DeepDISC-photoz: Deep Learning-Based Photometric Redshift Estimation for Rubin LSST

DeepDISC-photoz: Deep Learning-Based Photometric Redshift Estimation for Rubin LSST

Photometric redshifts will be a key data product for the Rubin Observatory Legacy Survey of Space and Time (LSST) as well as for future ground and space-based surveys. The need for photometric redshifts, or photo-zs, arises from sparse spectroscopic coverage of observed galaxies. LSST is expected to...

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Bibliographic Details
Main Authors: Grant Merz, Xin Liu, Samuel Schmidt, Alex I. Malz, Tianqing Zhang, Doug Branton, Colin J. Burke, Melissa Delucchi, Yaswant Sai Ejjagiri, Jeremy Kubica, Yichen Liu, Olivia Lynn, Drew Oldag, The LSST Dark Energy Science Collaboration
Format: Article
Language:English
Published: Maynooth Academic Publishing 2025-04-01
Series:The Open Journal of Astrophysics
Online Access:https://doi.org/10.33232/001c.136809
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https://doi.org/10.33232/001c.136809

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