Forecasting the accuracy of velocity-field reconstruction

TL;DR

This paper compares two methods for analyzing galaxy velocities and densities to test cosmological models, highlighting the importance of covariance estimation for accurate growth rate measurements.

Contribution

It introduces a statistical comparison of power-spectrum and reconstruction-and-scaling methods, emphasizing the role of covariance in error estimation.

Findings

Reconstruction errors are underestimated without full covariance inclusion.

Including covariances aligns errors with theoretical forecasts.

The study offers a roadmap for covariance evaluation in different bases.

Abstract

Joint analyses of the large-scale distribution of galaxies, and their motions under the gravitational influence of this density field, allow powerful tests of the cosmological model, including measurement of the growth rate of cosmic structure. In this paper we perform a statistical comparison between two important classes of method for performing these tests. In the first method, which we refer to as the "power-spectrum method", we measure the 2-point power spectra between the velocity and density tracers, and jointly fit these statistics using theoretical models. In the second method, which we refer to as the "reconstruction-and-scaling method", we use the density tracers to reconstruct a model velocity field through space, which we compare with the measured galaxy velocities on a point-by-point basis. By generating an ensemble of numerical simulations in a simplified test scenario, we show that the error in the growth rate inferred by the reconstruction-and-scaling method may be under-estimated, unless the full covariances of the underlying and reconstructed velocity fields are included in the analysis. In this case the inferred growth rate errors agree with both the power-spectrum method and a Fisher matrix forecast. We provide a roadmap for evaluating these covariances, considering reconstruction performed using both a Fourier basis within a cuboid, and a Spherical Fourier-Bessel basis within a curved-sky observational volume.