A neural marking scheme trained with contrastive learning tightens constraints on σ8 by 2.9× and Ωm by 1.8× over classical marks at k_max=0.2 h/Mpc while breaking their degeneracy at the Fisher level.
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astro-ph.CO 2years
2026 2verdicts
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Overview of HI modeling methods finds consistency in cosmic HI density but systematic differences in HI-halo mass relation shape and redshift evolution.
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Interpretable Neural Marked Statistics for Cosmological Inference
A neural marking scheme trained with contrastive learning tightens constraints on σ8 by 2.9× and Ωm by 1.8× over classical marks at k_max=0.2 h/Mpc while breaking their degeneracy at the Fisher level.
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HI Simulations for Cosmology with the SKA Observatory
Overview of HI modeling methods finds consistency in cosmic HI density but systematic differences in HI-halo mass relation shape and redshift evolution.