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.
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Pith papers citing it
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astro-ph.CO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
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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Slay the Shear: A Unified Statistical Framework for Weak Gravitational Lensing Shear Estimation
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.
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Accurate Galaxy Cluster Shear and Mass Calibration for LSST with AnaCal
AnaCal recovers input shear with low bias in high-shear cluster regimes under LSST-like conditions, producing 0.24% mean mass bias.