62 citations · 153 across the 16 of their papers we have counts for
5 papers · 1 filter
Using Machine Learning to Determine Morphologies of AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey
Chuan Tian, C. Megan Urry, Aritra Ghosh +9
We present a machine-learning framework to accurately characterize morphologies of Active Galactic Nucleus (AGN) host galaxies within . We first use PSFGAN to decouple host ga…
On the cosmic evolution of AGN obscuration and the X-ray luminosity function: XMM-Newton and Chandra spectral analysis of the 31.3 deg Stripe 82X
Alessandro Peca, Nico Cappelluti, Meg Urry +11
We present X-ray spectral analysis of XMM and Chandra observations in the 31.3 deg Stripe-82X (S82X) field. Of the 6181 X-ray sources in this field, we analyze a sample of 2937…
Probing the Structure and Evolution of BASS AGN through Eddington Ratios
Tonima Tasnim Ananna, C. Megan Urry, Claudio Ricci +23
We constrain the intrinsic Eddington ratio (\lamEdd ) distribution function for local AGN in bins of low and high obscuration (log NH <= 22 and 22 < log NH < 25), using the Swift-B…
GaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters
Aritra Ghosh, C. Megan Urry, Amrit Rau +11
We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology…
Accretion History of AGN: Estimating the Host Galaxy Properties in X-ray Luminous AGN from z=0-3
Brandon Coleman, Allison Kirkpatrick, Kevin C. Cooke +10
We aim to determine the intrinsic far-Infrared (far-IR) emission of X-ray-luminous quasars over cosmic time. Using a 16 deg^2 region of the Stripe 82 field surveyed by XMM-Newton a…