be increasing demand for fast high-precision methods for measuring galaxy fluxes. These will be essential for inferring the redshifts of the galaxies. In this paper, we introduce LUMOS, a deep learning method to measure photometry from galaxy images. LUMOS builds on BKGNET, an algorithm to predict the background and its associated error, and predicts the background-subtracted flux probability density function. We have developed LUMOS for data from the Physics of the Accelerating Universe Survey (PAUS), an imaging survey using a 40 narrow-band filter camera (PAUCam). PAUCam images are affected by scattered light, displaying a background noise pattern that can be predicted and corrected for. On average, LUMOS increases the SNR of the observations by a factor of 2 compared to an aperture photometry algorithm. It also incorporates other advantages like robustness towards distorting artefacts, e.g. cosmic rays or scattered light, the ability of deblending and less sensitivity to uncertainties in the galaxy profile parameters used to infer the photometry. Indeed, the number of flagged photometry outlier observations is reduced from 10 to 2 per cent, comparing to aperture photometry. Furthermore, with LUMOS photometry, the photo-z scatter is reduced by ≈10 per cent with the Deepz machine-learning photo-z code and the photo-z outlier rate by 20 per cent. The photo-z improvement is lower than expected from the SNR increment, however, currently the photometric calibration and outliers in the photometry seem to be its limiting factor. ; The PAU Survey is partially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2017-89838, PGC2018-094773, PGC2018-102021, SEV-2016-0588, SEV-2016-0597, MDM-2015-0509, PID2019-111317GB-C31 and Juan de la Cierva fellowship and LACEGAL and EWC Marie Sklodowska-Curie grant No 734374 and no.776247 with ERDF funds from the EU Horizon 2020 Programme, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA and Beatriu de Pinos program of the Generalitat de Catalunya. Funding for PAUS has also been provided by Durham University (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scientific Research (NWO) Vici grant 639.043.512), Bochum University (via a Heisenberg grant of the Deutsche Forschungsgemeinschaft (Hi 1495/5-1) as well as an ERC Consolidator Grant (No. 770935)), University College London, Portsmouth support through the Royal Society Wolfson fellowship and from the European Union's Horizon 2020 research and innovation programme under the grant agreement No 776247 EWC. ; Peer reviewed

In this paper, we introduce the DEEPZ deep learning photometric redshift (photo-z) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. DEEPZ reduces the σ68 scatter statistic by 50 per cent at iAB = 22.5 compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-z scatter by 10 per cent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys. ; The PAU Survey is partially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2017-89838, PGC2018-094773, SEV-2016-0588, SEV-2016-0597, and MDM2015-0509, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA program of the Generalitat de Catalunya. Funding for PAUS has also been provided by Durham University (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scientific Research (NWO) Vici grant 639.043.512), University College London and from the European Union's Horizon 2020 research and innovation programme under the grant agreement No. 776247 EWC. HH is supported by a Heisenberg grant of the Deutsche Forschungsgemeinschaft (Hi 1495/5-1) as well as an ERC Consolidator Grant (No. 770935). ; Peer reviewed

In any imaging survey, measuring accurately the astronomical background light is crucial to obtain good photometry. This paper introduces BKGNET, a deep neural network to predict the background and its associated error. BKGNET has been developed for data from the Physics of the Accelerating Universe Survey (PAUS), an imaging survey using a 40 narrow-band filter camera (PAUCam). The images obtained with PAUCam are affected by scattered light: an optical effect consisting of light multiply reflected that deposits energy in specific detector regions affecting the science measurements. Fortunately, scattered light is not a random effect, but it can be predicted and corrected for. We have found that BKGNET background predictions are very robust to distorting effects, while still being statistically accurate. On average, the use of BKGnet improves the photometric flux measurements by 7 per cent and up to 20 per cent at the bright end. BKGNET also removes a systematic trend in the background error estimation with magnitude in the i band that is present with the current PAU data management method. With BKGNET, we reduce the photometric redshift outlier rate by 35 per cent for the best 20 per cent galaxies selected with a photometric quality parameter. ; Funding for PAUS has been provided by Durham University (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scientific Research (NWO) Vici grant 639.043.512) and University College London. The PAUS participants from Spanish institutions are partially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA program of the Generalitat de Catalunya. The PAU data center is hosted by the Port d'Informacio Cientifica (PIC), maintained through a collaboration of CIEMAT and IFAE, with additional support from Universitat Autonoma de Barcelona and ERDF. CosmoHub has been developed by PIC and was partially funded by the 'Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion program of the Spanish government. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan V GPU used for this research. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 776247. AA is supported by a Royal Society Wolfson Fellowship. MS has been supported by the National Science Centre (grant UMO2016/23/N/ST9/02963). ; Peer reviewed

UK Space Agency ; European Research Council ; UK Science & Technology Facilities Council ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ; U.S. Department of Energy ; U.S. National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Argonne National Laboratory ; University of California at Santa Cruz ; University of Cambridge ; Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid ; University of Chicago ; University College London ; DES-Brazil Consortium ; University of Edinburgh ; Eidgenossische Technische Hochschule (ETH) Zurich ; Fermi National Accelerator Laboratory ; University of Illinois at Urbana-Champaign ; Institut de Ciencies de l'Espai (IEEC/CSIC) ; Institut de Fisica d'Altes Energies ; Lawrence Berkeley National Laboratory ; Ludwig-Maximilians Universitat Munchen ; associated Excellence Cluster Universe ; University of Michigan ; National Optical Astronomy Observatory ; University of Nottingham ; Ohio State University ; University of Pennsylvania ; University of Portsmouth ; SLAC National Accelerator Laboratory ; Stanford University ; University of Sussex ; Texas AM University ; OzDES Membership Consortium ; National Science Foundation ; MINECO ; European Union ; CERCA programme of the Generalitat de Catalunya ; European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) including ERC grant ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) ; U.S. Department of Energy, Office of Science, Office of High Energy Physics ; United States Government ; UK Space Agency: ST/K00283X/1 ; UK Science & Technology Facilities Council: ST/K0090X/1 ; CNPq: 465376/2014-2 ; National Science Foundation: AST-1138766 ; National Science Foundation: AST-1536171 ; MINECO: AYA2015-71825 ; MINECO: ESP2015-66861 ; MINECO: FPA2015-68048 ; MINECO: SEV-2016-0588 ; MINECO: SEV-2016-0597 ; MINECO: MDM-2015-0509 ; European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) including ERC grant: 240672 ; European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) including ERC grant: 291329 ; European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) including ERC grant: 306478 ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO): CE110001020 ; U.S. Department of Energy, Office of Science, Office of High Energy Physics: DE-AC02-07CH11359 ; Mock catalogues are a crucial tool in the analysis of galaxy surveys data, both for the accurate computation of covariance matrices, and for the optimization of analysis methodology and validation of data sets. In this paper, we present a set of 1800 galaxy mock catalogues designed to match the Dark Energy Survey Year-1 BAO sample (Crocce et al. 2017) in abundance, observational volume, redshift distribution and uncertainty, and redshift-dependent clustering. The simulated samples were built upon HALOGEN (Avila et al. 2015) halo catalogues, based on a 2LPTdensity field with an empirical halo bias, For each of them, a light-cone is constructed by the superposition of snapshots in the redshift range 0.45 < z < 1.4. Uncertainties introduced by so-called photometric redshifts estimators were modelled with a double-skewed-Gaussian curve fitted to the data. We populate haloes with galaxies by introducing a hybrid halo occupation distribution-halo abundance matching model with two free parameters. These are adjusted to achieve a galaxy bias evolution b(z(ph)) that matches the data at the 1 sigma level in the range 0.6 < z(ph) < 1.0. We further analyse the galaxy mock catalogues and compare their clustering to the data using the angular correlation function w(theta), the comoving transverse separation clustering xi(mu < 0.8)(S-perpendicular to) and the angular power spectrum C-l, finding them in agreement. This is the first large set of three-dimensional {RA,Dec.,z} galaxy mock catalogues able to simultaneously accurately reproduce the photometric redshift uncertainties and the galaxy clustering.

Spanish Ministerio de Economia y Competitividad (MINECO) ; Centro de Excelencia Severo Ochoa ; U.S. Department of Energy ; U.S. National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Argonne National Laboratory ; University of California at Santa Cruz ; University of Cambridge ; Centro de Investigaciones Energeticas ; Medioambientales y Tecnologicas-Madrid ; University of Chicago ; University College London ; DES-Brazil Consortium ; University of Edinburgh ; Eidgenossische Technische Hochschule (ETH) Zurich ; Fermi National Accelerator Laboratory ; University of Illinois at Urbana-Champaign ; Institut de Ciencies de l'Espai (IEEC/CSIC) ; Institut de Fisica d'Altes Energies ; Lawrence Berkeley National Laboratory ; Ludwig-Maximilians Universitar Munchen ; Excellence Cluster Universe ; University of Michigan ; National Optical Astronomy Observatory ; University of Nottingham ; Ohio State University ; University of Pennsylvania ; University of Portsmouth ; SLAC National Accelerator Laboratory ; Stanford University ; University of Sussex ; Texas AM University ; OzDES Membership Consortium ; National Science Foundation ; MINECO ; European Research Council under the European Union ; NASA ; Science and Technology Facilities Council ; ICREA ; Spanish Ministerio de Economia y Competitividad (MINECO): FPA2012-39684 ; Centro de Excelencia Severo Ochoa: SEV-2012-0234 ; Centro de Excelencia Severo Ochoa: SEV-2012-0249 ; Centro de Investigaciones Energeticas: SEV-2012-0234 ; Centro de Investigaciones Energeticas: SEV-2012-0249 ; National Science Foundation: AST-1138766 ; MINECO: AYA2012-39559 ; MINECO: ESP2013-48274 ; MINECO: FPA2013-47986 ; European Research Council under the European Union: 240672 ; European Research Council under the European Union: 291329 ; European Research Council under the European Union: 306478 ; NASA: PF5-160138 ; Science and Technology Facilities Council: ST/M001334/1 ; Small temperature anisotropies in the cosmic microwave background (CMB) can be sourced by density perturbations via the late-time integrated Sachs-Wolfe (ISW) effect. Large voids and superclusters are excellent environments to make a localized measurement of this tiny imprint. In some cases excess signals have been reported. We probed these claims with an independent data set, using the first year data of the Dark Energy Survey (DES) in a different footprint, and using a different superstructure finding strategy. We identified 52 large voids and 102 superclusters at redshifts 0.2 < z < 0.65. We used the Jubilee simulation to a priori evaluate the optimal ISW measurement configuration for our compensated top-hat filtering technique, and then performed a stacking measurement of the CMB temperature field based on the DES data. For optimal configurations, we detected a cumulative cold imprint of voids with Delta T-f approximate to -5.0 +/- 3.7 mu K and a hot imprint of superclusters Delta T-f approximate to 5.1 +/- 3.2 mu K; this is similar to 1.2 sigma higher than the expected vertical bar Delta T-f vertical bar approximate to 0.6 mu K imprint of such superstructures in Lambda cold dark matter (Lambda CDM). If we instead use an a posteriori selected filter size (R/R-v = 0.6), we can find a temperature decrement as large as Delta T-f approximate to -9.8 +/- 4.7 mu K for voids, which is similar to 2 sigma above Lambda CDM expectations and is comparable to previous measurements made using Sloan Digital Sky Survey superstructure data.

Spanish Ministerio de Ciencia e Innovacion (MICINN) ; Ramon y Cajal MICINN programme ; US Department of Energy ; US National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Argonne National Laboratory ; University of California at Santa Cruz ; University of Cambridge ; Centro de Investigaciones Energeticas ; Medioambientales y Tecnologicas-Madrid ; University of Chicago ; University College London ; DES-Brazil Consortium ; University of Edinburgh ; Eidgenossische Technische Hochschule (ETH) Zurich ; Fermi National Accelerator Laboratory ; University of Illinois at Urbana-Champaign ; Institut de Ciencies de l'Espai (IEEC/CSIC) ; Institut de Fisica d'Altes Energies ; Lawrence Berkeley National Laboratory ; Ludwig-Maximilians Universitat Munchen ; associated Excellence Cluster Universe ; University of Michigan ; National Optical Astronomy Observatory ; University of Nottingham ; Ohio State University ; University of Pennsylvania ; University of Portsmouth ; SLAC National Accelerator Laboratory ; Stanford University ; University of Sussex ; Texas AM University ; OzDES Membership Consortium ; National Science Foundation ; MINECO ; Centro de Excelencia Severo Ochoa ; European Research Council under the European Union ; Perren Fund ; European Research Council Advanced Grant ; ICREA ; Science and Technology Facilities Council ; Spanish Ministerio de Ciencia e Innovacion (MICINN): 200850I176 ; Spanish Ministerio de Ciencia e Innovacion (MICINN): AYA2009-13936 ; Spanish Ministerio de Ciencia e Innovacion (MICINN): AYA2012-39620 ; Spanish Ministerio de Ciencia e Innovacion (MICINN): AYA2013-44327 ; Spanish Ministerio de Ciencia e Innovacion (MICINN): ESP2013-48274 ; Spanish Ministerio de Ciencia e Innovacion (MICINN): ESP2014-58384 ; Spanish Ministerio de Ciencia e Innovacion (MICINN): CSD2007-00060 ; Spanish Ministerio de Ciencia e Innovacion (MICINN): 2009-SGR-1398 ; National Science Foundation: AST-1138766 ; MINECO: ESP2013-48274 ; MINECO: AYA2012-39559 ; MINECO: FPA2013-47986 ; Centro de Excelencia Severo Ochoa: SEV-2012-0234 ; European Research Council under the European Union: 240672 ; European Research Council under the European Union: 291329 ; European Research Council under the European Union: 306478 ; European Research Council Advanced Grant: FP7/291329 ; : AECT-2006-2-0011 ; : AECT-2015-1-0013 ; Science and Technology Facilities Council: ST/M001334/1 ; It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (kappa(WL)) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the counts-in-cells (CiC) method. We use maps of galaxies and weak lensing convergence produced from the Dark Energy Survey Science Verification data over 139 deg(2). We test whether the underlying density contrast is well described by a lognormal distribution for the galaxies, the convergence and their joint PDF. We confirm that the galaxy density contrast distribution is well modelled by a lognormal PDF convolved with Poisson noise at angular scales from 10 to 40 arcmin (corresponding to physical scales of 3-10 Mpc). We note that as kappa(WL) is a weighted sum of the mass fluctuations along the line of sight, its PDF is expected to be only approximately lognormal. We find that the kappa(WL) distribution is well modelled by a lognormal PDF convolved with Gaussian shape noise at scales between 10 and 20 arcmin, with a best-fitting chi(2)/dof of 1.11 compared to 1.84 for a Gaussian model, corresponding to p-values 0.35 and 0.07, respectively, at a scale of 10 arcmin. Above 20 arcmin a simple Gaussian model is sufficient. The joint PDF is also reasonably fitted by a bivariate lognormal. As a consistency check, we compare the variances derived from the lognormal modelling with those directly measured via CiC. Our methods are validated against maps from the MICE Grand Challenge N-body simulation.

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; European Research Council ; US Department of Energy ; US National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Collaborating Institutions in the Dark Energy Survey ; National Science Foundation ; MINECO ; Centro de Excelencia Severo Ochoa ; European Research Council under the European Union ; ICREA ; Science and Technology Facilities Council ; European Research Council: ERC-StG-335936 ; National Science Foundation: AST-1138766 ; MINECO: AYA2012-39559 ; MINECO: ESP2013-48274 ; MINECO: FPA2013-47986 ; Centro de Excelencia Severo Ochoa: SEV-2012-0234 ; European Research Council under the European Union: 240672 ; European Research Council under the European Union: 291329 ; European Research Council under the European Union: 306478 ; Science and Technology Facilities Council: ST/N000668/1 ; Science and Technology Facilities Council: ST/K00090X/1 ; 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] similar or equal to -0.7 beyond 8 kpc from the LMC centre. The age distribution has two peaks at similar or equal to 1.2 and similar or equal to 2.7 Gyr.

U.S. Department of Energy ; U.S. National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Collaborating Institutions in the Dark Energy Survey ; National Science Foundation ; MINECO ; Centro de Excelencia Severo Ochoa ; European Research Council under the European Union Seventh Framework Programme (FP7) ERC ; Science and Technology Facilities Council ; ICREA ; National Science Foundation: AST-1138766 ; MINECO: AYA2012-39559 ; MINECO: ESP201348274 ; MINECO: FPA2013-47986 ; Centro de Excelencia Severo Ochoa: SEV-2012-0234 ; European Research Council under the European Union Seventh Framework Programme (FP7) ERC: 240672 ; European Research Council under the European Union Seventh Framework Programme (FP7) ERC: 291329 ; European Research Council under the European Union Seventh Framework Programme (FP7) ERC: 306478 ; Science and Technology Facilities Council: ST/M001334/1 ; Measurements of the galaxy stellar mass function are crucial to understand the formation of galaxies in the Universe. In a hierarchical clustering paradigm, it is plausible that there is a connection between the properties of galaxies and their environments. Evidence for environmental trends has been established in the local Universe. The Dark Energy Survey (DES) provides large photometric data sets that enable further investigation of the assembly of mass. In this study, we use similar to 3.2 million galaxies from the (South Pole Telescope) SPTEast field in the DES science verification (SV) data set. From grizY photometry, we derive galaxy stellar masses and absolute magnitudes, and determine the errors on these properties using Monte Carlo simulations using the full photometric redshift probability distributions. We compute galaxy environments using a fixed conical aperture for a range of scales. We construct galaxy environment probability distribution functions and investigate the dependence of the environment errors on the aperture parameters. We compute the environment components of the galaxy stellar mass function for the redshift range 0.15 < z < 1.05. For z < 0.75, we find that the fraction of massive galaxies is larger in high-density environment than in lowdensity environments. We show that the low-density and high-density components converge with increasing redshift up to z similar to 1.0 where the shapes of the mass function components are indistinguishable. Our study shows how high-density structures build up around massive galaxies through cosmic time.

This article has been accepted for publication in Monthly Notices of the Royal Astronomical Soicety © 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved ; We present results of the first dynamical stream fits to the recently discovered Tucana III stream. These fits assume a fixed Milky Way potential and give proper motion predictions, which can be tested with the upcoming Gaia Data Release 2 (DR2). These fits reveal that Tucana III is on an eccentric orbit around the Milky Way and, more interestingly, that Tucana III passed within 15 kpc of the Large Magellanic Cloud (LMC) approximately 75 Myr ago. Given this close passage, we fit the Tucana III stream in the combined presence of the Milky Way and the LMC. We find that the predicted proper motions depend on the assumed mass of the LMC and that the LMC can induce a substantial proper motion perpendicular to the stream track. A detection of this misalignment will directly probe the extent of the LMC's influence on our Galaxy, and has implications for nearly all methods which attempt to constraint the Milky Way potential. Such a measurement will be possible with the upcoming Gaia DR2, allowing for a measurement of the LMC's mass. ; DE and VB acknowledge that the research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007- 2013) / ERC Grant Agreement no. 308024. EB acknowledges financial support from the European Research Council (StG-335936). ABP acknowledges generous support from the George P. and Cynthia Woods Institute for Fundamental Physics and Astronomy at Texas A&M University. 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, Fundacâo 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, Tecnología e Inovacâo, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey

Reproduced with permission of AAS ; We present chemical abundance measurements of three stars in the ultrafaint dwarf galaxy Horologium I, a Milky Way satellite discovered by the Dark Energy Survey. Using high-resolution spectroscopic observations, we measure the metallicity of the three stars, as well as abundance ratios of several α-elements, iron-peak elements, and neutron-capture elements. The abundance pattern is relatively consistent among all three stars, which have a low average metallicity of [Fe/H] ∼ -2.6 and are not α-enhanced ([α/Fe] ∼ 0.0). This result is unexpected when compared to other low-metallicity stars in the Galactic halo and other ultrafaint dwarfs and suggests the possibility of a different mechanism for the enrichment of Hor I compared to other satellites. We discuss possible scenarios that could lead to this observed nucleosynthetic signature, including extended star formation, enrichment by a Population III supernova, and or an association with the Large Magellanic Cloud ; 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 DES data management system is supported by the National Science Foundation under grant nos. AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV- 2012-0234, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE 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 (FP7/2007- 2013), including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project no. CE110001020

U.S. Department of Energy ; U.S. National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology andAstro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Ministerio da Ciencia ; Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Collaborating Institutions in the Dark Energy Survey ; National Science Foundation ; MINECO ; Centro de Excelencia Severo Ochoa ; European Research Council under the European Union's Seventh Framework Programme (FP7)/including ERC grant ; NASA through the Einstein Fellowship Program ; ICREA ; Science and Technology Facilities Council ; National Science Foundation: AST-1138766 ; MINECO: AYA2012-39559 ; MINECO: ESP2013-48274 ; MINECO: FPA2013-47986 ; Centro de Excelencia Severo Ochoa: SEV-2012-0234 ; European Research Council under the European Union's Seventh Framework Programme (FP7)/including ERC grant: 240672 ; European Research Council under the European Union's Seventh Framework Programme (FP7)/including ERC grant: 291329 ; European Research Council under the European Union's Seventh Framework Programme (FP7)/including ERC grant: 306478 ; NASA through the Einstein Fellowship Program: PF5-160138 ; Science and Technology Facilities Council: ST/L000768/1 ; Science and Technology Facilities Council: ST/M001334/1 ; Cosmic voids are usually identified in spectroscopic galaxy surveys, where 3D information about the large-scale structure of the Universe is available. Although an increasing amount of photometric data is being produced, its potential for void studies is limited since photometric redshifts induce line-of-sight position errors of >= 50 Mpc h(-1)which can render many voids undetectable. We present a new void finder designed for photometric surveys, validate it using simulations, and apply it to the high-quality photo-z redMaGiC galaxy sample of the DES Science Verification data. The algorithm works by projecting galaxies into 2D slices and finding voids in the smoothed 2D galaxy density field of the slice. Fixing the line-of-sight size of the slices to be at least twice the photo-z scatter, the number of voids found in simulated spectroscopic and photometric galaxy catalogues is within 20 per cent for all transverse void sizes, and indistinguishable for the largest voids (R-v >= 70 Mpc h(-1)). The positions, radii, and projected galaxy profiles of photometric voids also accurately match the spectroscopic void sample. Applying the algorithm to the DES-SV data in the redshift range 0.2 < z < 0.8, we identify 87 voids with comoving radii spanning the range 18-120 Mpc h(-1), and carry out a stacked weak lensing measurement. With a significance of 4.4 sigma, the lensing measurement confirms that the voids are truly underdense in the matter field and hence not a product of Poisson noise, tracer density effects or systematics in the data. It also demonstrates, for the first time in real data, the viability of void lensing studies in photometric surveys.

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ; U.S. Department of Energy ; U.S. National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Fending Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Collaborating Institutions in the Dark Energy Survey ; Argonne National Laboratory ; University of California at Santa Cruz ; University of Cambridge ; Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid ; University of Chicago ; University College London ; DES-Brazil Consortium ; University of Edinburgh ; Eidgenossische Technische Hochschule (ETH) Zurich ; Fermi National Accelerator Laboratory ; University of Illinois at Urbana-Champaign ; Institut de Ciencies de l'Espai (IEEC/CSIC) ; Institut de Fisica d'Altes Energies ; Lawrence Berkeley National Laboratory ; Ludwig-Maximilians Universitat Munchen ; associated Excellence Cluster Universe ; University of Michigan ; National Optical Astronomy Observatory ; University of Nottingham ; Ohio State University ; University of Pennsylvania ; University of Portsmouth ; SLAC National Accelerator Laboratory, Stanford University ; University of Sussex ; Texas AM University ; OzDES Membership Consortium ; National Science foundation ; MINECO ; European Union ; CERCA program of the Generalitat de Catalunya ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013) ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) ; U.S. Department of Energy, Office of Science, Office of High Energy Physics ; CNPq: 141935/2014-6 ; CNPq: 465376/2014-2 ; National Science foundation: AST-1138766 ; National Science foundation: AST-1536171 ; MINECO: AYA2015-71825 ; MINECO: ESP2015-66861 ; MINECO: FPA2015-68048 ; MINECO: SEV-2016-0588 ; MINECO: SEV-2016-0597 ; MINECO: MDM-2015-0509 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 240672 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 291329 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 306478 ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO): CE110001020 ; U.S. Department of Energy, Office of Science, Office of High Energy Physics: DE-AC02-07CH11359 ; We use data from the first-year observations of the DES collaboration to measure the galaxy angular power spectrum (APS), and search for its BAO feature. We test our methodology in a sample of 1800 DES Y1-like mock catalogues. We use the pseudo-C-l, method to estimate the APS and the mock catalogues to estimate its covariance matrix. We use templates to model the measured spectra and estimate template parameters firstly from the G's of the mocks using two different methods, a maximum likelihood estimator and a Markov Chain Monte Carlo, finding consistent results with a good reduced chi(2). Robustness tests are performed to estimate the impact of different choices of settings used in our analysis. Finally, we apply our method to a galaxy sample constructed from DES Y1 data specifically for LSS studies. This catalogue comprises galaxies within an effective area of 1318 deg(2) and 0.6 < z < 1.0. We find that the DES Y1 data favour a model with BAO at the 2.6 sigma C.L. However, the goodness of fit is somewhat poor, with chi(2)/(d.o.f.) = 1.49. We identify a possible cause showing that using a theoretical covariance matrix obtained from C-l's that are better adjusted to data results in an improved value of chi(2)/(dof) = 1.36 which is similar to the value obtained with the real-space analysis. Our results correspond to a distance measurement of D-A (Z(eff) = 0.81)/r(d) = 10.65 +/- 0.49, consistent with the main DES BAO findings. This is a companion paper to the main DES BAO article showing the details of the harmonic space analysis.

Despite vast improvements in the measurement of the cosmological parameters, the nature of dark energy and an accurate value of the Hubble constant (H-0) in the Hubble-Lemaitre law remain unknown. To break the current impasse, it is necessary to develop as many independent techniques as possible, such as the use of Type II supernovae (SNe II). The goal of this paper is to demonstrate the utility of SNe II for deriving accurate extragalactic distances, which will be an asset for the next generation of telescopes where more-distant SNe II will be discovered. More specifically, we present a sample from the Dark Energy Survey Supernova Program (DES-SN) consisting of 15 SNe II with photometric and spectroscopic information spanning a redshift range up to 0.35. Combining our DES SNe with publicly available samples, and using the standard candle method (SCM), we construct the largest available Hubble diagram with SNe II in the Hubble flow (70 SNe II) and find an observed dispersion of 0.27 mag. We demonstrate that adding a colour term to the SN II standardization does not reduce the scatter in the Hubble diagram. Although SNe II are viable as distance indicators, this work points out important issues for improving their utility as independent extragalactic beacons: find new correlations, define a more standard subclass of SNe II, construct new SN II templates, and dedicate more observing time to high-redshift SNe II. Finally, for the first time, we perform simulations to estimate the redshift-dependent distance-modulus bias due to selection effects. ; National Science Foundation (NSF) AST-1211916 TABASGO Foundation, Gary and Cynthia Bengier Christopher R. Redlich Fund Sylvia and Jim Katzman Foundation Miller Institute for Basic Research in Science (UC Berkeley) - European Union 839090 Spanish grant PGC2018-095317-B-C21 European Union (EU) EU/FP7-ERC grant 615929 National Science Foundation (NSF) Hyper Suprime-Cam (HSC) collaboration includes the astronomical communities of Japan Princeton University Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU) University of Tokyo High Energy Accelerator Research Organization (KEK) FIRST programme from the Japanese Cabinet Office Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of Science Japan Science & Technology Agency (JST) Toray Industries, Inc. Institute for Astronomy (the University of Hawaii) Max Planck Society Foundation CELLEX National Central University of Taiwan Space Telescope Science Institute National Aeronautics & Space Administration (NASA) NNX08AR22G National Aeronautics & Space Administration (NASA) National Science Foundation (NSF) AST-1238877 University of Maryland Eotvos Lorand University (ELTE) National Aeronautics & Space Administration (NASA) W.M. Keck Foundation National Research Council of Canada Centre National de la Recherche Scientifique (CNRS) Science & Technology Facilities Council (STFC) National Research Council Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) Australian Research Council National Council for Scientific and Technological Development (CNPq) Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) GN-2005A-Q11 GN-2005B-Q-7 GN-2006A-Q-7 GS-2005A-Q-11 GS-2005BQ-6 GS-2008B-Q-56 United States Department of Energy (DOE) Spanish Government Science & Technology Facilities Council (STFC) Higher Education Funding Council for England National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign Ohio State University Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University Ciencia Tecnologia e Inovacao (FINEP) Fundacao Carlos Chagas Filho de Amparo Conselho Nacional de Desenvolvimento Cient'tronomy at Texas AM University German Research Foundation (DFG) University of Portsmouth OzDES Membership Consortium National Science Foundation (NSF) AST-1138766 AST-1536171 AYA2015-71825 ESP2015-66861 FPA2015-68048 SEV2016-0588 SEV-2016-0597 European Union (EU) European Union - CERCA programme of the Generalitat de Catalunya European Research Council (ERC) European Research Council (ERC) 240672 291329 306478 National Council for Scientific and Technological Development (CNPq) 465376/2014-2 United States Department of Energy (DOE) United States Department of Energy (DOE) DE-AC02-05CH11231 United States Department of Energy (DOE) DE-AC02-05CH11231

US Department of Energy ; US National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Center for Particle Cosmology at the University of Pennsylvania ; Warren Center at the University of Pennsylvania ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Ministerio da Ciencia e Tecnologia ; Deutsche Forschungsgemeinschaft ; National Science Foundation ; MINECO ; Centro de Excelencia Severo Ochoa ; European Union ; Argonne National Laboratory ; University of California at Santa Cruz ; University of Cambridge ; University of Chicago ; University College London ; DES-Brazil Consortium ; Eidgenossische Technische Hochschule (ETH) Zurich ; Fermi National Accelerator Laboratory ; University of Edinburgh ; University of Illinois at Urbana-Champaign ; Institut de Ciencies de l'Espai (IEEC/CSIC) ; Institut de Fisica d'Altes Energies ; Lawrence Berkeley National Laboratory ; Ludwig-Maximilians Universitat ; associated Excellence Cluster Universe ; University of Michigan ; National Optical Astronomy Observatory ; University of Nottingham ; Ohio State University ; University of Pennsylvania ; University of Portsmouth ; University of Sussex ; Texas AM University ; SLAC National Accelerator Laboratory ; Stanford University ; Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid ; Science and Technology Facilities Council ; ICREA ; National Science Foundation: AST-1138766 ; MINECO: AYA2012-39559 ; MINECO: ESP2013-48274 ; MINECO: FPA2013-47986 ; Centro de Excelencia Severo Ochoa: SEV-2012-0234 ; Science and Technology Facilities Council: ST/M001334/1 ; Science and Technology Facilities Council: ST/L000768/1 ; We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 deg(2) contiguous patch of DES data from the Science Verification (SV) period of observations. Using large-scale measurements, we constrain the matter density of the Universe as Omega(m) = 0.31 +/- 0.09 and the clustering amplitude of the matter power spectrum as sigma(8) = 0.74 +/- 0.13 after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into S-8 = sigma(8)(Omega(m)/0.3)(0.16) = 0.74 +/- 0.12 for our fiducial lens redshift bin at 0.35 < z < 0.5, while S-8 = 0.78 +/- 0.09 using two bins over the range 0.2 < z < 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck Cosmic Microwave Background data, baryon accoustic oscillations and Supernova Type Ia measurements.

Spanish Ramon y Cajal MICINN program ; Ohio State University Center for Cosmology and AstroParticle Physics ; Spanish Ministerio de Economia y Competitividad ; Juan de la Cierva fellowship ; 'Plan Estatal de Investigacion Cientfica y Tecnica y de Innovacion' program of the Spanish government ; U.S. Department of Energy ; U.S. National Science Foundation ; Ministry of Science and Education of Spain ; Science and Technology Facilities Council of the United Kingdom ; Higher Education Funding Council for England ; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign ; Kavli Institute of Cosmological Physics at the University of Chicago ; Center for Cosmology and Astro-Particle Physics at the Ohio State University ; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University ; Financiadora de Estudos e Projetos ; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ; Ministerio da Ciencia, Tecnologia e Inovacao ; Deutsche Forschungsgemeinschaft ; Argonne National Laboratory ; University of California at Santa Cruz ; University of Cambridge ; Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid ; University of Chicago ; University College London ; DES-Brazil Consortium ; University of Edinburgh ; Eidgenossische Technische Hochschule (ETH) Zurich ; Fermi National Accelerator Laboratory ; University of Illinois at Urbana-Champaign ; Institut de Ciencies de l'Espai (IEEC/CSIC) ; Institut de Fisica d'Altes Energies ; Lawrence Berkeley National Laboratory ; Ludwig-Maximilians Universitat Munchen ; University of Michigan ; National Optical Astronomy Observatory ; University of Nottingham ; Ohio State University ; University of Pennsylvania ; University of Portsmouth ; SLAC National Accelerator Laboratory ; Stanford University ; University of Sussex ; Texas AM University ; OzDES Membership Consortium ; National Science Foundation ; MINECO ; ERDF funds from the European Union ; CERCA program of the Generalitat de Catalunya ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013) ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) ; U.S. Department of Energy, Office of Science, and Office of High Energy Physics ; Spanish Ministerio de Economia y Competitividad: ESP2013-48274-C3-1-P ; National Science Foundation: AST-1138766 ; National Science Foundation: AST-1536171 ; MINECO: AYA2015-71825 ; MINECO: ESP2015-66861 ; MINECO: FPA2015-68048 ; MINECO: SEV-2016-0588 ; MINECO: SEV-2016-0597 ; MINECO: MDM-2015-0509 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 240672 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 291329 ; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013): 306478 ; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO): CE110001020 ; U.S. Department of Energy, Office of Science, and Office of High Energy Physics: DE-AC02-07CH11359 ; We define and characterize a sample of 1.3million galaxies extracted from the first year of Dark Energy Survey data, optimized to measure baryon acoustic oscillations (BAO) in the presence of significant redshift uncertainties. The sample is dominated by luminous red galaxies located at redshifts z greater than or similar to 0.6. We define the exact selection using colour and magnitude cuts that balance the need of high number densities and small photometric redshift uncertainties, using the corresponding forecasted BAO distance error as a figure-of-merit in the process. The typical photo z uncertainty varies from 2.3 per cent to 3.6 per cent (in units of 1+z) from z = 0.6 to 1, with number densities from 200 to 130 galaxies per deg(2) in tomographic bins of width Delta z = 0.1. Next, we summarize the validation of the photometric redshift estimation. We characterize and mitigate observational systematics including stellar contamination and show that the clustering on large scales is robust in front of those contaminants. We show that the clustering signal in the autocorrelations and cross-correlations is generally consistent with theoretical models, which serve as an additional test of the redshift distributions.