SEMPER predicts SKA-Mid Band 2 observations in under 20 hours will recover at least 20% of the total SFRD from radio-emitting SFGs up to z≈6, including NIR-dark galaxies.
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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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Semi-empirical Predictions for Ultra-deep Radio Counts of Star-forming Galaxies with the SKAO
SEMPER predicts SKA-Mid Band 2 observations in under 20 hours will recover at least 20% of the total SFRD from radio-emitting SFGs up to z≈6, including NIR-dark galaxies.
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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.