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Register a new userDark Energy Survey Year 1 Results: A Precise H0 Measurement from DES Y1, BAO, and D/H Data
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We combine Dark Energy Survey Year 1 clustering and weak lensing data with Baryon Acoustic Oscillations (BAO) and Big Bang Nucleosynthesis (BBN) experiments to constrain the Hubble constant. Assuming a flat $Lambda$CDM model with minimal neutrino mass ($sum m_ u = 0.06$ eV) we find $H_0=67.2^{+1.2}_{-1.0}$ km/s/Mpc (68% CL). This result is completely independent of Hubble constant measurements based on the distance ladder, Cosmic Microwave Background (CMB) anisotropies (both temperature and polarization), and strong lensing constraints. There are now five data sets that: a) have no shared observational systematics; and b) each constrain the Hubble constant with a few percent level precision. We compare these five independent measurements, and find that, as a set, the differences between them are significant at the $2.1sigma$ level ($chi^2/dof=20.1/11$, probability to exceed=4%). This difference is low enough that we consider the data sets statistically consistent with each other. The best fit Hubble constant obtained by combining all five data sets is $H_0 = 69.1^{+0.4}_{-0.6}$ km/s/Mpc.
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We define and characterise a sample of 1.3 million galaxies extracted from the first year of Dark Energy Survey data, optimised to measure Baryon Acoustic Oscillations in the presence of significant redshift uncertainties. The sample is dominated by luminous red galaxies located at redshifts $z gtrsim 0.6$. We define the exact selection using color 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 $2.3%$ to $3.6%$ (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 summarise the validation of the photometric redshift estimation. We characterise 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 auto-correlations and cross-correlations is generally consistent with theoretical models, which serves as an additional test of the redshift distributions.
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.
Mock catalogues are a crucial tool in the analysis of galaxy surveys data, both for the accurate computation of covariance matrices, and for the optimisation 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 $2LPT$ density field with an exponential bias. For each of them, a lightcone 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 textit{double-skewed-Gaussian} curve fitted to the data. We also introduce a hybrid HOD-HAM model with two free parameters that are adjusted to achieve a galaxy bias evolution $b(z_{rm ph})$ that matches the data at the 1-$sigma$ level in the range $0.6<z_{rm ph}<1.0$. 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 $xi_{mu<0.8}(s_{perp})$ and the angular power spectrum $C_ell$.
We cross-correlate galaxy weak lensing measurements from the Dark Energy Survey (DES) year-one (Y1) data with a cosmic microwave background (CMB) weak lensing map derived from South Pole Telescope (SPT) and Planck data, with an effective overlapping area of 1289 deg$^{2}$. With the combined measurements from four source galaxy redshift bins, we reject the hypothesis of no lensing with a significance of $10.8sigma$. When employing angular scale cuts, this significance is reduced to $6.8sigma$, which remains the highest signal-to-noise measurement of its kind to date. We fit the amplitude of the correlation functions while fixing the cosmological parameters to a fiducial $Lambda$CDM model, finding $A = 0.99 pm 0.17$. We additionally use the correlation function measurements to constrain shear calibration bias, obtaining constraints that are consistent with previous DES analyses. Finally, when performing a cosmological analysis under the $Lambda$CDM model, we obtain the marginalized constraints of $Omega_{rm m}=0.261^{+0.070}_{-0.051}$ and $S_{8}equiv sigma_{8}sqrt{Omega_{rm m}/0.3} = 0.660^{+0.085}_{-0.100}$. These measurements are used in a companion work that presents cosmological constraints from the joint analysis of two-point functions among galaxies, galaxy shears, and CMB lensing using DES, SPT and Planck data.
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 $|Delta z|<0.01$. 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 $|Delta z|<0.01$. We compare our results to other analyses of redMaGiC photometric redshifts.
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