We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we ...derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper. We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information. We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SExtractor), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23.
We describe redMaPPer, a new red sequence cluster finder specifically designed to make optimal use of ongoing and near-future large photometric surveys. The algorithm has multiple attractive ...features: (1) it can iteratively self-train the red sequence model based on a minimal spectroscopic training sample, an important feature for high-redshift surveys. (2) It can handle complex masks with varying depth. (3) It produces cluster-appropriate random points to enable large-scale structure studies. (4) All clusters are assigned a full redshift probability distribution P(z). (5) Similarly, clusters can have multiple candidate central galaxies, each with corresponding centering probabilities. (6) The algorithm is parallel and numerically efficient: it can run a Dark Energy Survey-like catalog in ~500 CPU hours. (7) The algorithm exhibits excellent photometric redshift performance, the richness estimates are tightly correlated with external mass proxies, and the completeness and purity of the corresponding catalogs are superb. We apply the redMaPPer algorithm to ~10,000 deg super(2) of SDSS DR8 data and present the resulting catalog of ~25,000 clusters over the redshift range z isin 0.08, 0.55. The redMaPPer photometric redshifts are nearly Gaussian, with a scatter sigma sub(z) approximately 0.006 at z approximately 0.1, increasing to sigma sub(z) approximately 0.02 at z approximately 0.5 due to increased photometric noise near the survey limit. The median value for | Delta z|/(1 + z) for the full sample is 0.006. The incidence of projection effects is low (< or =, slant5%). Detailed performance comparisons of the redMaPPer DR8 cluster catalog to X-ray and Sunyaev-Zel'dovich catalogs are presented in a companion paper.
We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based ...photometric redshift methods-annz2, bpz calibrated against BCC-Ufig simulations, skynet, and tpz-are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z's. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 + or - 0.01 over the range 0.3 < z< 1.3, we construct three tomographic bins with means of z= {0.45,0.67,1.00}. These bins each have systematic uncertainties delta sub(z)<, ~ 0.05 in the mean of the fiducial skynet photo-z n(z). We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of sigma sub(8) of approximately 3%. This shift is within the one sigma statistical errors on sigma sub(8) for the DES SV shear catalogue. We further study the potential impact of systematic differences on the critical surface density, capital sigma sub(crit), finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of n(z) of width 0.05 for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis.
The Blanco Cosmology Survey is a four-band (griz) optical-imaging survey of ~80 deg super(2) of the southern sky. The survey consists of two fields centered approximately at (R.A., decl.) = (23 ...super(h), -55degrees) and (5 super(h)30 super(m), -53degrees) with imaging sufficient for the detection of Llow *galaxies at redshift z < or =, slant 1. In this paper, we present our reduction of the survey data and describe a new technique for the separation of stars and galaxies. We search the calibrated source catalogs for galaxy clusters at z < or =, slant 0.75 by identifying spatial over-densities of red-sequence galaxies and report the coordinates, redshifts, and optical richnesses, lambda, for 764 galaxy clusters at z < or =, slant 0.75. This sample, >85% of which are new discoveries, has a median redshift of z = 0.52 and median richness lambda(0.4 Llow *) = 16.4. Accompanying this paper we also release full survey data products including reduced images and calibrated source catalogs. These products are available at http://data.rcc.uchicago.edu/dataset/blanco-cosmology-survey.
ABSTRACT
We describe the derivation and validation of redshift distribution estimates and their uncertainties for the populations of galaxies used as weak-lensing sources in the Dark Energy Survey ...(DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (bpz) code is used to assign galaxies to four redshift bins between z ≈ 0.2 and ≈1.3, and to produce initial estimates of the lensing-weighted redshift distributions $n^i_{\rm PZ}(z)\propto \mathrm{d}n^i/\mathrm{d}z$ for members of bin i. Accurate determination of cosmological parameters depends critically on knowledge of ni, but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts $n^i(z)=n^i_{\rm PZ}(z-\Delta z^i)$ to correct the mean redshift of ni(z) for biases in $n^i_{\rm PZ}$. The Δzi are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the Cosmic Evolution Survey (COSMOS) field to bpz estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the Δzi of the three lowest redshift bins are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15 < z < 0.9. This paper details the bpz and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the ni(z) beyond the choice of Δzi. The clustering and COSMOS validation methods produce consistent estimates of Δzi in the bins where both can be applied, with combined uncertainties of $\sigma_{\Delta z^i}=0.015, 0.013, 0.011,$ and 0.022 in the four bins. Repeating the photo-z procedure instead using the Directional Neighbourhood Fitting algorithm, or using the ni(z) estimated from the matched sample in COSMOS, yields no discernible difference in cosmological inferences.
We present a forward-modeling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfer function-a mapping ...from cosmological/astronomical signals to the final data products used by the scientists. Using output from the cosmological simulations (the Blind Cosmology Challenge), we generate simulated images (the Ultra Fast Image Simulator) and catalogs representative of the DES data. In this work we demonstrate the framework by simulating the 244 deg super(2) coadd images and catalogs in five bands for the DES Science Verification data. The simulation output is compared with the corresponding data to show that major characteristics of the images and catalogs can be captured. We also point out several directions of future improvements. Two practical examples-star-galaxy classification and proximity effects on object detection-are then used to illustrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modeling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies that is sufficiently realistic and highly controllable.
Abstract
We construct the largest curved-sky galaxy weak lensing mass map to date from the DES first-year (DES Y1) data. The map, about 10 times larger than the previous work, is constructed over a ...contiguous ≈1500 deg2, covering a comoving volume of ≈10 Gpc3. The effects of masking, sampling, and noise are tested using simulations. We generate weak lensing maps from two DES Y1 shear catalogues, MetaCalibration and Im3shape, with sources at redshift 0.2 < z < 1.3, and in each of four bins in this range. In the highest signal-to-noise map, the ratio between the mean signal to noise in the E-mode map and the B-mode map is ∼1.5 (∼2) when smoothed with a Gaussian filter of σG = 30 (80) arcmin. The second and third moments of the convergence κ in the maps are in agreement with simulations. We also find no significant correlation of κ with maps of potential systematic contaminants. Finally, we demonstrate two applications of the mass maps: (1) cross-correlation
with different foreground tracers of mass and (2) exploration of the largest peaks and voids in the maps.
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 Ωm - σ8 plane. For one of the suites, we are able to show with high confidence that any biases in the inferred S8 = σ8(Ωm/0.3)0.5 and Ωm 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 60 per cent (70 per cent) probability that systematic bias in the recovered Ωm (S8) is 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.
The Dark Energy Survey (DES) will be unprecedented in its ability to probe exceptionally large cosmic volumes to relatively faint optical limits. Primarily designed for the study of comparatively ...low-redshift (z < 2) galaxies with the aim of constraining dark energy, an intriguing byproduct of the survey will be the identification of massive (>1012.0 M) galaxies at z 4. This will greatly improve our understanding of how galaxies form and evolve. By both passively evolving the low-redshift mass function and extrapolating the observed high-redshift mass function, we find that such galaxies should be rare but nonetheless present at early times, with predicted number densities of ∼0.02 deg−2. The unique combination of depth and coverage that DES provides will allow the identification of such galaxies should they exist - potentially identifying hundreds of such sources. We then model possible high-redshift galaxies and determine their detectability using the DES filter sets and depths. We model sources with a broad range stellar properties and find that for these galaxies to be detected they must be either sufficiently young, high mass and/or relatively dust free (E(B − V) < 0.45) - with these parameters jointly affecting each galaxy's detectability. We also propose colour-colour selection criteria for the identification of both pristine and dusty sources and find that, although contamination fractions will be high, the most reliable candidate massive high-redshift galaxies are likely to be identifiable in the DES data through prioritisation of colour-selected sources.
We compare cosmic microwave background lensing convergence maps derived from South Pole Telescope (SPT) data with galaxy survey data from the Blanco Cosmology Survey, WISE, and a new large ...Spitzer/IRAC field designed to overlap with the SPT survey. Using optical and infrared catalogs covering between 17 and 68 deg super(2) of sky, we detect a correlation between the SPT convergence maps and each of the galaxy density maps at >4sigma, with zero correlation robustly ruled out in all cases. The amplitude and shape of the cross-power spectra are in good agreement with theoretical expectations and the measured galaxy bias is consistent with previous work. The detections reported here utilize a small fraction of the full 2500 deg super(2) SPT survey data and serve as both a proof of principle of the technique and an illustration of the potential of this emerging cosmological probe.
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