Peculiar velocity surveys: optimal moments analysis.
A new formalism to analyze peculiar velocity surveys is presented. Results from these surveys are shown to be dominated by small-scale noise, aliasing, and incomplete cancellations. The formalism allows us to filter out the signal from scales that are not of interest and thus provides us with a clean signal that probe large scales. We use maximum likelihood techniques to analyze the filtered data and compare it to the analysis of the full dataset. The filtered analysis gives a much better parameter estimation than the full analysis, leading us to conclude that, indeed, the large-scale signal is obscured by small-scale noise.
Feldman
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Department of Physics and Astronomy, University of Kansas, Lawrence, Kansas 66045, USA. feldman@ku.edu
Watkins
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Melott
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Gorman
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