Estimating cosmic velocity fields from density fields and tidal tensors

Details Estimating cosmic velocity fields from density fields and tidal tensors Estimating cosmic velocity fields from density fields and tidal tensors

2011-11-28

arxiv.org/abs/1111.6629v1

Astronomy and Astrophysics

Astrophysics

Cosmology and Extragalactic Astrophysics

15 pages, 9 figures, 1 table

Scientific paper

In this work we investigate the nonlinear and nonlocal relation between cosmological density and peculiar velocity fields. Our goal is to provide an algorithm for the reconstruction of the nonlinear velocity field from the fully nonlinear density. We find that including the gravitational tidal field tensor using second order Lagrangian perturbation theory (2LPT) based upon an estimate of the linear component of the nonlinear density field significantly improves the estimate of the cosmic flow in comparison to linear theory not only in the low density, but also and more dramatically in the high density regions. In particular we test two estimates of the linear component: the lognormal model and the iterative Lagrangian linearisation. The present approach relies on a rigorous higher order Lagrangian perturbation theory analysis which incorporates a nonlocal relation. It does not require additional fitting from simulations being in this sense parameter free, it is independent of statistical-geometrical optimisation and it is straightforward and efficient to compute. The method is demonstrated to yield an unbiased estimator of the velocity field on scales >~5 h^{-1}Mpc with closely Gaussian distributed errors. Moreover, the statistics of the divergence of the peculiar velocity field is extremely well recovered showing a good agreement with the true one from N-body simulations. The typical errors of about 10 km/s (1 sigma confidence intervals) are reduced by more than 80% with respect to linear theory in the scale range between 5 and 10 h^{-1}Mpc in high density regions (delta>2). We also find that iterative Lagrangian linearisation is significantly superior in the low density regime with respect to the lognormal model.

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