Property-dependent systematic weights derived separately on ELG subsamples, with separate DES footprint treatment, mitigate spurious clustering in ~10% of subsamples but are not optimal for the full sample.
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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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DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering
Property-dependent systematic weights derived separately on ELG subsamples, with separate DES footprint treatment, mitigate spurious clustering in ~10% of subsamples but are not optimal for the full sample.
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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.