期刊
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
卷 389, 期 4, 页码 1739-1749出版社
WILEY-BLACKWELL
DOI: 10.1111/j.1365-2966.2008.13637.x
关键词
surveys; galaxies : kinematics and dynamics; cosmological parameters; galaxies : statistics; large-scale structure of Universe
资金
- Royal Society
- Leverhulme Trust
- Science and Technology Facilities Council [PP/F001118/1, ST/G504284/1] Funding Source: researchfish
- STFC [ST/G504284/1, ST/F001991/1, PP/F001118/1] Funding Source: UKRI
We investigate methods to best estimate the normalization of the mass density fluctuation power spectrum (sigma(8)) using peculiar velocity data from a survey like the six-degree Field Galaxy Velocity Survey (6dFGSv). We focus on two potential problems: (i) biases from non-linear growth of structure and (ii) the large number of velocities in the survey. Simulations of Lambda CDM-like models are used to test the methods. We calculate the likelihood from a full covariance matrix of velocities averaged in grid cells. This simultaneously reduces the number of data points and smoothes out non-linearities which tend to dominate on small scales. We show how the averaging can be taken into account in the predictions in a practical way, and show the effect of the choice of cell size. We find that a cell size can be chosen that significantly reduces the non-linearities without significantly increasing the error bars on cosmological parameters. We compare our results with those from a principal components analysis following Watkins et al. and Feldman et al. to select a set of optimal moments constructed from linear combinations of the peculiar velocities that are least sensitive to the non-linear scales. We conclude that averaging in grid cells performs equally well. We find that for a survey such as 6dFGSv we can estimate sigma(8) with less than 3 per cent bias from non-linearities. The expected error on sigma(8) after marginalizing over Omega(m) is approximately 16 per cent.
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