most citedInvestigating the Growth of Little Red Dot Descendants at z<4 with the JWST

6 citations

5 papers

cs.LG2026

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning

Rishit Chatterjee, Tahiya Chowdhury

Volunteer-led lake monitoring yields irregular, seasonal time series with many gaps arising from ice cover, weather-related access constraints, and occasional human errors, complic…

astro-ph.GA2025★ 1 cited

HELM's deep: Highly Extincted Low-Mass galaxies seen by JWST

L. Bisigello, G. Gandolfi, A. Grazian +25

The dust content of star-forming galaxies is generally positively correlated with their stellar mass. However, some recent JWST studies have shown the existence of a population of…

astro-ph.GA2025

Extreme equivalent width-selected low-mass starbursts at : insights into their role in cosmic reionization

M. Llerena, L. Pentericci, R. Amorín +22

We investigate the properties of extreme emission line galaxies (EELGs) at and their role in reionization. Compact, low-mass galaxies with intense optical emission lines ar…

astro-ph.GA2025★ 6 cited

Investigating the Growth of Little Red Dot Descendants at z<4 with the JWST

Jean-Baptiste Billand, David Elbaz, Fabrizio Gentile +16

One of JWST's most remarkable discoveries is a population of compact red galaxies known as Little Red Dots (LRDs). Their existence raises many questions about their nature, origin,…

astro-ph.GA2025★ 2 cited

Ultra High-Redshift or Closer-by, Dust-Obscured Galaxies? Deciphering the Nature of Faint, Previously Missed F200W-Dropouts in CEERS

G. Gandolfi, G. Rodighiero, L. Bisigello +42

The James Webb Space Telescope (JWST) is revolutionizing our understanding of the Universe by unveiling faint, near-infrared dropouts previously beyond our reach, ranging from exce…