16 research outputs found
Dark Energy Survey Year 3 results: Galaxy clustering and systematics treatment for lens galaxy samples
DES Collaboration: M. RodrĂguez-Monroy, N. Weaverdyck, J. Elvin-Poole et al.In this work, we present the galaxy clustering measurements of the two DES lens galaxy samples: a magnitude-limited sample optimized for the measurement of cosmological parameters, MAGLIM, and a sample of luminous red galaxies selected with the REDMAGIC algorithm. MAGLIM/REDMAGIC sample contains over 10 million/2.5 million galaxies and is divided into six/five photometric redshift bins spanning the range z â [0.20, 1.05]/z â [0.15, 0.90]. Both samples cover 4143 deg2 over which we perform our analysis blind, measuring the angular correlation function with an S/N ⌠63 for both samples. In a companion paper, these measurements of galaxy clustering are combined with the correlation functions of cosmic shear and galaxyâgalaxy lensing of each sample to place cosmological constraints with a 3 Ă 2pt analysis. We conduct a thorough study of the mitigation of systematic effects caused by the spatially varying survey properties and we correct the measurements to remove artificial clustering signals. We employ several decontamination methods with different configurations to ensure the robustness of our corrections and to determine the systematic uncertainty that needs to be considered for the final cosmology analyses. We validate our fiducial methodology using lognormal mocks, showing that our decontamination procedure induces biases no greater than 0.5Ï in the (Ωm, b) plane, where b is the galaxy bias.Funding for the Dark Energy Survey Projects has been provided by the US Department of Energy, the US 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 Ă Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento CientĂfico e TecnolĂłgico and the MinistĂ©rio da CiĂȘncia, 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 EnergĂ©ticas, Medioambientales y TecnolĂłgicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) ZĂŒrich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de CiĂšncies de lâEspai (IEEC/CSIC), the Institut de FĂsica dâAltes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians UniversitĂ€t MĂŒnchen and the associated Excellence Cluster Universe, the University of Michigan, NFSâs 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. This paper is based in part on observations at Cerro Tololo Inter-American Observatory at NSFâs 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 program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Unionâs Seventh Framework Program (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de CiĂȘncia e Tecnologia (INCT) do e-Universo (CNPq grant 465376/2014-2). This paper has been authored by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the US Department of Energy, Office of Science, Office of High Energy Physics.Peer reviewe
A Spectroscopic Road Map for Cosmic Frontier: DESI, DESI-II, Stage-5
In this white paper, we present an experimental road map for spectroscopic
experiments beyond DESI. DESI will be a transformative cosmological survey in
the 2020s, mapping 40 million galaxies and quasars and capturing a significant
fraction of the available linear modes up to z=1.2. DESI-II will pilot
observations of galaxies both at much higher densities and extending to higher
redshifts. A Stage-5 experiment would build out those high-density and
high-redshift observations, mapping hundreds of millions of stars and galaxies
in three dimensions, to address the problems of inflation, dark energy, light
relativistic species, and dark matter. These spectroscopic data will also
complement the next generation of weak lensing, line intensity mapping and CMB
experiments and allow them to reach their full potential.Comment: Contribution to Snowmass 202
Robust sampling for weak lensing and clustering analyses with the Dark Energy Survey
P. Lemos et al.Recent cosmological analyses rely on the ability to accurately sample from high-dimensional posterior distributions. A variety of algorithms have been applied in the field, but justification of the particular sampler choice and settings is often lacking. Here, we investigate three such samplers to motivate and validate the algorithm and settings used for the Dark Energy Survey (DES) analyses of the first 3 yr (Y3) of data from combined measurements of weak lensing and galaxy clustering. We employ the full DES Year 1 likelihood alongside a much faster approximate likelihood, which enables us to assess the outcomes from each sampler choice and demonstrate the robustness of our full results. We find that the ellipsoidal nested sampling algorithm MULTINEST reports inconsistent estimates of the Bayesian evidence and somewhat narrower parameter credible intervals than the sliced nested sampling implemented in POLYCHORD. We compare the findings from MULTINEST and POLYCHORD with parameter inference from the MetropolisâHastings algorithm, finding good agreement. We determine that POLYCHORD provides a good balance of speed and robustness for posterior and evidence estimation, and recommend different settings for testing purposes and final chains for analyses with DES Y3 data. Our methodology can readily be reproduced to obtain suitable sampler settings for future surveys.PL acknowledges STFC Consolidated Grants ST/R000476/1 and ST/T000473/1. NW is supported by the Chamberlain fellowship at Lawrence Berkeley National Laboratory. This work was supported through computational resources and services provided by the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231; and by the Sherlock cluster, supported by Stanford University and the Stanford Research Computing Center. 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 Ă Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento CientĂfico e TecnolĂłgico and the MinistĂ©rio da CiĂȘncia, 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 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 program of the Generalitat de Catalunya. Research leading to these results has received funding from the European Research Council under the European Unionâs Seventh Framework Program (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de CiĂȘncia e Tecnologia (INCT) do e-Universo (CNPq grant 465376/2014-2).Peer reviewe
A spectroscopic road map for cosmic frontier: DESI, DESI-II, Stage-5
International audienceIn this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential
A spectroscopic road map for cosmic frontier: DESI, DESI-II, Stage-5
International audienceIn this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential
Constraints on dark matter to dark radiation conversion in the late universe with DES-Y1 and external data
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 <0.32 for DES-Y1 3x2pt data, <0.030 for CMB+SN+BAO data, and <0.037 for the combined dataset. The probability that the DES and CMB+SN+BAO datasets are concordant increases from 4% for the ÎCDM model to 8% (less tension) for DMDR. The tension in S8=Ï8âΩm/0.3 between DES-Y1 3x2pt and CMB+SN+BAO is slightly reduced from 2.3Ï to 1.9Ï. We find no reduction in the Hubble tension when the combined data is compared to distance-ladder measurements in the DMDR model. The maximum-posterior goodness-of-fit statistics of DMDR and ÎCDM model are comparable, indicating no preference for the DMDR cosmology over ÎCDM
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Dark energy survey operations: years 4 and 5
The Dark Energy Survey (DES) is an operating optical survey aimed at understanding the accelerating expansion of the universe using four complementary methods: weak gravitational lensing, galaxy cluster counts, baryon acoustic oscillations, and Type Ia supernovae. To perform the 5000 sq-degree wide field and 30 sq-degree supernova surveys, the DES Collaboration built the Dark Energy Camera (DECam), a 3 square-degree, 570-Megapixel CCD camera that was installed at the prime focus of the Blanco 4-meter telescope at the Cerro Tololo Inter-American Observatory (CTIO). DES has completed its third observing season out of a nominal five. This paper describes DES "Year 4" (Y4) and "Year 5" (Y5), the survey strategy, an outline of the survey operations procedures, the efficiency of operations and the causes of lost observing time. It provides details about the quality of these two-season's data, a summary of the overall status, and plans for the final survey season.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, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico; Ministerio da Ciencia, Tecnologia e Inovacao; Deutsche Forschungsgemeinschaft; Dark Energy Survey; National Science Foundation [AST-1138766, AST-1536171]; MINECO [AYA2015-71825, ESP2015-66861, FPA2015-68048, SEV-2016-0588, SEV-2016-0597, MDM-2015-0509]; European Union; CERCA program of the Generalitat de Catalunya; European Research Council under the European Union's Seventh Framework Program (FP7/2007-2013) including ERC grant [240672, 291329, 306478]; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) [CE110001020]; Brazilian Instituto Nacional de Ciencia e Tecnologia (INCT) e-Universe (CNPq) [465376/2014-2]; U.S. Department of Energy, Office of Science, Office of High Energy Physics [DE-AC02-07CH11359]; 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; OzDES Membership Consortium; Texas AM UniversityThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
Dark Energy Survey year 3 results: covariance modelling and its impact on parameter estimation and quality of fit
We describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, we validate the assumptions and approximations of this model. These include the assumption of Gaussian likelihood, the trispectrum contribution to the covariance, the impact of evaluating the model at a wrong set of parameters, the impact of masking and survey geometry, deviations from Poissonian shot noise, galaxy weighting schemes, and other sub-dominant effects. We find that our covariance model is robust and that its approximations have little impact on goodness of fit and parameter estimation. The largest impact on best-fitting figure-of-merit arises from the so-called fsky approximation for dealing with finite survey area, which on average increases the Ï2 between maximum posterior model and measurement by 3.7 per cent (ÎÏ2 â 18.9). Standard methods to go beyond this approximation fail for DES-Y3, but we derive an approximate scheme to deal with these features. For parameter estimation, our ignorance of the exact parameters at which to evaluate our covariance model causes the dominant effect. We find that it increases the scatter of maximum posterior values for Ωm and Ï8 by about 3 per cent and for the dark energy equation-of-state parameter by about 5 per centâ
Dark Energy Survey Year 3 results: galaxy sample for BAO measurement
In this paper, we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y3 data. The definition is based on a colour and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.5, while ensuring a high-quality determination. The sample covers âŒ4100 deg2to a depth of i = 22.3â(AB) at 10Ï. It contains 7031â993 galaxies in the redshift range from z = 0.6 to 1.1, with a mean effective redshift of 0.835. Redshifts are estimated with the machine learning algorithm dnf, and are validated using the VIPERS PDR2 sample. We find a mean redshift bias of zbiasâŒ0.01 and a mean uncertainty, in units of 1 + zâ , of Ï68âŒ0.03â . We evaluate the galaxy population of the sample, showing it is mostly built upon Elliptical to Sbc types. Furthermore, we find a low level of stellar contamination of âČ4 per centâ . We present the method used to mitigate the effect of spurious clustering coming from observing conditions and other large-scale systematics. We apply it to the BAO sample and calculate weights that are used to get a robust estimate of the galaxy clustering signal. This paper is one of a series dedicated to the analysis of the BAO signal in DES Y3. In the companion papers, we present the galaxy mock catalogues used to calibrate the analysis and the angular diameter distance constraints obtained through the fitting to the BAO scale
Probing gravity with the DES-CMASS sample and BOSS spectroscopy
The DES-CMASS sample (DMASS) is designed to optimally combine the weak lensing measurements from the Dark Energy Survey (DES) and redshift-space distortions (RSD) probed by the CMASS galaxy sample from the Baryonic Oscillation Spectroscopic Survey. In this paper, we demonstrate the feasibility of adopting DMASS as the equivalent of CMASS for a joint analysis of DES and BOSS in the framework of modified gravity. We utilize the angular clustering of the DMASS galaxies, cosmic shear of the DES metacalibration sources, and cross-correlation of the two as data vectors. By jointly fitting the combination of the data with the RSD measurements from the CMASS sample and Planck data, we obtain the constraints on modified gravity parameters ÎŒ0=â0.37+0.47â0.45 and ÎŁ0=0.078+0.078â0.082â . Our constraints of modified gravity with DMASS are tighter than those with the DES Year 1 redMaGiC sample with the same external data sets by 29 per cent for ÎŒ0 and 21 per cent for ÎŁ0, and comparable to the published results of the DES Year 1 modified gravity analysis despite this work using fewer external data sets. This improvement is mainly because the galaxy bias parameter is shared and more tightly constrained by both CMASS and DMASS, effectively breaking the degeneracy between the galaxy bias and other cosmological parameters. Such an approach to optimally combine photometric and spectroscopic surveys using a photometric sample equivalent to a spectroscopic sample can be applied to combining future surveys having a limited overlap such as DESI and LSST