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Register a new userSynthetic Galaxy Clusters and Observations Based on Dark Energy Survey Year 3 Data
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Added by
Tamas Norbert Varga
Publication date
2021
fields
Physics
and research's language is
English
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We develop a novel data-driven method for generating synthetic optical observations of galaxy clusters. In cluster weak lensing, the interplay between analysis choices and systematic effects related to source galaxy selection, shape measurement and photometric redshift estimation can be best characterized in end-to-end tests going from mock observations to recovered cluster masses. To create such test scenarios, we measure and model the photometric properties of galaxy clusters and their sky environments from the Dark Energy Survey Year 3 (DES Y3) data in two bins of cluster richness $lambdain[30;,45)$, $lambdain[45;,60)$ and three bins in cluster redshift ($zin[0.3;,0.35)$, $zin[0.45;,0.5)$ and $zin[0.6;,0.65)$. Using deep-field imaging data we extrapolate galaxy populations beyond the limiting magnitude of DES Y3 and calculate the properties of cluster member galaxies via statistical background subtraction. We construct mock galaxy clusters as random draws from a distribution function, and render mock clusters and line-of-sight catalogs into synthetic images in the same format as actual survey observations. Synthetic galaxy clusters are generated from real observational data, and thus are independent from the assumptions inherent to cosmological simulations. The recipe can be straightforwardly modified to incorporate extra information, and correct for survey incompleteness. New realizations of synthetic clusters can be created at minimal cost, which will allow future analyses to generate the large number of images needed to characterize systematic uncertainties in cluster mass measurements.
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Galaxy-galaxy lensing is a powerful probe of the connection between galaxies and their host dark matter halos, which is important both for galaxy evolution and cosmology. We extend the measurement and modeling of the galaxy-galaxy lensing signal in the recent Dark Energy Survey Year 3 cosmology analysis to the highly nonlinear scales ($sim 100$ kpc). This extension enables us to study the galaxy-halo connection via a Halo Occupation Distribution (HOD) framework for the two lens samples used in the cosmology analysis: a luminous red galaxy sample (redMaGiC) and a magnitude-limited galaxy sample (MagLim). We find that redMaGiC (MagLim) galaxies typically live in dark matter halos of mass $log_{10}(M_{h}/M_{odot}) approx 13.7$ which is roughly constant over redshift ($13.3-13.5$ depending on redshift). We constrain these masses to $sim 15%$, approximately $1.5$ times improvement over previous work. We also constrain the linear galaxy bias more than 5 times better than what is inferred by the cosmological scales only. We find the satellite fraction for redMaGiC (MagLim) to be $sim 0.1-0.2$ ($0.1-0.3$) with no clear trend in redshift. Our constraints on these halo properties are broadly consistent with other available estimates from previous work, large-scale constraints and simulations. The framework built in this paper will be used for future HOD studies with other galaxy samples and extensions for cosmological analyses.
In this paper we present and validate the galaxy sample used for the analysis of the Baryon Acoustic Oscillation signal (BAO) 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 photometric redshift determination. The sample covers $approx 4100$ square degrees to a depth of $i = 22.3 (AB)$ at $10sigma$. It contains 7,031,993 galaxies in the redshift range from $z$= 0.6 to 1.1, with a mean effective redshift of 0.835. Photometric redshifts are estimated with the machine learning algorithm DNF, and are validated using the VIPERS PDR2 sample. We find a mean redshift bias of $z_{mathrm{bias}} approx 0.01$ and a mean uncertainty, in units of $1+z$, of $sigma_{68} approx 0.03$. 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 $lesssim 4%$. 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 DES Y3 BAO sample and calculate sample 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 the DES Y3 data. In the companion papers, Ferrero et al. (2021) and DES Collaboration (2021), 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, respectively. The galaxy sample, masks and additional material will be released in the public DES data repository upon acceptance.
We describe the Dark Energy Survey (DES) photometric data set assembled from the first three years of science operations to support DES Year 3 cosmology analyses, and provide usage notes aimed at the broad astrophysics community. Y3 Gold improves on previous releases from DES, Y1 Gold and Data Release 1 (DES DR1), presenting an expanded and curated data set that incorporates algorithmic developments in image detrending and processing, photometric calibration, and object classification. Y3 Gold comprises nearly 5000 square degrees of grizY imaging in the south Galactic cap, including nearly 390 million objects, with depth reaching S/N ~ 10 for extended objects up to $i_{AB}sim 23.0$, and top-of-the-atmosphere photometric uniformity $< 3$ mmag. Compared to DR1, photometric residuals with respect to Gaia are reduced by $50%$, and per-object chromatic corrections are introduced. Y3 Gold augments DES DR1 with simultaneous fits to multi-epoch photometry for more robust galaxy color measurements and corresponding photometric redshift estimates. Y3 Gold features improved morphological star-galaxy classification with efficiency $>98%$ and purity $>99%$ for galaxies with $19 < i_{AB} < 22.5$. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used to select the cosmology analysis samples. This paper will be complemented by online resources.
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 $zin[0.20,1.05]$ / $zin[0.15,0.90]$. Both samples cover 4143 deg$^2$ over which we perform our analysis blind, measuring the angular correlation function with a S/N $sim 63$ for both samples. In a companion paper (DES Collaboration et al. 2021)), these measurements of galaxy clustering are combined with the correlation functions of cosmic shear and galaxy-galaxy lensing of each sample to place cosmological constraints with a 3$times$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 log-normal mocks, showing that our decontamination procedure induces biases no greater than $0.5sigma$ in the $(Omega_m, b)$ plane, where $b$ is galaxy bias. We demonstrate that failure to remove the artificial clustering would introduce strong biases up to $sim 7 sigma$ in $Omega_m$ and of more than $4 sigma$ in galaxy bias.
We present and characterize the galaxy-galaxy lensing signal measured using the first three years of data from the Dark Energy Survey (DES Y3) covering 4132 deg$^2$. These galaxy-galaxy measurements are used in the DES Y3 3$times$2pt cosmological analysis, which combines weak lensing and galaxy clustering information. We use two lens samples: a magnitude-limited sample and the redMaGic sample, which span the redshift range $sim 0.2-1$ with 10.7 M and 2.6 M galaxies respectively. For the source catalog, we use the Metacalibration shape sample, consisting of $simeq$100 M galaxies separated into 4 tomographic bins. Our galaxy-galaxy lensing estimator is the mean tangential shear, for which we obtain a total S/N of $sim$148 for MagLim ($sim$120 for redMaGic), and $sim$67 ($sim$55) after applying the scale cuts of 6 Mpc/$h$. Thus we reach percent-level statistical precision, which requires that our modeling and systematic-error control be of comparable accuracy. The tangential shear model used in the 3$times$2pt cosmological analysis includes lens magnification, a five-parameter intrinsic alignment model (TATT), marginalization over a point-mass to remove information from small scales and a linear galaxy bias model validated with higher-order terms. We explore the impact of these choices on the tangential shear observable and study the significance of effects not included in our model, such as reduced shear, source magnification and source clustering. We also test the robustness of our measurements to various observational and systematics effects, such as the impact of observing conditions, lens-source clustering, random-point subtraction, scale-dependent Metacalibration responses, PSF residuals, and B-modes.
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