Breaking the degeneracy: Optimal use of three-point weak lensing statistics

Sanaz Vafaei, Tingting Lu, Ludovic van Waerbeke, Elisabetta Semboloni, Catherine Heymans, Ue-Li Pen

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

We study the optimal use of three-point statistics in the analysis of weak lensing by large-scale structure. The three-point statistics have long been advocated as a powerful tool to break measured degeneracies between cosmological parameters. Using ray-tracing simulations. incorporating important survey features such as a realistic depth-dependent redshift distribution, we find that a joint two- and three-point correlation function analysis is a much stronger probe of cosmology than the skewness statistic. We compare different observing strategies, showing that for a limited survey time there is an optimal depth for the measurement of three-point statistics, which balances statistical noise and cosmic variance against signal amplitude. We find that the chosen CFHTIS observing strategy was optimal and forecast that a joint two- and three-point analysis of the completed CFHTLS-Wide will constrain the amplitude of the matter power spectrum sigma(8) to 10% and the matter density parameter Omega(m) to 17%, a factor of 2.5 improvement on the two-point analysis alone. Our error analysis includes all non-Gaussian terms, finding that the coupling between cosmic variance and shot noise is a non-negligible contribution which should be included in any future analytical error calculations. (C) 2009 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)340-351
Number of pages12
JournalAstroparticle Physics
Volume32
Issue number6
DOIs
Publication statusPublished - Jan 2010

Keywords / Materials (for Non-textual outputs)

  • Weak gravitational lensing
  • Cosmology
  • N-BODY SIMULATIONS
  • CFHT LEGACY SURVEY
  • COSMIC SHEAR
  • COSMOLOGICAL PARAMETERS
  • 2-POINT STATISTICS
  • POWER SPECTRUM
  • PROBE
  • CONSTRAINTS
  • CONTAMINATION
  • COVARIANCES

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