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We measure the redshift evolution of galaxy bias for a magnitude-limitedgalaxy sample by combining the galaxy density maps and weak lensing shear mapsfor a $\sim$116 deg$^{2}$ area of the Dark Energy Survey (DES) ScienceVerification data. This method was first developed in Amara et al. (2012) andlater re-examined in a companion paper (Pujol et al. 2016) with rigoroussimulation tests and analytical treatment of tomographic measurements. In thiswork we apply this method to the DES SV data and measure the galaxy bias for ai$<$22.5 galaxy sample. We find the galaxy bias and 1$\sigma$ error bars in 4photometric 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$0.56 (z=0.8-1.0). Thesemeasurements are consistent at the 2$\sigma$ level with measurements on thesame dataset using galaxy clustering and cross-correlation of galaxies with CMBlensing, with most of the redshift bins consistent within the 1{\sigma} errorbars. In addition, our method provides the only $\sigma_8$-independentconstraint among the three. We forward-model the main observational effectsusing mock galaxy catalogs by including shape noise, photo-z errors and maskingeffects. We show that our bias measurement from the data is consistent withthat expected from simulations. With the forthcoming full DES data set, weexpect this method to provide additional constraints on the galaxy biasmeasurement from more traditional methods. Furthermore, in the process of ourmeasurement, we build up a 3D mass map that allows further exploration of thedark matter distribution and its relation to galaxy evolution.

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