The little coadd that could: Estimating shear from coadded images

TL;DR

This paper demonstrates that coadded images can be effectively used for weak lensing shear measurements, achieving sub-0.1% bias, thus offering a computationally efficient alternative to simultaneous multi-epoch fitting in large surveys.

Contribution

It shows that coadds can match the accuracy of simultaneous fitting for shear estimation, with a new cell-based coaddition scheme suitable for LSST.

Findings

Coadds can constrain shear bias below 0.1%.

No significant difference between coadd and simultaneous fitting methods.

Rejecting about 20% of epochs has minimal impact on survey depth.

Abstract

Upcoming wide field surveys will have many overlapping epochs of the same region of sky. The conventional wisdom is that in order to reduce the errors sufficiently for systematics-limited measurements, like weak lensing, we must do simultaneous fitting of all the epochs. Using current algorithms this will require a significant amount of computing time and effort. In this paper, we revisit the potential of using coadds for shear measurements. We show on a set of image simulations that the multiplicative shear bias can be constrained below the 0.1% level on coadds, which is sufficient for future lensing surveys. We see no significant differences between simultaneous fitting and coadded approaches for two independent shear codes: Metacalibration and BFD. One caveat of our approach is the assumption of a principled coadd, i.e. the PSF is mathematically well-defined for all the input images. This requires us to reject CCD images that do not fully cover the coadd region. We estimate that the number of epochs that must be rejected for a survey like LSST is on the order of 20%, resulting in a small loss in depth of less than 0.1 magnitudes. We also put forward a cell-based coaddition scheme that meets the above requirements for unbiased weak lensing shear estimation in the context of LSST.