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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2026 2verdicts
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Horizon-AGN shows galaxy and black hole merger rates both rise with stellar mass and fall with redshift, peaking near z=2-3, establishing a direct evolutionary link from galaxy interactions to black hole coalescences.
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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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One Merge to Rule Them All: From Galaxy Interactions to Black Hole Mergers Using Horizon-AGN
Horizon-AGN shows galaxy and black hole merger rates both rise with stellar mass and fall with redshift, peaking near z=2-3, establishing a direct evolutionary link from galaxy interactions to black hole coalescences.