Not a Copernican observer: biased peculiar velocity statistics in the local Universe

Abstract

We assess the effect of the local large scale structure on the estimation of two-point statistics of the observed radial peculiar velocities of galaxies. A large N-body simulation is used to examine these statistics from the perspective of random observers as well as "Local Group (LG)-like" observers conditioned to reside in an environment resembling the observed universe within 20 Mpc. The local environment systematically distorts the shape and amplitude of velocity statistics with respect to ensemble-averaged measurements made by a Copernican (random) observer. The Virgo cluster has the most significant impact, introducing large systematic deviations in all the statistics. For a simple "top-hat" selection function, an idealized survey extending to $\sim 160h^{-1}\mathrm{Mpc}$ or deeper is needed to completely mitigate the effects of the local environment. Using shallower catalogues leads to systematic deviations of the order of $50$ to $200\%$ depending on the scale considered. For a flat redshift distribution similar to the one of the CosmicFlows-3 survey, the deviations are even more prominent in both the shape and amplitude at all separations considered $(\stackrel{<}{{}_{\sim }}100h^{-1}\mathrm{Mpc})$. Conclusions based on statistics calculated without taking into account the impact of the local environment should be revisited.

10 pages, 4 figures, submitted to MNRAS, comments are welcome

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Cited by in corpus (7)

• Analyzing the Large-Scale Bulk Flow using CosmicFlows4: Increasing Tension with the Standard Cosmological Model
• Caught in the cosmic web: Environmental effect on halo concentrations, shape, and spin
• An estimation of the Local growth rate from Cosmicflows-3 peculiar velocities
• Statistics of a single sky: constrained random fields and the imprint of Bardeen potentials on galaxy clustering
• Complementary consistency test of the Copernican principle via Noether's theorem and machine learning forecasts
• Peculiar Velocity Reconstruction From Simulations and Observations Using Deep Learning Algorithms
• Impact of our local environment on cosmological statistics