Optimal Moments for the Analysis of Peculiar Velocity Surveys II: Testing

Abstract

Analyses of peculiar velocity surveys face several challenges, including low signal--to--noise in individual velocity measurements and the presence of small--scale, nonlinear flows. This is the second in a series of papers in which we describe a new method of overcoming these problems by using data compression as a filter with which to separate large--scale, linear flows from small--scale noise that can bias results. We demonstrate the effectiveness of our method using realistic catalogs of galaxy velocities drawn from N--body simulations. Our tests show that a likelihood analysis of simulated catalogs that uses all of the information contained in the peculiar velocities results in a bias in the estimation of the power spectrum shape parameter $\Gamma$ and amplitude $\beta$, and that our method of analysis effectively removes this bias. We expect that this new method will cause peculiar velocity surveys to re--emerge as a useful tool to determine cosmological parameters.