Publication details for Prof Richard MasseyKitching, T.D., Rowe, B., Gill, M., Heymans, C., Massey, R., Witherick, D., Courbin, F., Georgatzis, K., Gentile, M., Gruen, D., Kilbinger, M., Li, G.L., Mariglis, A.P., Meylan, G., Storkey, A. & Xin, B. (2013). Image analysis for cosmology: results from the GREAT10 star challenge. The Astrophysical Journal Supplement Series 205(2): 12.
- Publication type: Journal Article
- ISSN/ISBN: 0067-0049, 1538-4365
- DOI: 10.1088/0067-0049/205/2/12
- Keywords: Atmospheric effects, Cosmology: observations, Methods: data analysis, Techniques: image processing.
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
We present the results from the first public blind point-spread function (PSF) reconstruction challenge, the GRavitational lEnsing Accuracy Testing 2010 (GREAT10) Star Challenge. Reconstruction of a spatially varying PSF, sparsely sampled by stars, at non-star positions is a critical part in the image analysis for weak lensing where inaccuracies in the modeled ellipticity e and size R 2 can impact the ability to measure the shapes of galaxies. This is of importance because weak lensing is a particularly sensitive probe of dark energy and can be used to map the mass distribution of large scale structure. Participants in the challenge were presented with 27,500 stars over 1300 images subdivided into 26 sets, where in each set a category change was made in the type or spatial variation of the PSF. Thirty submissions were made by nine teams. The best methods reconstructed the PSF with an accuracy of σ(e) ≈ 2.5 × 10–4 and σ(R 2)/R 2 ≈ 7.4 × 10–4. For a fixed pixel scale, narrower PSFs were found to be more difficult to model than larger PSFs, and the PSF reconstruction was severely degraded with the inclusion of an atmospheric turbulence model (although this result is likely to be a strong function of the amplitude of the turbulence power spectrum).