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

TL;DR

This paper measures how galaxy bias evolves with redshift using combined galaxy density and weak lensing maps from DES SV data, providing a novel, $\sigma_8$-independent constraint and insights into dark matter distribution.

Contribution

It applies a previously developed method to DES SV data to measure galaxy bias across redshifts, including a $\sigma_8$-independent constraint and a 3D mass map.

Findings

Galaxy bias measurements are consistent with other methods within 2σ.

The method provides a $\sigma_8$-independent constraint on galaxy bias.

Constructed a 3D mass map for dark matter exploration.

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 1{\sigma} 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.