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  1. Abstract

    We present a machine-learning framework to accurately characterize the morphologies of active galactic nucleus (AGN) host galaxies withinz< 1. We first use PSFGAN to decouple host galaxy light from the central point source, then we invoke the Galaxy Morphology Network (GaMorNet) to estimate whether the host galaxy is disk-dominated, bulge-dominated, or indeterminate. Using optical images from five bands of the HSC Wide Survey, we build models independently in three redshift bins: low (0 <z< 0.25), mid (0.25 <z< 0.5), and high (0.5 <z< 1.0). By first training on a large number of simulated galaxies, then fine-tuning using far fewer classified real galaxies, our framework predicts the actual morphology for ∼60%–70% of the host galaxies from test sets, with a classification precision of ∼80%–95%, depending on the redshift bin. Specifically, our models achieve a disk precision of 96%/82%/79% and bulge precision of 90%/90%/80% (for the three redshift bins) at thresholds corresponding to indeterminate fractions of 30%/43%/42%. The classification precision of our models has a noticeable dependency on host galaxy radius and magnitude. No strong dependency is observed on contrast ratio. Comparing classifications of real AGNs, our models agree well with traditional 2D fitting with GALFIT. The PSFGAN+GaMorNetframework does not depend on the choice of fitting functions or galaxy-related input parameters, runs orders of magnitude faster than GALFIT, and is easily generalizable via transfer learning, making it an ideal tool for studying AGN host galaxy morphology in forthcoming large imaging surveys.

     
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  2. Abstract

    We introduce a novel machine-learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology Posterior Estimation Network (GaMPEN) estimates values and uncertainties for a galaxy’s bulge-to-total-light ratio (LB/LT), effective radius (Re), and flux (F). To estimate posteriors, GaMPEN uses the Monte Carlo Dropout technique and incorporates the full covariance matrix between the output parameters in its loss function. GaMPEN also uses a spatial transformer network (STN) to automatically crop input galaxy frames to an optimal size before determining their morphology. This will allow it to be applied to new data without prior knowledge of galaxy size. Training and testing GaMPEN on galaxies simulated to matchz< 0.25 galaxies in Hyper Suprime-Cam Wideg-band images, we demonstrate that GaMPEN achieves typical errors of 0.1 inLB/LT, 0.″17 (∼7%) inRe, and 6.3 × 104nJy (∼1%) inF. GaMPEN's predicted uncertainties are well calibrated and accurate (<5% deviation)—for regions of the parameter space with high residuals, GaMPEN correctly predicts correspondingly large uncertainties. We also demonstrate that we can apply categorical labels (i.e., classifications such ashighly bulge dominated) to predictions in regions with high residuals and verify that those labels are ≳97% accurate. To the best of our knowledge, GaMPEN is the first machine-learning framework for determining joint posterior distributions of multiple morphological parameters and is also the first application of an STN to optical imaging in astronomy.

     
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  3. Abstract We determine the low-redshift X-ray luminosity function, active black hole mass function (BHMF), and Eddington ratio distribution function (ERDF) for both unobscured (Type 1) and obscured (Type 2) active galactic nuclei (AGNs), using the unprecedented spectroscopic completeness of the BAT AGN Spectroscopic Survey (BASS) data release 2. In addition to a straightforward 1/ V max approach, we also compute the intrinsic distributions, accounting for sample truncation by employing a forward-modeling approach to recover the observed BHMF and ERDF. As previous BHMFs and ERDFs have been robustly determined only for samples of bright, broad-line (Type 1) AGNs and/or quasars, ours are the first directly observationally constrained BHMF and ERDF of Type 2 AGNs. We find that after accounting for all observational biases, the intrinsic ERDF of Type 2 AGNs is significantly more skewed toward lower Eddington ratios than the intrinsic ERDF of Type 1 AGNs. This result supports the radiation-regulated unification scenario, in which radiation pressure dictates the geometry of the dusty obscuring structure around an AGN. Calculating the ERDFs in two separate mass bins, we verify that the derived shape is consistent, validating the assumption that the ERDF (shape) is mass-independent. We report the local AGN duty cycle as a function of mass and Eddington ratio, by comparing the BASS active BHMF with the local mass function for all supermassive black holes. We also present the log N − log S of the Swift/BAT 70 month sources. 
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  4. Abstract We present the active galactic nucleus (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 1449 optical spectra, of which 1182 are released for the first time, for the 858 hard-X-ray-selected AGNs in the Swift BAT 70-month sample. The majority of the spectra (801/1449, 55%) are newly obtained from Very Large Telescope (VLT)/X-shooter or Palomar/Doublespec. Many of the spectra have both higher resolution ( R > 2500, N ∼ 450) and/or very wide wavelength coverage (3200–10000 Å, N ∼ 600) that are important for a variety of AGN and host galaxy studies. We include newly revised AGN counterparts for the full sample and review important issues for population studies, with 47 AGN redshifts determined for the first time and 790 black hole mass and accretion rate estimates. This release is spectroscopically complete for all AGNs (100%, 858/858), with 99.8% having redshift measurements (857/858) and 96% completion in black hole mass estimates of unbeamed AGNs (722/752). This AGN sample represents a unique census of the brightest hard-X-ray-selected AGNs in the sky, spanning many orders of magnitude in Eddington ratio ( L / L Edd = 10 −5 –100), black hole mass ( M BH = 10 5 –10 10 M ⊙ ), and AGN bolometric luminosity ( L bol = 10 40 –10 47 erg s −1 ). 
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  5. ABSTRACT We present a multiwavelength analysis of 28 of the most luminous low-redshift narrow-line, ultra-hard X-ray-selected active galactic nuclei (AGN) drawn from the 70-month Swift/BAT all-sky survey, with bolometric luminosities of $\log (L_{\rm bol} /{\rm erg\, s}^{-1}) \gtrsim 45.25$. The broad goal of our study is to determine whether these objects have any distinctive properties, potentially setting them aside from lower luminosity obscured AGN in the local Universe. Our analysis relies on the first data release of the BAT AGN Spectroscopic Survey (BASS/DR1) and on dedicated observations with the VLT, Palomar, and Keck observatories. We find that the vast majority of our sources agree with commonly used AGN selection criteria which are based on emission line ratios and on mid-infrared colours. Our AGN are pre-dominantly hosted in massive galaxies (9.8 ≲ log (M*/M⊙) ≲ 11.7); based on visual inspection of archival optical images, they appear to be mostly ellipticals. Otherwise, they do not have distinctive properties. Their radio luminosities, determined from publicly available survey data, show a large spread of almost four orders of magnitude – much broader than what is found for lower X-ray luminosity obscured AGN in BASS. Moreover, our sample shows no preferred combination of black hole masses (MBH) and/or Eddington ratio (λEdd), covering 7.5 ≲ log (MBH/M⊙) ≲ 10.3 and 0.01 ≲ λEdd ≲ 1. Based on the distribution of our sources in the λEdd−NH plane, we conclude that our sample is consistent with a scenario where the amount of obscuring material along the line of sight is determined by radiation pressure exerted by the AGN on the dusty circumnuclear gas. 
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