Limitations for shapelet-based weak-lensing measurements

TL;DR

This paper investigates the limitations of shapelet-based methods for weak-lensing measurements, highlighting biases caused by model constraints, galaxy shapes, and PSF effects, which challenge the accuracy needed for future surveys.

Contribution

It systematically analyzes how shapelet modeling biases affect shear estimates, emphasizing the need for accurate calibration in upcoming weak-lensing surveys.

Findings

Shapelet models bias shear estimates for steep and elliptical galaxies.

Elliptical basis functions reduce bias but still depend on accurate priors.

Bias depends on galaxy morphology, PSF size, and shape.

Abstract

We seek to understand the impact on shape estimators obtained from circular and elliptical shapelet models under two realistic conditions: (a) only a limited number of shapelet modes is available for the model, and (b) the intrinsic galactic shapes are not restricted to shapelet models. We create a set of simplistic simulations, in which the galactic shapes follow a Sersic profile. By varying the Sersic index and applied shear, we quantify the amount of bias on shear estimates which arises from insufficient modeling. Additional complications due to PSF convolution, pixelation and pixel noise are also discussed. Steep and highly elliptical galaxy shapes cannot be accurately modeled within the circular shapelet basis system and are biased towards shallower and less elongated shapes. This problem can be cured partially by allowing elliptical basis functions, but for steep profiles elliptical shapelet models still depend critically on accurate ellipticity priors. As a result, shear estimates are typically biased low. Independently of the particular form of the estimator, the bias depends on the true intrinsic galaxy morphology, but also on the size and shape of the PSF. As long as the issues discussed here are not solved, the shapelet method cannot provide weak-lensing measurements with an accuracy demanded by upcoming missions and surveys, unless one can provide an accurate and reliable calibration, specific for the dataset under investigation.