Shankar Agarwal, Hume A. Feldman, Richard Watkins
The estimation and analysis of large-scale bulk flow moments of peculiar velocity surveys is complicated by non-spherical survey geometry, the non-uniform sampling of the matter velocity field by the survey objects, and the typically large measurement errors of the measured line-of-sight velocities. Previously we have developed an optimal "minimum variance" (MV) weighting scheme for using peculiar velocity data to estimate bulk flow moments for idealized dense and isotropic surveys with Gaussian radial distributions that avoids many of these complications. These moments are designed to be easy to interpret and are comparable between surveys. In this paper, we test the robustness of our MV estimators using numerical simulations. Using MV weights, we estimate the underlying bulk flow moments for DEEP, SFI++ and COMPOSITE mock catalogues extracted from the LasDamas and the Horizon Run numerical simulations and compare these estimates to the true moments calculated directly from the simulation boxes. We show that the MV estimators are negligibly affected by nonlinear flows; in particular they are unbiased and have errors that are consistent with predictions from linear theory.
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http://arxiv.org/abs/1201.0128
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