A new deep-to-wide transfer function reduces mean redshift biases in Euclid tomographic bins by matching reference sample color distributions to the wide survey.
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A multimodal neural network trained on MPA-JHU references produces SFR, stellar mass, and metallicity estimates for 547 million low-redshift galaxies in DESI LS DR10.
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Euclid: Improving redshift distribution reconstruction using a deep-to-wide transfer function
A new deep-to-wide transfer function reduces mean redshift biases in Euclid tomographic bins by matching reference sample color distributions to the wide survey.
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A Value-added Physical Properties Catalog for Low-redshift Galaxies from DESI Legacy Imaging Surveys DR10
A multimodal neural network trained on MPA-JHU references produces SFR, stellar mass, and metallicity estimates for 547 million low-redshift galaxies in DESI LS DR10.