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

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 $\mathrm{\Gamma }$ 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.