First spectroscopic variability in a z~7 LRD shows rapid changes in both narrow and broad line regions, implying direct ionization from the central source to surrounding nebular gas.
J., Kokorev, V., Kocevski, D
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Tilted supercritical accretion disks around black holes can accrete mass at rates up to ten times the Eddington limit due to standing shocks, unlike untilted disks that respect the limit.
SPHEREx data confirm 77 new luminous heavily reddened quasars at 1.5<z<3.9 that are hot-dust poor relative to unobscured quasars, supporting a blow-out feedback phase.
Abundant early heavy seeds plus frequent mergers produce the massive black holes seen by JWST at z>9 and yield about four LISA events per year at z>=8.
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.
citing papers explorer
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The GlimmIr: Spectroscopic Variability in a z~7 LRD Indicates Rapid Changes in Both the Narrow and Broad Line Regions
First spectroscopic variability in a z~7 LRD shows rapid changes in both narrow and broad line regions, implying direct ionization from the central source to surrounding nebular gas.
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The nature of tilted supercritical accretion discs
Tilted supercritical accretion disks around black holes can accrete mass at rates up to ten times the Eddington limit due to standing shocks, unlike untilted disks that respect the limit.
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Hidden Monsters with SPHEREx I: A goldmine for heavily reddened quasars at cosmic noon
SPHEREx data confirm 77 new luminous heavily reddened quasars at 1.5<z<3.9 that are hot-dust poor relative to unobscured quasars, supporting a blow-out feedback phase.
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First results of AMBRA: Abundant Seeds and Early Mergers as a Pathway to the First Massive Black Holes
Abundant early heavy seeds plus frequent mergers produce the massive black holes seen by JWST at z>9 and yield about four LISA events per year at z>=8.
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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.