Weak gravitational lensing shear measurement with FPFS: analytical mitigation of noise bias and selection bias

TL;DR

This paper introduces an improved Fourier Power Function Shapelets (FPFS) method for weak gravitational lensing shear measurement, providing analytic bias corrections that meet Stage IV experiment requirements without external calibration.

Contribution

The paper presents an enhanced FPFS shear measurement technique with analytic bias corrections, eliminating the need for external image simulations and improving accuracy for faint and isolated galaxies.

Findings

Achieves small residual multiplicative bias (~10^-3) and additive bias (~10^-4)

Works accurately for faint galaxies and is robust against stellar contamination

Code processes over 1000 galaxy images per CPU second

Abstract

Dedicated 'Stage IV' observatories will soon observe the entire extragalactic sky, to measure the 'cosmic shear' distortion of galaxy shapes by weak gravitational lensing. To measure the apparent shapes of those galaxies, we present an improved version of the Fourier Power Function Shapelets (FPFS) shear measurement method. This now includes analytic corrections for sources of bias that plague all shape measurement algorithms: including noise bias (due to noise in nonlinear combinations of observable quantities) and selection bias (due to sheared galaxies being more or less likely to be detected). Crucially, these analytic solutions do not rely on calibration from external image simulations. For isolated galaxies, the small residual $\sim$$10^{-3}$ multiplicative bias and $\lesssim$$10^{-4}$ additive bias now meet science requirements for Stage IV experiments. FPFS also works accurately for faint galaxies and robustly against stellar contamination. Future work will focus on deblending overlapping galaxies. The code used for this paper can process $>$$1000$ galaxy images per CPU second and is available from https://github.com/mr-superonion/FPFS.