arXiv subjects

A. E. Evrard

Publications and source records attributed to A. E. Evrard.

At least 91 records · Page 5Linked to original sources

arXiv2019

Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

We present cosmological results from a combined analysis of galaxy clustering and weak gravitational lensing, using 1321 deg$^2$ of $griz$ imaging data from the first year of the Dark Energy Survey (DES Y1). We combine three two-point functions: (i) the cosmic shear correlation function of 26 million source galaxies in four redshift bins, (ii) the galaxy angular autocorrelation function of 650,000 luminous red galaxies in five redshift bins, and (iii) the galaxy-shear cross-correlation of luminous red galaxy positions and source galaxy shears. To demonstrate the robustness of these results, we use independent pairs of galaxy shape, photometric redshift estimation and validation, and likelihood analysis pipelines. To prevent confirmation bias, the bulk of the analysis was carried out while blind to the true results; we describe an extensive suite of systematics checks performed and passed during this blinded phase. The data are modeled in flat $Λ$CDM and $w$CDM cosmologies, marginalizing over 20 nuisance parameters, varying 6 (for $Λ$CDM) or 7 (for $w$CDM) cosmological parameters including the neutrino mass density and including the 457 $\times$ 457 element analytic covariance matrix. We find consistent cosmological results from these three two-point functions, and from their combination obtain $S_8 \equiv σ_8 (Ω_m/0.3)^{0.5} = 0.783^{+0.021}_{-0.025}$ and $Ω_m = 0.264^{+0.032}_{-0.019}$ for $Λ$CDM for $w$CDM, we find $S_8 = 0.794^{+0.029}_{-0.027}$, $Ω_m = 0.279^{+0.043}_{-0.022}$, and $w=-0.80^{+0.20}_{-0.22}$ at 68% CL. The precision of these DES Y1 results rivals that from the Planck cosmic microwave background measurements, allowing a comparison of structure in the very early and late Universe on equal terms. Although the DES Y1 best-fit values for $S_8$ and $Ω_m$ are lower than the central values from Planck ...

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arXiv2019

Mass Calibration of Optically Selected DES clusters using a Measurement of CMB-Cluster Lensing with SPTpol Data

We use cosmic microwave background (CMB) temperature maps from the 500 deg$^{2}$ SPTpol survey to measure the stacked lensing convergence of galaxy clusters from the Dark Energy Survey (DES) Year-3 redMaPPer (RM) cluster catalog. The lensing signal is extracted through a modified quadratic estimator designed to be unbiased by the thermal Sunyaev-Zel{'}dovich (tSZ) effect. The modified estimator uses a tSZ-free map, constructed from the SPTpol 95 and 150 GHz datasets, to estimate the background CMB gradient. For lensing reconstruction, we employ two versions of the RM catalog: a flux-limited sample containing 4003 clusters and a volume-limited sample with 1741 clusters. We detect lensing at a significance of 8.7$σ$(6.7$σ$) with the flux(volume)-limited sample. By modeling the reconstructed convergence using the Navarro-Frenk-White profile, we find the average lensing masses to be $M_{200m}$ = ($1.62^{+0.32}_{-0.25}$ [stat.] $\pm$ 0.04 [sys.]) and ($1.28^{+0.14}_{-0.18}$ [stat.] $\pm$ 0.03 [sys.]) $\times\ 10^{14}\ M_{\odot}$ for the volume- and flux-limited samples respectively. The systematic error budget is much smaller than the statistical uncertainty and is dominated by the uncertainties in the RM cluster centroids. We use the volume-limited sample to calibrate the normalization of the mass-richness scaling relation, and find a result consistent with the galaxy weak-lensing measurements from DES (Mcclintock et al. 2018).

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arXiv2019

Transfer learning for galaxy morphology from one survey to another

Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.

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arXiv2019

Three new VHS-DES Quasars at 6.7 < z < 6.9 and Emission Line Properties at z > 6.5

We report the results from a search for z > 6.5 quasars using the Dark Energy Survey (DES) Year 3 dataset combined with the VISTA Hemisphere Survey (VHS) and WISE All-Sky Survey. Our photometric selection method is shown to be highly efficient in identifying clean samples of high-redshift quasars leading to spectroscopic confirmation of three new quasars - VDESJ 0244-5008 (z=6.724), VDESJ 0020-3653 (z=6.834) and VDESJ 0246-5219 (z=6.90) - which were selected as the highest priority candidates in the survey data without any need for additional follow-up observations. The new quasars span the full range in luminosity covered by other z>6.5 quasar samples (J AB = 20.2 to 21.3; M1450 = -25.6 to -26.6). We have obtained spectroscopic observations in the near infrared for VDESJ 0244-5008 and VDESJ 0020-3653 as well as our previously identified quasar, VDESJ 0224-4711 at z=6.50 from Reed et al. (2017). We use the near infrared spectra to derive virial black-hole masses from the full-width-half-maximum of the MgII line. These black-hole masses are ~ 1 - 2 x 10$^9$M$_\odot$. Combining with the bolometric luminosities of these quasars of L$_{\rm{bol}}\simeq$ 1 - 3 x 10$^{47}$implies that the Eddington ratios are high - $\simeq$0.6-1.1. We consider the C\textrm{\textsc{IV}} emission line properties of the sample and demonstrate that our high-redshift quasars do not have unusual C\textrm{\textsc{IV}} line properties when compared to carefully matched low-redshift samples. Our new DES+VHS $z>6.5$ quasars now add to the growing census of luminous, rapidly accreting supermassive black-holes seen well into the epoch of reionisation.

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arXiv2018

Dark Energy Survey Year 1 results: Validation of weak lensing cluster member contamination estimates from P(z) decomposition

Weak lensing source galaxy catalogs used in estimating the masses of galaxy clusters can be heavily contaminated by cluster members, prohibiting accurate mass calibration. In this study we test the performance of an estimator for the extent of cluster member contamination based on decomposing the photometric redshift $P(z)$ of source galaxies into contaminating and background components. We perform a full scale mock analysis on a simulated sky survey approximately mirroring the observational properties of the Dark Energy Survey Year One observations (DES Y1), and find excellent agreement between the true number profile of contaminating cluster member galaxies in the simulation and the estimated one. We further apply the method to estimate the cluster member contamination for the DES Y1 redMaPPer cluster mass calibration analysis, and compare the results to an alternative approach based on the angular correlation of weak lensing source galaxies. We find indications that the correlation based estimates are biased by the selection of the weak lensing sources in the cluster vicinity, which does not strongly impact the $P(z)$ decomposition method. Collectively, these benchmarks demonstrate the strength of the $P(z)$ decomposition method in alleviating membership contamination and enabling highly accurate cluster weak lensing studies without broad exclusion of source galaxies, thereby improving the total constraining power of cluster mass calibration via weak lensing.

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arXiv2018

Weak Lensing Analysis of SPT selected Galaxy Clusters using Dark Energy Survey Science Verification Data

We present weak lensing (WL) mass constraints for a sample of massive galaxy clusters detected by the South Pole Telescope (SPT) via the Sunyaev-Zeldovich effect (SZE). We use $griz$ imaging data obtained from the Science Verification (SV) phase of the Dark Energy Survey (DES) to fit the WL shear signal of 33 clusters in the redshift range $0.25 \le z \le 0.8$ with NFW profiles and to constrain a four-parameter SPT mass-observable relation. To account for biases in WL masses, we introduce a WL mass to true mass scaling relation described by a mean bias and an intrinsic, log-normal scatter. We allow for correlated scatter within the WL and SZE mass-observable relations and use simulations to constrain priors on nuisance parameters related to bias and scatter from WL. We constrain the normalization of the $ζ-M_{500}$ relation, $A_\mathrm{SZ}=12.0_{-6.7}^{+2.6}$ when using a prior on the mass slope $B_\mathrm{SZ}$ from the latest SPT cluster cosmology analysis. Without this prior, we recover $A_\mathrm{SZ}=10.8_{-5.2}^{+2.3}$ and $B_\mathrm{SZ}=1.30_{-0.44}^{+0.22}$. Results in both cases imply lower cluster masses than measured in previous work with and without WL, although the uncertainties are large. The WL derived value of $B_\mathrm{SZ}$ is $\approx 20\%$ lower than the value preferred by the most recent SPT cluster cosmology analysis. The method demonstrated in this work is designed to constrain cluster masses and cosmological parameters simultaneously and will form the basis for subsequent studies that employ the full SPT cluster sample together with the DES data.

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arXiv2018

Dark Energy Survey Year 1 Results: Measurement of the Baryon Acoustic Oscillation scale in the distribution of galaxies to redshift 1

We present angular diameter distance measurements obtained by locating the BAO scale in the distribution of galaxies selected from the first year of Dark Energy Survey data. We consider a sample of over 1.3 million galaxies distributed over a footprint of 1318 deg$^2$ with $0.6 < z_{\rm photo} < 1$ and a typical redshift uncertainty of $0.03(1+z)$. This sample was selected, as fully described in a companion paper, using a color/magnitude selection that optimizes trade-offs between number density and redshift uncertainty. We investigate the BAO signal in the projected clustering using three conventions, the angular separation, the co-moving transverse separation, and spherical harmonics. Further, we compare results obtained from template based and machine learning photometric redshift determinations. We use 1800 simulations that approximate our sample in order to produce covariance matrices and allow us to validate our distance scale measurement methodology. We measure the angular diameter distance, $D_A$, at the effective redshift of our sample divided by the true physical scale of the BAO feature, $r_{\rm d}$. We obtain close to a 4 per cent distance measurement of $D_A(z_{\rm eff}=0.81)/r_{\rm d} = 10.75\pm 0.43 $. These results are consistent with the flat $Λ$CDM concordance cosmological model supported by numerous other recent experimental results. All data products are publicly available here: https://des.ncsa.illinois.edu/releases/y1a1/bao

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arXiv2018

DES Y1 Results: Validating cosmological parameter estimation using simulated Dark Energy Surveys

We use mock galaxy survey simulations designed to resemble the Dark Energy Survey Year 1 (DES Y1) data to validate and inform cosmological parameter estimation. When similar analysis tools are applied to both simulations and real survey data, they provide powerful validation tests of the DES Y1 cosmological analyses presented in companion papers. We use two suites of galaxy simulations produced using different methods, which therefore provide independent tests of our cosmological parameter inference. The cosmological analysis we aim to validate is presented in DES Collaboration et al. (2017) and uses angular two-point correlation functions of galaxy number counts and weak lensing shear, as well as their cross-correlation, in multiple redshift bins. While our constraints depend on the specific set of simulated realisations available, for both suites of simulations we find that the input cosmology is consistent with the combined constraints from multiple simulated DES Y1 realizations in the $Ω_m-σ_8$ plane. For one of the suites, we are able to show with high confidence that any biases in the inferred $S_8=σ_8(Ω_m/0.3)^{0.5}$ and $Ω_m$ are smaller than the DES Y1 $1-σ$ uncertainties. For the other suite, for which we have fewer realizations, we are unable to be this conclusive; we infer a roughly 70% probability that systematic biases in the recovered $Ω_m$ and $S_8$ are sub-dominant to the DES Y1 uncertainty. As cosmological analyses of this kind become increasingly more precise, validation of parameter inference using survey simulations will be essential to demonstrate robustness.

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arXiv2018

Dark Energy Survey Year 1 Results: Methods for Cluster Cosmology and Application to the SDSS

We perform the first blind analysis of cluster abundance data. Specifically, we derive cosmological constraints from the abundance and weak-lensing signal of \redmapper\ clusters of richness $λ\geq 20$ in the redshift range $z\in[0.1,0.3]$ as measured in the Sloan Digital Sky Survey (SDSS). We simultaneously fit for cosmological parameters and the richness--mass relation of the clusters. For a flat $Λ$CDM cosmological model with massive neutrinos, we find $S_8 \equiv σ_{8}(Ω_m/0.3)^{0.5}=0.79^{+0.05}_{-0.04}$. This value is both consistent and competitive with that derived from cluster catalogues selected in different wavelengths. Our result is also consistent with the combined probes analyses by the Dark Energy Survey (DES) and the Kilo-Degree Survey (KiDS), and with the Cosmic Microwave Background (CMB) anisotropies as measured by \planck. We demonstrate that the cosmological posteriors are robust against variation of the richness--mass relation model and to systematics associated with the calibration of the selection function. In combination with Baryon Acoustic Oscillation (BAO) data and Big-Bang Nucleosynthesis (BBN) data, we constrain the Hubble rate to be $h=0.66\pm 0.02$, independent of the CMB. Future work aimed at improving our understanding of the scatter of the richness--mass relation has the potential to significantly improve the precision of our cosmological posteriors. The methods described in this work were developed for use in the forthcoming analysis of cluster abundances in the DES. Our SDSS analysis constitutes the first part of a staged-unblinding analysis of the full DES data set.

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arXiv2018

Measuring Linear and Non-linear Galaxy Bias Using Counts-in-Cells in the Dark Energy Survey Science Verification Data

Non-linear bias measurements require a great level of control of potential systematic effects in galaxy redshift surveys. Our goal is to demonstrate the viability of using Counts-in-Cells (CiC), a statistical measure of the galaxy distribution, as a competitive method to determine linear and higher-order galaxy bias and assess clustering systematics. We measure the galaxy bias by comparing the first four moments of the galaxy density distribution with those of the dark matter distribution. We use data from the MICE simulation to evaluate the performance of this method, and subsequently perform measurements on the public Science Verification (SV) data from the Dark Energy Survey (DES). We find that the linear bias obtained with CiC is consistent with measurements of the bias performed using galaxy-galaxy clustering, galaxy-galaxy lensing, CMB lensing, and shear+clustering measurements. Furthermore, we compute the projected (2D) non-linear bias using the expansion $δ_{g} = \sum_{k=0}^{3} (b_{k}/k!) δ^{k}$, finding a non-zero value for $b_2$ at the $3σ$ level. We also check a non-local bias model and show that the linear bias measurements are robust to the addition of new parameters. We compare our 2D results to the 3D prediction and find compatibility in the large scale regime ($>30$ Mpc $h^{-1}$)

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arXiv2018

The XXL Survey XX: The 365 cluster catalogue

In the currently debated context of using clusters of galaxies as cosmological probes, the need for well-defined cluster samples is critical. The XXL Survey has been specifically designed to provide a well characterised sample of some 500 X-ray detected clusters suitable for cosmological studies. The main goal of present article is to make public and describe the properties of the cluster catalogue in its present state, as well as of associated catalogues as super-clusters and fossil groups. We release a sample containing 365 clusters in total. We give the details of the follow-up observations and explain the procedure adopted to validate the cluster spectroscopic redshifts. Considering the whole XXL cluster sample, we have provided two types of selection, both complete in a particular sense: one based on flux-morphology criteria, and an alternative based on the [0.5-2] keV flux within one arcmin of the cluster centre. We have also provided X-ray temperature measurements for 80$\%$ of the clusters having a flux larger than 9$\times$10$^{-15}$$\rm \thinspace erg \, s^{-1} \, cm^{-2}$. Our cluster sample extends from z$\sim$0 to z$\sim$1.2, with one cluster at z$\sim$2. Clusters were identified through a mean number of six spectroscopically confirmed cluster members. Our updated luminosity function and luminosity-temperature relation are compatible with our previous determinations based on the 100 brightest clusters, but show smaller uncertainties. We also present an enlarged list of super-clusters and a sample of 18 possible fossil groups. This intermediate publication is the last before the final release of the complete XXL cluster catalogue when the ongoing C2 cluster spectroscopic follow-up is complete. It provides a unique inventory of medium-mass clusters over a 50~\dd\ area out to z$\sim$1.

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arXiv2018

Dark Energy Survey Year 1 Results: Methodology and Projections for Joint Analysis of Galaxy Clustering, Galaxy Lensing, and CMB Lensing Two-point Functions

Optical imaging surveys measure both the galaxy density and the gravitational lensing-induced shear fields across the sky. Recently, the Dark Energy Survey (DES) collaboration used a joint fit to two-point correlations between these observables to place tight constraints on cosmology (DES Collaboration et al. 2017). In this work, we develop the methodology to extend the DES year one joint probes analysis to include cross-correlations of the optical survey observables with gravitational lensing of the cosmic microwave background (CMB) as measured by the South Pole Telescope (SPT) and Planck. Using simulated analyses, we show how the resulting set of five two-point functions increases the robustness of the cosmological constraints to systematic errors in galaxy lensing shear calibration. Additionally, we show that contamination of the SPT+Planck CMB lensing map by the thermal Sunyaev-Zel'dovich effect is a potentially large source of systematic error for two-point function analyses, but show that it can be reduced to acceptable levels in our analysis by masking clusters of galaxies and imposing angular scale cuts on the two-point functions. The methodology developed here will be applied to the analysis of data from the DES, the SPT, and Planck in a companion work.

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arXiv2018

The XXL Survey XXV. Cosmological analysis of the C1 cluster number counts

Context. We present an estimation of cosmological parameters with clusters of galaxies. Aims. We constrain the $Ω_m$, $σ_8$, and $w$ parameters from a stand-alone sample of X-ray clusters detected in the 50 deg$^2$ XMM-XXL survey with a well-defined selection function. Methods. We analyse the redshift distribution of a sample comprising 178 high S/N clusters out to a redshift of unity. The cluster sample scaling relations are determined in a self-consistent manner. Results. In a lambda cold dark matter ($Λ$CDM) model, the cosmology favoured by the XXL clusters compares well with results derived from the Planck S-Z clusters for a totally different sample (mass/redshift range, selection biases, and scaling relations). However, with this preliminary sample and current mass calibration uncertainty, we find no inconsistency with the Planck CMB cosmology. If we relax the $w$ parameter, the Planck CMB uncertainties increase by a factor of $\sim$10 and become comparable with those from XXL clusters. Combining the two probes allows us to put constraints on $Ω_m$=0.316$\pm$0.060, $σ_8$=0.814$\pm$0.054, and $w$=-1.02$\pm$0.20. Conclusions. This first self-consistent cosmological analysis of a sample of serendipitous XMM clusters already provides interesting insights into the constraining power of the XXL survey. Subsequent analysis will use a larger sample extending to lower confidence detections and include additional observable information, potentially improving posterior uncertainties by roughly a factor of 3.

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arXiv2018

Dark Energy Survey Year 1 Results: Calibration of redMaGiC Redshift Distributions in DES and SDSS from Cross-Correlations

We present calibrations of the redshift distributions of redMaGiC galaxies in the Dark Energy Survey Year 1 (DES Y1) and Sloan Digital Sky Survey (SDSS) DR8 data. These results determine the priors of the redshift distribution of redMaGiC galaxies, which were used for galaxy clustering measurements and as lenses for galaxy-galaxy lensing measurements in DES Y1 cosmological analyses. We empirically determine the bias in redMaGiC photometric redshift estimates using angular cross-correlations with Baryon Oscillation Spectroscopic Survey (BOSS) galaxies. For DES, we calibrate a single parameter redshift bias in three photometric redshift bins: $z \in[0.15,0.3]$, [0.3,0.45], and [0.45,0.6]. Our best fit results in each bin give photometric redshift biases of $|Δz|<0.01$. To further test the redMaGiC algorithm, we apply our calibration procedure to SDSS redMaGiC galaxies, where the statistical precision of the cross-correlation measurement is much higher due to a greater overlap with BOSS galaxies. For SDSS, we also find best fit results of $|Δz|<0.01$. We compare our results to other analyses of redMaGiC photometric redshifts.

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arXiv2018

Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV

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. KS 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 KS 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 correlation between reconstructions from data and foreground redMaPPer clusters is increased 18 per cent by the Wiener filter and 32 per cent by GLIMPSE.

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arXiv2018

Dark Energy Survey Year 1 Results: Weak Lensing Mass Calibration of redMaPPer Galaxy Clusters

We constrain the mass--richness scaling relation of redMaPPer galaxy clusters identified in the Dark Energy Survey Year 1 data using weak gravitational lensing. We split clusters into $4\times3$ bins of richness $λ$ and redshift $z$ for $λ\geq20$ and $0.2 \leq z \leq 0.65$ and measure the mean masses of these bins using their stacked weak lensing signal. By modeling the scaling relation as $\langle M_{\rm 200m}|λ,z\rangle = M_0 (λ/40)^F ((1+z)/1.35)^G$, we constrain the normalization of the scaling relation at the 5.0 per cent level as $M_0 = [3.081 \pm 0.075 ({\rm stat}) \pm 0.133 ({\rm sys})] \cdot 10^{14}\ {\rm M}_\odot$ at $λ=40$ and $z=0.35$. The richness scaling index is constrained to be $F=1.356 \pm 0.051\ ({\rm stat})\pm 0.008\ ({\rm sys})$ and the redshift scaling index $G=-0.30\pm 0.30\ ({\rm stat})\pm 0.06\ ({\rm sys})$. These are the tightest measurements of the normalization and richness scaling index made to date. We use a semi-analytic covariance matrix to characterize the statistical errors in the recovered weak lensing profiles. Our analysis accounts for the following sources of systematic error: shear and photometric redshift errors, cluster miscentering, cluster member dilution of the source sample, systematic uncertainties in the modeling of the halo--mass correlation function, halo triaxiality, and projection effects. We discuss prospects for reducing this systematic error budget, which dominates the uncertainty on $M_0$. Our result is in excellent agreement with, but has significantly smaller uncertainties than, previous measurements in the literature, and augurs well for the power of the DES cluster survey as a tool for precision cosmology and upcoming galaxy surveys such as LSST, Euclid and WFIRST.

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arXiv2018

Dark Energy Survey Year 1 Results: Weak Lensing Shape Catalogues

We present two galaxy shape catalogues from the Dark Energy Survey Year 1 data set, covering 1500 square degrees with a median redshift of $0.59$. The catalogues cover two main fields: Stripe 82, and an area overlapping the South Pole Telescope survey region. We describe our data analysis process and in particular our shape measurement using two independent shear measurement pipelines, METACALIBRATION and IM3SHAPE. The METACALIBRATION catalogue uses a Gaussian model with an innovative internal calibration scheme, and was applied to $riz$-bands, yielding 34.8M objects. The IM3SHAPE catalogue uses a maximum-likelihood bulge/disc model calibrated using simulations, and was applied to $r$-band data, yielding 21.9M objects. Both catalogues pass a suite of null tests that demonstrate their fitness for use in weak lensing science. We estimate the 1$σ$ uncertainties in multiplicative shear calibration to be $0.013$ and $0.025$ for the METACALIBRATION and IM3SHAPE catalogues, respectively.

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arXiv2018

Dark Energy Survey Year 1 Results: Galaxy clustering for combined probes

We measure the clustering of DES Year 1 galaxies that are intended to be combined with weak lensing samples in order to produce precise cosmological constraints from the joint analysis of large-scale structure and lensing correlations. Two-point correlation functions are measured for a sample of $6.6 \times 10^{5}$ luminous red galaxies selected using the \textsc{redMaGiC} algorithm over an area of $1321$ square degrees, in the redshift range $0.15 < z < 0.9$, split into five tomographic redshift bins. The sample has a mean redshift uncertainty of $σ_{z}/(1+z) = 0.017$. We quantify and correct spurious correlations induced by spatially variable survey properties, testing their impact on the clustering measurements and covariance. We demonstrate the sample's robustness by testing for stellar contamination, for potential biases that could arise from the systematic correction, and for the consistency between the two-point auto- and cross-correlation functions. We show that the corrections we apply have a significant impact on the resultant measurement of cosmological parameters, but that the results are robust against arbitrary choices in the correction method. We find the linear galaxy bias in each redshift bin in a fiducial cosmology to be $b(z$=$0.24)=1.40 \pm 0.08$, $b(z$=$0.38)=1.61 \pm 0.05$, $b(z$=$0.53)=1.60 \pm 0.04$ for galaxies with luminosities $L/L_*>$$0.5$, $b(z$=$0.68)=1.93 \pm 0.05$ for $L/L_*>$$1$ and $b(z$=$0.83)=1.99 \pm 0.07$ for $L/L_*$$>1.5$, broadly consistent with expectations for the redshift and luminosity dependence of the bias of red galaxies. We show these measurements to be consistent with the linear bias obtained from tangential shear measurements.

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