The Shear Testing Programme – I. Weak lensing analysis of simulated ground-based observations

By Catherine Heymans, L. Waerbeke, D. Bacon, J. Bergé, G. Bernstein, E. Bertin, Sarah Bridle, Michael L. Brown, D. Clowe, H. Dahle and 15 more. 2005

376 citations recorded by the source corpus.

The Shear Testing Programme (STEP) is a collaborative project to improve the accuracy and reliability of all weak lensing measurements in preparation for the next generation of wide-field surveys. In this first STEP paper, we present the results of a blind analysis of simulated ground-based observations of relatively simple galaxy morphologies. The most successful methods are shown to achieve percent level accuracy. From the cosmic shear pipelines that have been used to constrain cosmology, we find weak lensing shear measured to an accuracy that is within the statistical errors of current weak lensing analyses, with shear measurements accurate to better than 7 per cent. The dominant source of measurement error is shown to arise from calibration uncertainties where the measured shear is over or underestimated by a constant multiplicative factor. This is of concern as calibration errors cannot be detected through standard diagnostic tests. The measured calibration errors appear to result from stellar contamination, false object detection, the shear measurement method itself, selection bias and/or the use of biased weights. Additive systematics (false detections of shear) resulting from residual point-spread function anisotropy are, in most cases, reduced to below an equivalent shear of 0.001, an order of magnitude below cosmic shear distortions on the scales probed by current surveys. Our results provide a snapshot view of the accuracy of current ground-based weak lensing methods and a benchmark upon which we can improve. To this end we provide descriptions of each method tested and include details of the eight different implementations of the commonly used Kaiser, Squires & Broadhurst method (KSB+) to aid the improvement of future KSB+ analyses.

View Paper: https://www.semanticscholar.org/paper/9b8124f6bccc1b2abec23dd7ec73804bdc114f58

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  1. H. Hoekstra
  2. Rachel Mandelbaum
  3. Catherine Heymans
  4. P. Hopkins
  5. H. Hildebrandt
  6. M. Bartelmann
  7. B. Joachimi
  8. Andrey V. Kravtsov

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