Control of systematic errors in obtaining dark energy constraints from galaxy and weak lensing surveys

Michael Schneider
UC Davis


While optical imaging surveys are potentially powerful probes of dark energy, their effectiveness depends critically on the control of a number of systematic errors. I will describe tools and techniques we have developed for mitigating several sources of error in future galaxy clustering and cosmic shear surveys. In particular, we have proposed a method to calibrate photometric redshift errors using the cross-correlation of galaxies at different inferred redshifts and are developing improved shear power spectrum estimators and statistical models of the non-linearly evolved mass-density field with the goal of obtaining unbiased and accurate parameter constraints. The latter work makes use of a new statistical framework for using limited numbers of N-body simulations to build a model for the sample variance distribution of the nonlinear matter power spectrum. The performance of these tools with preliminary models is promising and a demonstration using the Deep Lens Survey data is in the works.