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  1. 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 ourmore »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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  2. Abstract The 2 mm Mapping Obscuration to Reionization with ALMA (MORA) Survey was designed to detect high-redshift ( z ≳ 4), massive, dusty star-forming galaxies (DSFGs). Here we present two likely high-redshift sources, identified in the survey, whose physical characteristics are consistent with a class of optical/near-infrared (OIR)-invisible DSFGs found elsewhere in the literature. We first perform a rigorous analysis of all available photometric data to fit spectral energy distributions and estimate redshifts before deriving physical properties based on our findings. Our results suggest the two galaxies, called MORA-5 and MORA-9, represent two extremes of the “OIR-dark” class of DSFGs. MORA-5 ( z phot = 4.3 − 1.3 + 1.5 ) is a significantly more active starburst with a star formation rate (SFR) of 830 − 190 + 340 M ⊙ yr −1 compared to MORA-9 ( z phot = 4.3 − 1.0 + 1.3 ), whose SFR is a modest 200 − 60 + 250 M ⊙ yr −1 . Based on the stellar masses ( M ⋆ ≈ 10 10−11 M ⊙ ), space density ( n ∼ (5 ± 2) × 10 −6 Mpc −3 , which incorporates two other spectroscopically confirmed OIR-dark DSFGs in the MORAmore »sample at z = 4.6 and z = 5.9), and gas depletion timescales (<1 Gyr) of these sources, we find evidence supporting the theory that OIR-dark DSFGs are the progenitors of recently discovered 3 < z < 4 massive quiescent galaxies.« less
  3. ABSTRACT We present optical and near-infrared imaging covering a ∼1.53 deg2 region in the Super-Cluster Assisted Shear Survey (SuperCLASS) field, which aims to make the first robust weak lensing measurement at radio wavelengths. We derive photometric redshifts for ≈176 000 sources down to $i^\prime _{\rm AB}\sim 24$ and present photometric redshifts for 1.4 GHz expanded Multi-Element Radio Linked Interferometer Network (e-MERLIN) and Karl G. Jansky Very Large Array (VLA) detected radio sources found in the central 0.26 deg2. We compile an initial catalogue of 149 radio sources brighter than S1.4 > 75 μJy and find their photometric redshifts span 0 < zphot < 4 with radio luminosities between 1021 and 1025 W Hz−1, with medians of $\langle z \rangle \, =0.55$ and $\langle L_{1.4}\rangle \, =1.9\times 10^{23}$ W Hz−1, respectively. We find 95 per cent of the μJy radio source sample (141/149) have spectral energy distributions (SEDs) best fit by star-forming templates while 5 per cent (8/149) are better fit by active galactic nuclei (AGN). Spectral indices are calculated for sources with radio observations from the VLA and Giant Metrewave Radio Telescope (GMRT) at 325 MHz, with an average spectral slope of α = 0.59 ± 0.04. Using the full photometric redshift catalogue, we construct a density map at the redshift of the known galaxy clusters,more »z = 0.20 ± 0.08. Four of the five clusters are prominently detected at $\gt 7\, \sigma$ in the density map and we confirm the photometric redshifts are consistent with previously measured spectra from a few galaxies at the cluster centres.« less
  4. ABSTRACT The SuperCLuster Assisted Shear Survey (SuperCLASS) is a legacy programme using the e-MERLIN interferometric array. The aim is to observe the sky at L-band (1.4 GHz) to a r.m.s. of $7\, \mu {\rm Jy}\,$beam−1 over an area of $\sim 1\, {\rm deg}^2$ centred on the Abell 981 supercluster. The main scientific objectives of the project are: (i) to detect the effects of weak lensing in the radio in preparation for similar measurements with the Square Kilometre Array (SKA); (ii) an extinction free census of star formation and AGN activity out to z ∼ 1. In this paper we give an overview of the project including the science goals and multiwavelength coverage before presenting the first data release. We have analysed around 400 h of e-MERLIN data allowing us to create a Data Release 1 (DR1) mosaic of $\sim 0.26\, {\rm deg}^2$ to the full depth. These observations have been supplemented with complementary radio observations from the Karl G. Jansky Very Large Array (VLA) and optical/near infrared observations taken with the Subaru, Canada-France-Hawaii, and Spitzer Telescopes. The main data product is a catalogue of 887 sources detected by the VLA, of which 395 are detected by e-MERLIN and 197 of these aremore »resolved. We have investigated the size, flux, and spectral index properties of these sources finding them compatible with previous studies. Preliminary photometric redshifts, and an assessment of galaxy shapes measured in the radio data, combined with a radio-optical cross-correlation technique probing cosmic shear in a supercluster environment, are presented in companion papers.« less