Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps

Abstract

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a $\sim$116 deg${}^2$ area of the Dark Energy Survey (DES) Science Verification data. This method was first developed in Amara et al. (2012) and later re-examined in a companion paper (Pujol et al. 2016) with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i$<$22.5 galaxy sample. We find the galaxy bias and 1$\sigma$ error bars in 4 photometric redshift bins to be 1.12$\pm$0.19 (z=0.2-0.4), 0.97$\pm$0.15 (z=0.4-0.6), 1.38$\pm$0.39 (z=0.6-0.8)), and 1.45$\pm$0.56 (z=0.8-1.0). These measurements are consistent at the 2$\sigma$ level with measurements on the same dataset using galaxy clustering and cross-correlation of galaxies with CMB lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only ${\sigma }_8$-independent constraint among the three. We forward-model the main observational effects using mock galaxy catalogs by including shape noise, photo-z errors and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

14 pages, 9 figures, 2 table; to be published in MNRAS; update title/affiliation to match journal version

References in corpus (10)

• Why your model parameter confidences might be too optimistic -- unbiased estimation of the inverse covariance matrix
• The Blanco Cosmology Survey: Data Acquisition, Processing, Calibration, Quality Diagnostics and Data Release
• Photometric redshift analysis in the Dark Energy Survey Science Verification data
• An algorithm to build mock galaxy catalogues using MICE simulations
• SDSS Galaxy Clustering: Luminosity & Colour Dependence and Stochasticity
• An Implementation of Bayesian Lensing Shear Measurement
• Scale Dependent Galaxy Bias in the SDSS as a function of Luminosity and Colour
• GaBoDS: The Garching-Bonn Deep Survey: VII. Probing galaxy bias using weak gravitational lensing
• A new method to measure galaxy bias by combining the density and weak lensing fields
• Cyber-infrastructure to Support Science and Data Management for the Dark Energy Survey

Cited by in corpus (21)

• Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
• The Dark Energy Survey: more than dark energy - an overview
• Neutrino Mass Ordering from Oscillations and Beyond: 2018 Status and Future Prospects
• Dark Energy Survey Year 1 Results: Galaxy-Galaxy Lensing
• Dark Energy Survey Year 1 Results: Curved-Sky Weak Lensing Mass Map
• Determining the progenitors of merging black-hole binaries
• Two- and three-dimensional wide-field weak lensing mass maps from the Hyper Suprime-Cam Subaru Strategic Program S16A data
• Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV
• Weak Lensing Tomographic Redshift Distribution Inference for the Hyper Suprime-Cam Subaru Strategic Program three-year shape catalogue
• Weak lensing magnification in the Dark Energy Survey Science Verification Data
• Scale dependence of galaxy biasing investigated by weak gravitational lensing: An assessment using semi-analytic galaxies and simulated lensing data
• Linear and non-linear bias: predictions vs. measurements
• Cross-correlating 21 cm and galaxy surveys: implications for cosmology and astrophysics
• Cross-correlating 2D and 3D galaxy surveys
• A new method to measure galaxy bias by combining the density and weak lensing fields
• A Composite Likelihood Approach for Inference under Photometric Redshift Uncertainty
• Lensing corrections to the $E_g(z)$ statistics from large scale structure
• Measuring Linear and Non-linear Galaxy Bias Using Counts-in-Cells in the Dark Energy Survey Science Verification Data
• Galaxy bias from galaxy-galaxy lensing in the DES Science Verification Data
• Dark Energy Survey Year 1 Results: Wide field mass maps via forward fitting in harmonic space
• Searching for Dark Structures: A Comparison of Weak-lensing Convergence Maps and Lensing-weighted Galaxy Density Maps