paper

ASKI: full-sky lensing map making algorithms

arXiv:0901.2001 · doi:10.1111/j.1365-2966.2009.15609.x

Abstract

Within the context of upcoming full-sky lensing surveys, the edge-preserving non- linear algorithm Aski is presented. Using the framework of Maximum A Posteriori inversion, it aims at recovering the full-sky convergence map from surveys with masks. It proceeds in two steps: CCD images of crowded galactic fields are deblurred using automated edge-preserving deconvolution; once the reduced shear is estimated, the convergence map is also inverted via an edge- preserving method. For the deblurring, it is found that when the observed field is crowded, this gain can be quite significant for realistic ground-based surveys when both positivity and edge-preserving penalties are imposed during the iterative deconvolution. For the convergence inversion, the quality of the reconstruction is investigated on noisy maps derived from the horizon N-body simulation, with and without Galactic cuts, and quantified using one-point statistics, power spectra, cluster counts, peak patches and the skeleton. It is found that the reconstruction is able to interpolate and extrapolate within the Galactic cuts/non-uniform noise; its sharpness-preserving penalization avoids strong biasing near the clusters of the map; it reconstructs well the shape of the PDF as traced by its skewness and kurtosis; the geometry and topology of the reconstructed map is close to the initial map as traced by the peak patch distribution and the skeleton's differential length; the two-points statistics of the recovered map is consistent with the corresponding smoothed version of the initial map; the distribution of point sources is also consistent with the corresponding smoothing, with a significant improvement when edge preserving prior is applied. The contamination of B-modes when realistic Galactic cuts are present is also investigated. Leakage mainly occurs on large scales.

24 pages, 21 figures accepted for publication to MNRAS;

References in corpus (16)

Cited by in corpus (17)