PITA, a new semi-supervised deep learning algorithm, outperforms prior photo-z methods by using a triple-task loss on images, colors, and available redshifts to produce a smooth latent space.
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Multi-phase molecular gas in IRAS20551-4250 is dominated by cold CO, shows UV-heated warm H2, tidal features from a merger, and no molecular outflows, consistent with ongoing star formation.
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Optimizing Deep Learning Photometric Redshifts for the Roman Space Telescope with HST/CANDELS
PITA, a new semi-supervised deep learning algorithm, outperforms prior photo-z methods by using a triple-task loss on images, colors, and available redshifts to produce a smooth latent space.
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GOALS-JWST: Resolved multi-phase molecular gas in IRAS 20551-4250 using JWST and ALMA
Multi-phase molecular gas in IRAS20551-4250 is dominated by cold CO, shows UV-heated warm H2, tidal features from a merger, and no molecular outflows, consistent with ongoing star formation.