DES Y3 3x2pt analysis constrains S8=0.776±0.017 and Ωm=0.339±0.032 in flat ΛCDM, consistent with Planck CMB results at p=0.13-0.48.
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Redshift-bin-optimized color cuts using unWISE photometry reduce stellar contamination in the DES Y3 MagLim lens sample by 1.3-5.5% varying across bins and footprint.
N-body light-cone mocks show 2-4 sigma deviations in third-order angular clustering between LCDM and f(R)/nDGP models at z=0.15-0.3 for halos and galaxies, with stronger signals in the dark-matter field.
AI techniques for photometric redshift estimation have converged and are now limited by the size, systematics, and selection effects in spectroscopic training samples rather than by methodology.
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Dark Energy Survey Year 3 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
DES Y3 3x2pt analysis constrains S8=0.776±0.017 and Ωm=0.339±0.032 in flat ΛCDM, consistent with Planck CMB results at p=0.13-0.48.
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Taming Additive Systematics via Redshift-Bin-Optimized Star-Galaxy Separation
Redshift-bin-optimized color cuts using unWISE photometry reduce stellar contamination in the DES Y3 MagLim lens sample by 1.3-5.5% varying across bins and footprint.
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Galaxy and halo angular clustering in LCDM and Modified Gravity cosmologies
N-body light-cone mocks show 2-4 sigma deviations in third-order angular clustering between LCDM and f(R)/nDGP models at z=0.15-0.3 for halos and galaxies, with stronger signals in the dark-matter field.
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Machine Learning Techniques for Astrophysics and Cosmology: Photometric Redshifts
AI techniques for photometric redshift estimation have converged and are now limited by the size, systematics, and selection effects in spectroscopic training samples rather than by methodology.