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# Testing the minimum variance method for estimating large-scale velocity moments

Monthly Notices of the Royal Astronomical Society (Impact Factor: 5.11). 12/2011; 424(4). DOI: 10.1111/j.1365-2966.2012.21345.x

Source: arXiv

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Hume A. Feldman, Available from: Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.

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**ABSTRACT:**We calculate the cosmic Mach number M - the ratio of the bulk flow of the velocity field on scale R to the velocity dispersion within regions of scale R. M is effectively a measure of the ratio of large-scale to small-scale power and can be a useful tool to constrain the cosmological parameter space. Using a compilation of existing peculiar velocity surveys, we calculate M and compare it to that estimated from mock catalogues extracted from the Large Suite of Dark Matter Simulations (LasDamas, a Λ cold dark matter cosmology) numerical simulations. We find agreement with expectations for the LasDamas cosmology at ˜1.5σ confidence level. We also show that our Mach estimates for the mocks are not biased by selection function effects. To achieve this, we extract dense and nearly isotropic distributions using Gaussian selection functions with the same width as the characteristic depth of the real surveys, and show that the Mach numbers estimated from the mocks are very similar to the values based on Gaussian profiles of the corresponding widths. We discuss the importance of the survey window functions in estimating their effective depths. We investigate the non-linear matter power spectrum interpolator PKANN as an alternative to numerical simulations, in the study of Mach number.Monthly Notices of the Royal Astronomical Society 06/2013; 432(1):307-317. DOI:10.1093/mnras/stt464 · 5.11 Impact Factor -
##### Article: An Unbiased Estimator of Peculiar Velocity with Gaussian Distributed Errors for Precision Cosmology

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**ABSTRACT:**We introduce a new estimator of the peculiar velocity of a galaxy or group of galaxies from redshift and distance estimates. This estimator results in peculiar velocity estimates which are statistically unbiased and have Gaussian distributed errors, thus complying with the assumptions of analyses that rely on individual peculiar velocities. We apply this estimator to the SFI++ and the Cosmicflows-2 catalogues of galaxy distances and, since peculiar velocity estimates of distant galaxies are error dominated, examine their error distributions. The adoption of the new estimator significantly improves the accuracy and validity of studies of the large-scale peculiar velocity field that assume Gaussian distributed velocity errors and eliminates potential systematic biases, thus helping to bring peculiar velocity analysis into the era of precision cosmology. In addition, our method of examining the distribution of velocity errors should provide a useful check of the statistics of large peculiar velocity catalogues, particularly those that are compiled out of data from multiple sources.Monthly Notices of the Royal Astronomical Society 11/2014; 450(2). DOI:10.1093/mnras/stv651 · 5.11 Impact Factor