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We present ALMA 870 μm and JCMT/SCUBA2 850 μm dust continuum observations of a sample of optically dark and strongly lensed galaxies in cluster fields. The ALMA and SCUBA2 observations reach a median rms of ∼0.11 mJy and 0.44 mJy, respectively, with the latter close to the confusion limit of the data at 850 μm. This represents one of the most sensitive searches for dust emission in optically dark galaxies. We detect the dust emission in 12 out of 15 galaxies at >3.8σ, corresponding to a detection rate of 80%. Thanks to the gravitational lensing, we reach a deeper limiting flux than previous surveys in blank fields by a factor of ∼3. We estimate delensed infrared luminosities in the range 2.9 × 1011–4.9 × 1012L⊙, which correspond to dust-obscured star formation rates of ∼30–520 M⊙ yr−1. Stellar population fits to the optical-to-NIR photometric data yield a median redshift z = 4.26 and delensed stellar mass 6.0 × 1010M⊙. They contribute a lensing-corrected star formation rate density at least an order of magnitude higher than that of equivalently massive UV-selected galaxies at z > 3. The results suggest that there is a missing population of massive star-forming galaxies in the early Universe, which may dominate the SFR density at the massive end (M⋆ > 1010.3M⊙). Five optically dark galaxies are located within r < 50″ in one cluster field, representing a potential overdensity structure that has a physical origin at a confidence level >99.974% from Poisson statistics. Follow-up spectroscopic observations with ALMA and/or JWST are crucial to confirm whether it is associated with a protocluster at similar redshifts. [ABSTRACT FROM AUTHOR]

We investigate the performance of machine-learning techniques in classifying active galactic nuclei (AGNs), including X-ray-selected AGNs (XAGNs), infrared-selected AGNs (IRAGNs), and radio-selected AGNs (RAGNs). Using the known physical parameters in the Cosmic Evolution Survey (COSMOS) field, we are able to create quality training samples in the region of the Hyper Suprime-Cam (HSC) survey. We compare several Python packages (e.g., scikit-learn, Keras, and XGBoost) and use XGBoost to identify AGNs and show the performance (e.g., accuracy, precision, recall, F1 score, and AUROC). Our results indicate that the performance is high for bright XAGN and IRAGN host galaxies. The combination of the HSC (optical) information with the Wide-field Infrared Survey Explorer band 1 and band 2 (near-infrared) information performs well to identify AGN hosts. For both type 1 (broad-line) XAGNs and type 1 (unobscured) IRAGNs, the performance is very good by using optical-to-infrared information. These results can apply to the five-band data from the wide regions of the HSC survey and future all-sky surveys. [ABSTRACT FROM AUTHOR]

We examine the robustness of the color–color selection of quiescent galaxies (QGs) against contamination of dusty star-forming galaxies using the latest submillimeter data. We selected 18,304 QG candidates out to z ∼ 3 using the commonly adopted NUV–r–J selection based on the high-quality multiwavelength COSMOS2015 catalog. Using extremely deep 450 and 850 μm catalogs from the latest JCMT SCUBA-2 Large Programs, S2COSMOS and STUDIES, as well as the Atacama Large Millimeter/submillimeter Array submillimeter, VLA 3 GHz, and Spitzer MIPS 24 μm catalogs, we identified luminous, dusty, star-forming galaxies among the QG candidates. We also conducted stacking analyses in the SCUBA-2 450 and 850 μm images to look for less-luminous dusty galaxies among the QG candidates. By cross matching to the 24 μm and 3 GHz data, we were able to identify a subgroup of "IR-radio-bright" QGs that possess strong 450 and 850 μm stacking signals. The potential contamination of these luminous and less-luminous dusty galaxies accounts for approximately 10% of the color-selected QG candidates. In addition, there exists a spatial correlation between the luminous star-forming galaxies and the QGs at a ≲60 kpc scale. Finally, we found a high QG fraction among radio active galactic nuclei (AGNs) at z < 1.5. Our data show a strong correlation between QGs and radio AGNs, which may suggest a connection between the quenching process and the radio-mode AGN feedback. [ABSTRACT FROM AUTHOR]

We analyze an extremely deep 450 μm image (1σ = 0.56 mJy beam−1) of a ≃300 arcmin2 area in the CANDELS/COSMOS field as part of the Sub-millimeter Common User Bolometric Array-2 Ultra Deep Imaging EAO Survey. We select a robust (signal-to-noise ratio ≥4) and flux-limited (≥4 mJy) sample of 164 submillimeter galaxies (SMGs) at 450 μm that have K-band counterparts in the COSMOS2015 catalog identified from radio or mid-infrared imaging. Utilizing this SMG sample and the 4705 K-band-selected non-SMGs that reside within the noise level ≤1 mJy beam−1 region of the 450 μm image as a training set, we develop a machine-learning classifier using K-band magnitude and color–color pairs based on the 13-band photometry available in this field. We apply the trained machine-learning classifier to the wider COSMOS field (1.6 deg2) using the same COSMOS2015 catalog and identify a sample of 6182 SMG candidates with similar colors. The number density, radio and/or mid-infrared detection rates, redshift and stellar-mass distributions, and the stacked 450 μm fluxes of these SMG candidates, from the S2COSMOS observations of the wide field, agree with the measurements made in the much smaller CANDELS field, supporting the effectiveness of the classifier. Using this SMG candidate sample, we measure the two-point autocorrelation functions from z = 3 down to z = 0.5. We find that the SMG candidates reside in halos with masses of ≃(2.0 ± 0.5) × 1013h−1M☉ across this redshift range. We do not find evidence of downsizing that has been suggested by other recent observational studies. [ABSTRACT FROM AUTHOR]

Recent progress in submillimetre surveys by single-dish telescopes allows us to further challenge the consistency between cosmological simulations and observations. In particular, we compare our simulations that include dust formation and destruction with the recent SCUBA-2 surveys ('STUDIES') by putting emphases on basic observational properties of dust emission such as dust temperature, size of infrared (IR)-emitting region, IR luminosity function, and IRX–β relation. After confirming that our models reproduce the local galaxy properties, we examine the STUDIES sample at |$z$|  ≈ 1–4, finding that the simulation reproduces the aforementioned quantities except for the |$z$|  ≳ 2 IR luminosity function at the massive end (∼1013 L⊙). This means that the current simulation correctly reproduces the overall scaling between the size and luminosity (or star formation rate) of dusty region, but lacks extreme starburst phenomena at |$z$|  ≳ 2. We also discuss extinction curves and possible active galactic nucleus contribution. [ABSTRACT FROM AUTHOR]