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Improving Photometric Redshift Estimates with Training Sample Augmentation

Large imaging surveys will rely on photometric redshifts (photo- z 's), which are typically estimated through machine-learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for Legacy Survey of Space and Time (LSST), so we seek m...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Irene Moskowitz, Eric Gawiser, John Franklin Crenshaw, Brett H. Andrews, Alex I. Malz, Samuel Schmidt, The LSST Dark Energy Science Collaboration
Format: Artigo
Sprache:Inglês
Veröffentlicht: IOP Publishing 2024-01-01
Schriftenreihe:The Astrophysical Journal Letters
Schlagworte:
Observational cosmology
Online-Zugang:https://doi.org/10.3847/2041-8213/ad4039
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