Deep-field Metacalibration

Abstract

We introduce deep-field metacalibration, a new technique that reduces the pixel noise in metacalibration estimators of weak lensing shear signals by using a deeper imaging survey for calibration. In standard metacalibration, a small artificial shear is applied to the observed images of galaxies in order to estimate the response the object’s shape measurement to shear, which is used to calibrate statistical shear estimates. As part of a correction for the effect of shearing correlated noise in the image, extra noise is added that increases the uncertainty on statistical shear estimates by ∼ 20%. Our new deep-field metacalibration technique leverages a separate, deeper imaging survey to calculate calibrations with less degradation in image noise. We demonstrate that weak lensing shear measurement with deep-field metacalibration is unbiased up to second-order shear effects for isolated sources. For the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the improvement in weak lensing precision will depend on the somewhat unknown details of the LSST Deep Drilling Field (DDF) observations in terms of area and depth, the relative point spread function properties of the DDF and main LSST surveys, and the relative contribution of pixel noise versus intrinsic shape noise to the total shape noise in the survey. We conservatively estimate that the degradation in precision is reduced from 20% for metacalibration to ≲ 5% for deep-field metacalibration, which we attribute primarily to the increased source density and reduced pixel noise contributions to the overall shape noise. Finally, we show that the technique is robust to sample variance in the LSST DDFs due to their large area, with the equivalent calibration error being ≲ 0.1%. The deep-field metacalibration technique provides higher signal-to-noise weak lensing measurements while still meeting the stringent systematic error requirements of future surveys for isolated sources.