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

    Published 2025-04-01
    “…We also examine the impact of the data quality and the size of the training set and model. We find that the biggest factor in DeepDISC photo-z quality is the signal-to-noise of the imaging data, and see a reduction in photo-z scatter approximately proportional to the image data signal-to-noise. …”
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