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

 

Authors: A. I. Salvador, F. J. Sánchez, A. Pagul et al.
Journal:  
Year: 07/2018
Download: ADS| Arxiv


Abstract

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 $\delta_{g} = \sum_{k=0}^{3} (b_{k}/k!) \delta^{k}$, finding a non-zero value for $b_2$ at the $3\sigma$ 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 $h^{-1}$)

A highly precise shape-noise-free shear bias estimator

 

Authors: A. Pujol, M. Kilbinger, F. Sureau et al.
Journal:  
Year: 06/2018
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Abstract

We present a new method to estimate shear measurement bias in image simulations that significantly improves its precision with respect to the state-of-the-art methods. This method is based on measuring the shear response for individual images. We generate sheared versions of the same image to measure how the shape measurement changes with the changes in the shear, so that we obtain a shear response for each original image, as well as its additive bias. Using the exact same noise realizations for each sheared version allows us to obtain an exact estimation of its shear response. The estimated shear bias of a sample of galaxies comes from the measured averages of the shear response and individual additive bias. The precision of this method supposes an improvement with respect to previous methods since our method is not affected by shape noise. As a consequence, the method does not require shape noise cancellation for a precise estimation of shear bias. The method can be easily applied to many applications such as shear measurement validation and calibration, reducing the number of necessary simulated images by a few orders of magnitude to achieve the same precision requirements.

The Dark Energy Survey Data Release 1

 

Authors: DES Collaboration
Journal:  
Year: 01/2018
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Abstract

We describe the first public data release of the Dark Energy Survey, DES DR1, consisting of reduced single epoch images, coadded images, coadded source catalogs, and associated products and services assembled over the first three years of DES science operations. DES DR1 is based on optical/near-infrared imaging from 345 distinct nights (August 2013 to February 2016) by the Dark Energy Camera mounted on the 4-m Blanco telescope at Cerro Tololo Inter-American Observatory in Chile. We release data from the DES wide-area survey covering ~5,000 sq. deg. of the southern Galactic cap in five broad photometric bands, grizY. DES DR1 has a median delivered point-spread function of g = 1.12, r = 0.96, i = 0.88, z = 0.84, and Y = 0.90 arcsec FWHM, a photometric precision of < 1% in all bands, and an astrometric precision of 151 mas. The median coadded catalog depth for a 1.95" diameter aperture at S/N = 10 is g = 24.33, r = 24.08, i = 23.44, z = 22.69, and Y = 21.44 mag. DES DR1 includes nearly 400M distinct astronomical objects detected in ~10,000 coadd tiles of size 0.534 sq. deg. produced from ~39,000 individual exposures. Benchmark galaxy and stellar samples contain ~310M and ~ 80M objects, respectively, following a basic object quality selection. These data are accessible through a range of interfaces, including query web clients, image cutout servers, jupyter notebooks, and an interactive coadd image visualization tool. DES DR1 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

Cosmic CARNage I: on the calibration of galaxy formation models

 

Authors: A. Knebe, F. R. Pearce, V. Gonzalez-Perez et al.
Journal:  
Year: 12/2017
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Abstract

We present a comparison of nine galaxy formation models, eight semi-analytical and one halo occupation distribution model, run on the same underlying cold dark matter simulation (cosmological box of co-moving width 125h1 Mpc, with a dark-matter particle mass of 1.24×109h1 Msun) and the same merger trees. While their free parameters have been calibrated to the same observational data sets using two approaches, they nevertheless retain some 'memory' of any previous calibration that served as the starting point (especially for the manually-tuned models). For the first calibration, models reproduce the observed z = 0 galaxy stellar mass function (SMF) within 3-{\sigma}. The second calibration extended the observational data to include the z = 2 SMF alongside the z~0 star formation rate function, cold gas mass and the black hole-bulge mass relation. Encapsulating the observed evolution of the SMF from z = 2 to z = 0 is found to be very hard within the context of the physics currently included in the models. We finally use our calibrated models to study the evolution of the stellar-to-halo mass (SHM) ratio. For all models we find that the peak value of the SHM relation decreases with redshift. However, the trends seen for the evolution of the peak position as well as the mean scatter in the SHM relation are rather weak and strongly model dependent. Both the calibration data sets and model results are publicly available.

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

 

Authors: DES Collaboration
Journal:  
Year: 08/2017
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Abstract

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 $\Lambda$CDM and $w$CDM cosmologies, marginalizing over 20 nuisance parameters, varying 6 (for $\Lambda$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 $S_8 \equiv \sigma_8 (\Omega_m/0.3)^{0.5} = 0.783^{+0.021}_{-0.025}$ and $\Omega_m = 0.264^{+0.032}_{-0.019}$ for $\Lambda$CDM for $w$CDM, we find $S_8 = 0.794^{+0.029}_{-0.027}$, $\Omega_m = 0.279^{+0.043}_{-0.022}$, 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 $\Omega_m$ are lower than the central values from Planck ...

Dark Energy Survey Year 1 Results: Curved-Sky Weak Lensing Mass Map

 

Authors: C. Chang, A. Pujol, B. Mawdsley et al.
Journal:  
Year: 08/2017
Download: ADS| Arxiv


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 previous work, is constructed over a contiguous $\approx1,500 $deg$^2$, covering a comoving volume of $\approx10 $Gpc$^3$. The effects of masking, sampling, and noise are tested using simulations. We generate weak lensing maps from two DES Y1 shear catalogs, 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 and the B-mode map is $\sim$1.5 ($\sim$2) when smoothed with a Gaussian filter of $\sigma_{G}=30$ (80) arcminutes. The second and third moments of the convergence $\kappa$ in the maps are in agreement with simulations. We also find no significant correlation of $\kappa$ 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.

Shear measurement bias: dependencies on methods, simulation parameters and measured parameters

 

Authors: A. Pujol, F. Sureau, J. Bobin et al.
Journal: A&A
Year: 06/2017
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Abstract

We present a study of the dependencies of shear and ellipticity bias on simulation (input) and measured (output) parameters, noise, PSF anisotropy, pixel size and the model bias coming from two different and independent shape estimators. We use simulated images from Galsim based on the GREAT3 control-space-constant branch and we measure ellipticity and shear bias from a model-fitting method (gFIT) and a moment-based method (KSB). We show the bias dependencies found on input and output parameters for both methods and we identify the main dependencies and causes. We find consistent results between the two methods (given the precision of the analysis) and important dependencies on orientation and morphology properties such as flux, size and ellipticity. We show cases where shear bias and ellipticity bias behave very different for the two methods due to the different nature of these measurements. We also show that noise and pixelization play an important role on the bias dependences on the output properties. We find a large model bias for galaxies consisting of a bulge and a disk with different ellipticities or orientations. We also see an important coupling between several properties on the bias dependences. Because of this we need to study several properties simultaneously in order to properly understand the nature of shear bias.

nIFTy Cosmology: the clustering consistency of galaxy formation models

 

Authors: A. Pujol, R. A. Skibba, E. Gaztañaga et al.
Journal: MNRAS
Year: 02/2017
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Abstract

We present a clustering comparison of 12 galaxy formation models (including Semi-Analytic Models (SAMs) and Halo Occupation Distribution (HOD) models) all run on halo catalogues and merger trees extracted from a single {\Lambda}CDM N-body simulation. We compare the results of the measurements of the mean halo occupation numbers, the radial distribution of galaxies in haloes and the 2-Point Correlation Functions (2PCF). We also study the implications of the different treatments of orphan (galaxies not assigned to any dark matter subhalo) and non-orphan galaxies in these measurements. Our main result is that the galaxy formation models generally agree in their clustering predictions but they disagree significantly between HOD and SAMs for the orphan satellites. Although there is a very good agreement between the models on the 2PCF of central galaxies, the scatter between the models when orphan satellites are included can be larger than a factor of 2 for scales smaller than 1 Mpc/h. We also show that galaxy formation models that do not include orphan satellite galaxies have a significantly lower 2PCF on small scales, consistent with previous studies. Finally, we show that the 2PCF of orphan satellites is remarkably different between SAMs and HOD models. Orphan satellites in SAMs present a higher clustering than in HOD models because they tend to occupy more massive haloes. We conclude that orphan satellites have an important role on galaxy clustering and they are the main cause of the differences in the clustering between HOD models and SAMs.

What determines large scale galaxy clustering: halo mass or local density?

 

Authors: A. Pujol, K. Hoffmann, N. Jiménez et al.
Journal: A&A
Year: 02/2017
Download: ADS| Arxiv


Abstract

Using a dark matter simulation we show how halo bias is determined by local density and not by halo mass. This is not totally surprising as, according to the peak-background split model, local matter density (bar δ) is the property that constrains bias at large scales. Massive haloes have a high clustering because they reside in high density regions. Small haloes can be found in a wide range of environments which differentially determine their clustering amplitudes. This contradicts the assumption made by standard halo occupation distribution (HOD) models that bias and occupation of haloes is determined solely by their mass. We show that the bias of central galaxies from semi-analytic models of galaxy formation as a function of luminosity and colour is therefore not correctly predicted by the standard HOD model. Using bar δ (of matter or galaxies) instead of halo mass, the HOD model correctly predicts galaxy bias. These results indicate the need to include information about local density and not only mass in order to correctly apply HOD analysis in these galaxy samples. This new model can be readily applied to observations and has the advantage that, in contrast with the dark matter halo mass, the galaxy density can be directly observed.

A new method to measure galaxy bias by combining the density and weak lensing fields

 

Authors: A. Pujol, C. Chang, E. Gaztañaga et al.
Journal: MNRAS
Year: 10/2016
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Abstract

We present a new method to measure redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on the work of Amara et al., who use the galaxy density field to construct a bias-weighted convergence field κg. The main difference between Amara et al.'s work and our new implementation is that here we present another way to measure galaxy bias, using tomography instead of bias parametrizations. The correlation between κg and the true lensing field κ allows us to measure galaxy bias using different zero-lag correlations, such as <κgκ>/<κκ> or <κgκg>/<κgκ>. Our method measures the linear bias factor on linear scales, under the assumption of no stochasticity between galaxies and matter. We use the Marenostrum Institut de Ciències de l'Espai (MICE) simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This article is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method and the regime in which it is consistent with the linear galaxy bias defined by projected two-point correlation functions (2PCF). We find that our method is consistent with a linear bias at the per cent level for scales larger than 30 arcmin, while non-linearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on σ8 as do the 2PCF measurements. We will apply this method to the Dark Energy Survey Science Verification data in a follow-up article.