Post-starburst galaxies show compact morphologies with minimal wavelength-dependent structural change and low overall disturbance levels, except for enhanced residual asymmetry in massive systems at z > 1, supporting two distinct quenching pathways.
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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.
BAGPIPES fitting of 9289 massive quiescent galaxies shows most SFHs rise gradually then quench in 1-2 Gyr, with faster quenching at z>1 and slower at z<1, interpreted as multiple AGN feedback and gas-supply mechanisms.
citing papers explorer
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The multiwavelength structure of post-starburst galaxies at 0.5 < z < 3 with JWST PRIMER: compact morphologies and residual disturbances
Post-starburst galaxies show compact morphologies with minimal wavelength-dependent structural change and low overall disturbance levels, except for enhanced residual asymmetry in massive systems at z > 1, supporting two distinct quenching pathways.
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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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Inferring the star-formation histories of massive quiescent galaxies with BAGPIPES: Evidence for multiple quenching mechanisms
BAGPIPES fitting of 9289 massive quiescent galaxies shows most SFHs rise gradually then quench in 1-2 Gyr, with faster quenching at z>1 and slower at z<1, interpreted as multiple AGN feedback and gas-supply mechanisms.