Power spectrum estimation from peculiar velocity catalogues

E. MacAulay*, H. A. Feldman, P. G. Ferreira, A. H. Jaffe, S. Agarwal, M. J. Hudson, R. Watkins

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The peculiar velocities of galaxies are an inherently valuable cosmological probe, providing an unbiased estimate of the distribution of matter on scales much larger than the depth of the survey. Much research interest has been motivated by the high dipole moment of our local peculiar velocity field, which suggests a large-scale excess in the matter power spectrum and can appear to be in some tension with the Λ cold dark matter (ΛCDM) model. We use a composite catalogue of 4537 peculiar velocity measurements with a characteristic depth of 33 h -1Mpc to estimate the matter power spectrum. We compare the constraints with this method, directly studying the full peculiar velocity catalogue, to results by Macaulay et al., studying minimum variance moments of the velocity field, as calculated by Feldman, Watkins & Hudson. We find good agreement with the ΛCDM model on scales of k > 0.01hMpc -1. We find an excess of power on scales of k < 0.01hMpc -1 with a 1σ uncertainty which includes the ΛCDM model. We find that the uncertainty in excess at these scales is larger than an alternative result studying only moments of the velocity field, which is due to the minimum variance weights used to calculate the moments. At small scales, we are able to clearly discriminate between linear and non-linear clustering in simulated peculiar velocity catalogues and find some evidence (although less clear) for linear clustering in the real peculiar velocity data.

Original languageEnglish
Pages (from-to)1709-1717
Number of pages9
JournalMonthly Notices of the Royal Astronomical Society
Issue number3
Publication statusPublished - 21 Sept 2012


  • Cosmology
  • Galaxies
  • Kinematics and dynamics
  • Large-scale structure of universe
  • Observations
  • Statistics
  • Theory


Dive into the research topics of 'Power spectrum estimation from peculiar velocity catalogues'. Together they form a unique fingerprint.

Cite this