Deep-field Metacalibration

We introduce deep-field metacalibration, a new technique that reduces the pixel noise in metacalibration estimators of weak lensing shear signals by using deeper imaging survey for calibration. In standard when estimating object's response, extra is added to correct effect shearing image, increasing uncertainty on estimates ~ 20%. Our leverages separate, calculate calibrations with less degradation image noise. demonstrate measurement unbiased up second-order effects. provide algorithms apply this surveys and describe how generalize it rely explicitly object detection (e.g., metacalibration). For Vera C. Rubin Observatory Legacy Survey Space Time (LSST), improvement precision will depend somewhat unknown details LSST Deep Drilling Field (DDF) observations terms area depth, relative point-spread function properties DDF main surveys, contribution vs. intrinsic shape total survey. conservatively estimate reduced from 20% 5% or which we attribute primarily increased source density contributions overall Finally, show robust sample variance DDFs due their large area, equivalent calibration error being 0.1%. The provides higher signal-to-noise measurements while still meeting stringent systematic requirements future surveys.