Analyses of peculiar velocity surveys face several challenges, including low signal-to-noise ratio 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 Γ and amplitude β and that our method of analysis effectively removes this bias. We expect that this new method will cause peculiar velocity surveys to reemerge as a useful tool to determine cosmological parameters.
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