DES Y1 Results: Validating cosmological parameter estimation using simulated Dark Energy Surveys
N. MacCrann, J. DeRose, R. H. Wechsler, J. Blazek, E. Gaztanaga, M., Crocce, E. S. Rykoff, M. R. Becker, B. Jain, E. Krause, T. F. Eifler, D., Gruen, J. Zuntz, M. A. Troxel, J. Elvin-Poole, J. Prat, M. Wang, S. Dodelson,, A. Kravtsov, P. Fosalba, M. T. Busha, A. E. Evrard

TL;DR
This paper validates cosmological parameter estimation methods for the Dark Energy Survey Year 1 data using simulated galaxy surveys, confirming the robustness of the analysis and identifying potential biases.
Contribution
It introduces two independent simulation suites to test and validate the cosmological parameter inference methods used in DES Y1 analysis.
Findings
Input cosmology consistent with constraints in simulations.
Biases in key parameters are smaller than Y1 uncertainties.
Validation confirms robustness of the analysis methods.
Abstract
We use mock galaxy survey simulations designed to resemble the Dark Energy Survey Year 1 (DES Y1) data to validate and inform cosmological parameter estimation. When similar analysis tools are applied to both simulations and real survey data, they provide powerful validation tests of the DES Y1 cosmological analyses presented in companion papers. We use two suites of galaxy simulations produced using different methods, which therefore provide independent tests of our cosmological parameter inference. The cosmological analysis we aim to validate is presented in DES Collaboration et al. (2017) and uses angular two-point correlation functions of galaxy number counts and weak lensing shear, as well as their cross-correlation, in multiple redshift bins. While our constraints depend on the specific set of simulated realisations available, for both suites of simulations we find that the input…
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