AKRA 3.0 uses conjugate gradient to solve the normal equations for weak lensing mass mapping, producing the highest-resolution DES Y3 convergence map to date and demonstrating unbiased power spectra extracted directly from the map.
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Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.
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AKRA 3.0: A matrix-free Inversion Framework for Weak Lensing Mass Mapping and Its Application to DES Y3 Data
AKRA 3.0 uses conjugate gradient to solve the normal equations for weak lensing mass mapping, producing the highest-resolution DES Y3 convergence map to date and demonstrating unbiased power spectra extracted directly from the map.
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Machine-learning applications for weak-lensing cosmology
Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.