Galaxy shear estimation from stacked images
Article first published online: 3 AUG 2009
DOI: 10.1111/j.1365-2966.2009.15161.x
© 2009 The Author. Journal compilation © 2009 RAS
Issue

Monthly Notices of the Royal Astronomical Society
Volume 398, Issue 1, pages 471–476, September 2009
Additional Information
How to Cite
Lewis, A. (2009), Galaxy shear estimation from stacked images. Monthly Notices of the Royal Astronomical Society, 398: 471–476. doi: 10.1111/j.1365-2966.2009.15161.x
Publication History
- Issue published online: 19 AUG 2009
- Article first published online: 3 AUG 2009
- Accepted 2009 May 29. Received 2009 May 18; in original form 2009 January 12
- Abstract
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Keywords:
- gravitational lensing;
- methods: data analysis
ABSTRACT
Statistics of the weak lensing of galaxies can be used to constrain cosmology if the galaxy shear can be estimated accurately. In general, this requires accurate modelling of unlensed galaxy shapes and the point spread function (PSF). I discuss suboptimal but potentially robust methods for estimating galaxy shear by stacking images such that the stacked-image distribution is closely Gaussian by the central limit theorem. The shear can then be determined by radial fitting, requiring only an accurate model of the PSF rather than also needing to model each galaxy accurately. When noise is significant, asymmetric errors in the centroid must be corrected, but the method may ultimately be able to give accurate unbiased results when there is a high galaxy density with constant shear. It provides a useful baseline for more optimal methods, and a test case for estimating biases, though the method is not directly applicable to realistic data. I test stacking methods on the simple toy simulations with constant PSF and shear provided by the GREAT08 project, on which most other existing methods perform significantly more poorly, and briefly discuss generalizations to more realistic cases. In the Appendix, I discuss a simple analytic galaxy population model where stacking gives optimal errors in a perfect ideal case.

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