Weak lensing tomography with orthogonal polynomials

TL;DR

This paper introduces orthogonal polynomials called TaRDiS for weak lensing tomography, demonstrating their effectiveness in constraining cosmological parameters and simplifying the interpretation of tomographic data.

Contribution

It develops and analyzes TaRDiS, a novel set of orthogonal polynomials for weak lensing tomography, improving parameter estimation and understanding of the method.

Findings

TaRDiS performs comparably to traditional methods.

Each polynomial extracts independent information.

Combining polynomials reduces parameter degeneracies.

Abstract

The topic of this article is weak cosmic shear tomography where the line of sight-weighting is carried out with a set of specifically constructed orthogonal polynomials, dubbed TaRDiS (Tomography with orthogonAl Radial Distance polynomIal Systems). We investigate the properties of these polynomials and employ weak convergence spectra, which have been obtained by weighting with these polynomials, for the estimation of cosmological parameters. We quantify their power in constraining parameters in a Fisher-matrix technique and demonstrate how each polynomial projects out statistically independent information, and how the combination of multiple polynomials lifts degeneracies. The assumption of a reference cosmology is needed for the construction of the polynomials, and as a last point we investigate how errors in the construction with a wrong cosmological model propagate to misestimates in cosmological parameters. TaRDiS performs on a similar level as traditional tomographic methods and some key features of tomography are made easier to understand.