KiLeR combines shear ratios with kinematic intrinsic shapes to mitigate first-order lensing systematics and forecasts a 192% improvement in dark energy constraints from the Roman telescope.
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Unified framework proves the score function yields the minimum-variance unbiased shear estimator and that response-weighted inverse-variance weights minimize shape noise independent of galaxy shape distributions, with RDSM reducing noise by ~17.5% at LSST depth.
Edge discontinuities in coadds cause significant shear biases only in extreme cases such as two-input-image stacks or 25% PSF size jumps, and these cases can be flagged and removed with a simple PSF variation statistic.
AnaCal recovers input shear with low bias in high-shear cluster regimes under LSST-like conditions, producing 0.24% mean mass bias.
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Edges In Coadded Images
Edge discontinuities in coadds cause significant shear biases only in extreme cases such as two-input-image stacks or 25% PSF size jumps, and these cases can be flagged and removed with a simple PSF variation statistic.