A method called the degeneracy distillery uses symbolic transformations to flatten the Fisher information matrix globally from simulations alone, identifying independent parameter combinations and reducing neural posterior estimation simulation budgets by up to 10x.
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DES Y3 weak lensing analysis with hybrid map-level statistics and simulation-based inference yields S8 = 0.808 ± 0.017, Ωm = 0.325 ± 0.024, and w < -0.766, improving the figure of merit by 60% over prior state-of-the-art.
Machine learning techniques can mitigate limitations in traditional weak-lensing analyses and enhance extraction of cosmological information from galaxy imaging surveys.
citing papers explorer
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The Degeneracy Distillery
A method called the degeneracy distillery uses symbolic transformations to flatten the Fisher information matrix globally from simulations alone, identifying independent parameter combinations and reducing neural posterior estimation simulation budgets by up to 10x.
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Dark Energy Survey Year 3 results: optimized $w$CDM simulation-based inference with weak lensing map-level hybrid statistics
DES Y3 weak lensing analysis with hybrid map-level statistics and simulation-based inference yields S8 = 0.808 ± 0.017, Ωm = 0.325 ± 0.024, and w < -0.766, improving the figure of merit by 60% over prior state-of-the-art.
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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.