On Combining Lensing Shear Information from Multiple Filters

TL;DR

This paper investigates how combining galaxy shape measurements across multiple filters can improve weak lensing shear estimates, finding high shape correlation and potential gains in effective galaxy number density.

Contribution

It introduces a method to assess the benefit of multi-filter shape measurements for lensing shear, using covariance analysis on real data.

Findings

Galaxy shapes are highly correlated across filters.

Combining shapes can increase effective galaxy number density.

Potential for improved shear measurement accuracy.

Abstract

We consider the possible gain in the measurement of lensing shear from imaging data in multiple filters. Galaxy shapes may differ significantly across filters, so that the same galaxy offers multiple samples of the shear. On the other extreme, if galaxy shapes are identical in different filters, one can combine them to improve the signal-to-noise and thus increase the effective number density of faint, high redshift galaxies. We use the GOODS dataset to test these scenarios by calculating the covariance matrix of galaxy ellipticities in four visual filters (B,V,i,z). We find that galaxy shapes are highly correlated, and estimate the gain in galaxy number density by combining their shapes.