JWST data show the clumpy galaxy fraction increasing from ~10% at z~7.75 to ~70% at z~2.75 for log(M*/Msun) >=9, with mass dependence and suggested formation mechanisms differing by epoch.
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A Hubble-like sequence of galaxy morphologies exists by redshift 4, with low-mass galaxies as persistent star-forming disks and massive galaxies following either stable disk or rapid compaction-quenching paths.
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.
Hydrodynamical simulations underproduce faint compact galaxies at z>3 relative to CANDELS data, with the mismatch persisting after completeness corrections and pointing to deficiencies in star formation and feedback modeling.
citing papers explorer
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The Fraction of Clumpy Galaxies in JADES over $2<z<9$
JWST data show the clumpy galaxy fraction increasing from ~10% at z~7.75 to ~70% at z~2.75 for log(M*/Msun) >=9, with mass dependence and suggested formation mechanisms differing by epoch.
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The Hubble sequence in JWST CEERS from unbiased galaxy morphologies
A Hubble-like sequence of galaxy morphologies exists by redshift 4, with low-mass galaxies as persistent star-forming disks and massive galaxies following either stable disk or rapid compaction-quenching paths.
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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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Probing the faint-end of simulated galaxy counts at z>3
Hydrodynamical simulations underproduce faint compact galaxies at z>3 relative to CANDELS data, with the mismatch persisting after completeness corrections and pointing to deficiencies in star formation and feedback modeling.