activity
20242026
most citedDenser Environments Cultivate Larger Galaxies: A Comprehensive Study beyond the Local Universe with 3 Million Hyper Suprime-Cam Galaxies

12 citations · 12 across the 7 of their papers we have counts for

collaborators

8 papers

astro-ph.GA2026

Rubin J122659.4+090236: An Extremely Low Surface Brightness Galaxy Candidate Discovered in the Rubin LSST Early Data Preview 2

Dipanjan Mitra, Kanak Saha, Sugata Kaviraj +28

We report the serendipitous discovery of an exceptionally low surface brightness galaxy (LSBG) candidate, Rubin J122659.4+090236, in Rubin Observatory imaging of the interacting NG…

astro-ph.GA2026

AGN-DB: A Unified Multi-Wavelength Database of Active Galactic Nuclei

Alessandro Peca, Nico Cappelluti, C. Megan Urry +29

We present the Active Galactic Nuclei Database (AGN-DB), a comprehensive, multi-wavelength catalog compiled from more than 100 publicly available AGN catalogs and samples released…

astro-ph.GA2026

LEGGOS III: Mapping Star Formation and Dust in Gravitationally Lensed Galaxies with , a UMAP and Clustering Framework

Alex Ross, Gourav Khullar, Taylor Hutchison +10

Strong gravitational lensing combined with JWST's spatio-spectral resolution enables resolved studies of star-forming regions in 2-4 galaxies, but identifying and character…

astro-ph.IM2026

Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid

Aritra Ghosh, Drew Oldag, Michael Tauraso +29

The NSF-DOE Vera C. Rubin Observatory, Roman Space Telescope, Euclid, and other next-generation surveys will deliver imaging, spectroscopic, and time-domain data at scales that inc…

astro-ph.GA2026

Obscured AGN at z < 1.5: X-ray to Far-Infrared SEDs and Host Galaxy Morphologies in the GOODS Fields

William W. H. Jarvis, Connor Auge, David Sanders +9

We present an analysis of spectral energy distributions (SEDs), galaxy light profiles, and visual morphological classifications for 194 X-ray luminous AGN (intrinsic absorption-cor…

astro-ph.GA2025

Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within in the Hyper Supreme-Cam Wide Survey

Chuan Tian, C. Megan Urry, Aritra Ghosh +8

We present a composite machine learning framework to estimate posterior probability distributions of bulge-to-total light ratio, half-light radius, and flux for Active Galactic Nuc…