Implications of a wavelength dependent PSF for weak lensing measurements

TL;DR

This paper investigates how wavelength-dependent PSF affects weak lensing measurements, proposing methods to accurately estimate the effective PSF using broad-band data, and demonstrating that current survey data can meet Euclid's accuracy requirements.

Contribution

It evaluates the biases introduced by wavelength-dependent PSF in weak lensing and demonstrates machine learning approaches can achieve the necessary accuracy for Euclid.

Findings

Standard SED fitting methods introduce redshift-dependent biases.

Machine learning can achieve the required PSF accuracy.

Photometric redshift and PSF estimation correlations can be effectively modeled.

Abstract

The convolution of galaxy images by the point-spread function (PSF) is the dominant source of bias for weak gravitational lensing studies, and an accurate estimate of the PSF is required to obtain unbiased shape measurements. The PSF estimate for a galaxy depends on its spectral energy distribution (SED), because the instrumental PSF is generally a function of the wavelength. In this paper we explore various approaches to determine the resulting `effective' PSF using broad-band data. Considering the Euclid mission as a reference, we find that standard SED template fitting methods result in biases that depend on source redshift, although this may be remedied if the algorithms can be optimised for this purpose. Using a machine-learning algorithm we show that, at least in principle, the required accuracy can be achieved with the current survey parameters. It is also possible to account for the correlations between photometric redshift and PSF estimates that arise from the use of the same photometry. We explore the impact of errors in photometric calibration, errors in the assumed wavelength dependence of the PSF model and limitations of the adopted template libraries. Our results indicate that the required accuracy for Euclid can be achieved using the data that are planned to determine photometric redshifts.