Goodness-of-fit analysis of the Cosmicflows-2 database of velocities

TL;DR

This study assesses the Cosmicflows-2 velocity data's compatibility with the LCDM cosmological model using bulk flow analysis, confirming consistency within 2 sigma confidence limits.

Contribution

Introduces a bulk velocity-based goodness-of-fit method using Wiener filter reconstruction to evaluate the Cosmicflows-2 data against the LCDM model.

Findings

CF2 data is consistent with LCDM within 2 sigma

Bulk flow analysis effectively filters small-scale nonlinear effects

Method validates the data's compatibility with standard cosmology

Abstract

The goodness-of-fit (GoF) of the Cosmicflows-2 (CF2) database of peculiar velocities with the LCDM standard model of cosmology is presented. Standard application of the Chi^2 statistics of the full database, of its 4,838 data points, is hampered by the small scale nonlinear dynamics which is not accounted for by the (linear regime) velocity power spectrum. The bulk velocity constitutes a highly compressed representation of the data which filters out the small scales non-linear modes. Hence the statistics of the bulk flow provides an efficient tool for assessing the GoF of the data given a model. The particular approach introduced here is to use the (spherical top-hat window) bulk velocity extracted from the Wiener filter reconstruction of the 3D velocity field as a linear low pass filtered highly compressed representation of the CF2 data. An ensemble 2250 random linear realizations of the WMAP/LCDM model has been used to calculate the bulk velocity auto-covariance matrix. We find that the CF2 data is consistent with the WMAP/LCDM model to better than the 2 sigma confidence limits. This provides a further validation that the CF2 database is consistent with the standard model of cosmology.