On the effect of projections on convergence peak counts and Minkowski functionals

TL;DR

This paper investigates how different planar projections of celestial sphere data affect non-Gaussian statistics like peak counts and Minkowski Functionals, revealing systematic biases introduced by projections.

Contribution

It provides a comprehensive evaluation of the impact of various planar projections on weak lensing convergence map statistics, highlighting biases and their dependence on projection type.

Findings

Peak counts overestimate at low SNR and underestimate at high SNR in projections.

V0 Minkowski Functional is minimally affected by projection.

V1 and V2 Minkowski Functionals are overestimated in projections.

Abstract

The act of projecting data sampled on the surface of the celestial sphere onto a regular grid on the plane can introduce error and a loss of information. This paper evaluates the effects of different planar projections on non-Gaussian statistics of weak lensing convergence maps. In particular we investigate the effect of projection on peak counts and Minkowski Functionals (MFs) derived from convergence maps and the suitability of a number of projections at matching the peak counts and MFs obtained from a sphere. We find that the peak counts derived from planar projections consistently overestimate the counts at low SNR thresholds and underestimate at high SNR thresholds across the projections evaluated, although the difference is reduced when smoothing of the maps is increased. In the case of the Minkowski Functionals, V0 is minimally affected by projection used, while projected V1 and V2 are consistently overestimated with respect to the spherical case.