4.7 Article

Galaxy-galaxy lensing estimators and their covariance properties

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stx1828

关键词

gravitational lensing: weak; galaxies: evolution; large-scale structure of Universe; cosmology: observations

资金

  1. Carnegie Mellon University
  2. Department of Energy Early Career Award program
  3. NASA [NNX15AL17G]
  4. Alfred P. Sloan Foundation
  5. National Science Foundation
  6. U.S. Department of Energy Office of Science
  7. University of Arizona
  8. Brazilian Participation Group
  9. Brookhaven National Laboratory
  10. University of Florida
  11. French Participation Group
  12. German Participation Group
  13. Harvard University
  14. Instituto de Astrofisica de Canarias
  15. Michigan State/Notre Dame/JINA Participation Group
  16. Johns Hopkins University
  17. Lawrence Berkeley National Laboratory
  18. Max Planck Institute for Astrophysics
  19. Max Planck Institute for Extraterrestrial Physics
  20. New Mexico State University
  21. New York University
  22. Ohio State University
  23. Pennsylvania State University
  24. University of Portsmouth
  25. Princeton University
  26. Spanish Participation Group
  27. University of Tokyo
  28. University of Utah
  29. Vanderbilt University
  30. University of Virginia
  31. University of Washington
  32. Yale University
  33. NASA [NNX15AL17G, 799149] Funding Source: Federal RePORTER

向作者/读者索取更多资源

We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.

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