Extracting cosmological insights from noisy, distorted galaxy images presents significant challenges, with biased measurements posing a major concern. To overcome this, shear measurement methods must be carefully designed to mitigate systematic errors while maintaining statistical rigor. Metadetection, BFD, and AnaCal exemplify innovative approaches that address these challenges, paving the way for accurate analysis of billions of galaxy shapes with the next generation of large-scale surveys.
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