Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userDark Energy Survey Year 1 Results: galaxy mock catalogues for BAO
84
0
0.0
(
0
)
Added by
Santiago Javier \\'Avila P\\'erez
Publication date
2017
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
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 $C_ell$.
rate research
Read More
The calibration and validation of scientific analysis in simulations is a fundamental tool to ensure unbiased and robust results in observational cosmology. In particular, mock galaxy catalogs are a crucial resource to achieve these goals in the measurement of Baryon Acoustic Oscillations (BAO) in the clustering of galaxies. Here we present a set of 1952 galaxy mock catalogs designed to mimic the Dark Energy Survey (DES) Year 3 BAO sample over its full photometric redshift range $0.6 < z_{rm photo} < 1.1$. The mocks are based upon 488 ICE-COLA fast $N$-body simulations of full-sky light-cones and are created by populating halos with galaxies, using a hybrid Halo Occupation Distribution - Halo Abundance Matching model. This model has 10 free parameters, which are determined, for the first time, using an automatic likelihood minimization procedure. We also introduce a novel technique to assign photometric redshift for simulated galaxies, following a two-dimensional probability distribution with VIMOS Public Extragalactic Redshift Survey (VIPERS) data. The calibration was designed to match the observed abundance of galaxies as a function of photometric redshift, the distribution of photometric redshift errors, and the clustering amplitude on scales smaller than those used for BAO measurements. An exhaustive analysis is done to ensure that the mocks reproduce the input properties. Finally, mocks are tested by comparing the angular correlation function $w(theta)$, angular power spectrum $C_ell$ and projected clustering $xi_p(r_perp)$ to theoretical predictions and data. The success in reproducing accurately the photometric redshift uncertainties and the galaxy clustering as a function of redshift render this mock creation pipeline as a benchmark for future analyses of photometric galaxy surveys.
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.
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$sigma$ uncertainties in multiplicative shear calibration to be $0.013$ and $0.025$ for the METACALIBRATION and IM3SHAPE catalogues, respectively.
We present galaxy-galaxy lensing measurements from 1321 sq. deg. of the Dark Energy Survey (DES) Year 1 (Y1) data. The lens sample consists of a selection of 660,000 red galaxies with high-precision photometric redshifts, known as redMaGiC, split into five tomographic bins in the redshift range $0.15 < z < 0.9$. We use two different source samples, obtained from the Metacalibration (26 million galaxies) and Im3shape (18 million galaxies) shear estimation codes, which are split into four photometric redshift bins in the range $0.2 < z < 1.3$. We perform extensive testing of potential systematic effects that can bias the galaxy-galaxy lensing signal, including those from shear estimation, photometric redshifts, and observational properties. Covariances are obtained from jackknife subsamples of the data and validated with a suite of log-normal simulations. We use the shear-ratio geometric test to obtain independent constraints on the mean of the source redshift distributions, providing validation of those obtained from other photo-$z$ studies with the same data. We find consistency between the galaxy bias estimates obtained from our galaxy-galaxy lensing measurements and from galaxy clustering, therefore showing the galaxy-matter cross-correlation coefficient $r$ to be consistent with one, measured over the scales used for the cosmological analysis. The results in this work present one of the three two-point correlation functions, along with galaxy clustering and cosmic shear, used in the DES cosmological analysis of Y1 data, and hence the methodology and the systematics tests presented here provide a critical input for that study as well as for future cosmological analyses in DES and other photometric galaxy surveys.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
