Spectroscopic study of 11 LRDs at z~4 finds AGN origin for optical emission via broad Hα correlations and introduces a clumpy envelope model with growth timescales of 10^5-10^7 years.
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Little Red Dots show soft ionizing spectra consistent with massive stars, based on high H-alpha EWs and low HeII/H-beta ratios that rule out hard AGN spectra via Cloudy modeling.
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.
Halo-driven transient rapid growth followed by thermodynamic suppression explains over-massive black holes and Little Red Dots as precursors to standard SMBH-galaxy coevolution.
citing papers explorer
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The Structure and Evolution of LRDs: Insights from JWST NIRSpec Medium and High Resolution Spectroscopy at $z\sim4$
Spectroscopic study of 11 LRDs at z~4 finds AGN origin for optical emission via broad Hα correlations and introduces a clumpy envelope model with growth timescales of 10^5-10^7 years.
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The Missing Hard Photons of Little Red Dots: Their Incident Ionizing Spectra Resemble Massive Stars
Little Red Dots show soft ionizing spectra consistent with massive stars, based on high H-alpha EWs and low HeII/H-beta ratios that rule out hard AGN spectra via Cloudy modeling.
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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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Halo-driven Origin and Suppression of Over-massive Black Holes and Little Red Dots
Halo-driven transient rapid growth followed by thermodynamic suppression explains over-massive black holes and Little Red Dots as precursors to standard SMBH-galaxy coevolution.