681 citations · 2.1k across the 47 of their papers we have counts for
10 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…
BASS XXXVII: The role of radiative feedback in the growth and obscuration properties of nearby supermassive black holes
C. Ricci, T. T. Ananna, M. J. Temple +22
We study the relation between obscuration and supermassive black hole (SMBH) growth using a large sample of hard X-ray selected Active Galactic Nuclei (AGN). We find a strong decre…
BASS XXII: The BASS DR2 AGN Catalog and Data
Michael J. Koss, Claudio Ricci, Benny Trakhtenbrot +32
We present the AGN catalog and optical spectroscopy for the second data release of the Swift BAT AGN Spectroscopic Survey (BASS DR2). With this DR2 release we provide 1425 optical…
BAT AGN Spectroscopic Survey XXI: The Data Release 2 Overview
Michael J. Koss, Benny Trakhtenbrot, Claudio Ricci +24
The BAT AGN Spectroscopic Survey (BASS) is designed to provide a highly complete census of the key physical parameters of supermassive black holes (SMBHs) that power local active g…
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…
BASS XXV: DR2 Broad-line Based Black Hole Mass Estimates and Biases from Obscuration
Julian E. Mejıa-Restrepo, Benny Trakhtenbrot, Michael J. Koss +26
We present measurements of broad emission lines and virial estimates of supermassive black hole masses () for a large sample of ultra-hard X-ray selected active galactic nu…
BASS XXX: Distribution Functions of DR2 Eddington-ratios, Black Hole Masses, and X-ray Luminosities
Tonima Tasnim Ananna, Anna K. Weigel, Benny Trakhtenbrot +19
We determine the low-redshift X-ray luminosity function (XLF), active black hole mass function (BHMF), and Eddington-ratio distribution function (ERDF) for both unobscured (Type 1)…