Enhancing Lyα Emitter Identification in HETDEX with a Convolutional Neural Network
We present a deep learning framework to enhance the identification of Ly α emitters (LAEs) in the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX), an untargeted spectroscopic survey of LAEs at 1.9 < z < 3.5 without imaging preselection. We primarily address the low signal-to-noise ratio (S/...
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| Autors principals: | , , , , , , , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
IOP Publishing
2026-01-01
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| Col·lecció: | The Astronomical Journal |
| Matèries: | |
| Accés en línia: | https://doi.org/10.3847/1538-3881/ae5baf |
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