Toward an Optimal Reconstruction of the Shear Field with PDF-folding

Abstract

Weak lensing provides a direct way of mapping the density distribution in the Universe. To reconstruct the density field from the shear catalog, an important step is to build the shear field from the shear catalog, which can be quite nontrivial due to the inhomogeneity of the background galaxy distribution and the shape noise. We propose the PDF-folding method as a statistically optimal way of reconstructing the shear field. It is an extention of the PDF-SYM method, which was previously designed for optimizing the stacked shear signal as well as the shear-shear correlation for the Fourier_Quad shear estimators. PDF-folding does not require smoothing kernels as in traditional methods, therefore it suffers less information loss on small scales and avoids possible biases due to the spatial variation in the shear on the scale of the kernel. We show with analytic reasoning as well as numerical examples that the new method can reach the optimal signal-to-noise ratio on the reconstructed shear map under general observing conditions, i.e., with inhomogeneous background densities or masks. We also show the performance of the new method on real data around foreground galaxy clusters.