The SCUBA-2 850 μm\mu m follow-up of WISE-selected, luminous dust-obscured quasars

Hot dust-obscured galaxies (Hot DOGs) are a new population recently discovered in the \wise All-Sky survey. Multiwavelength follow-up observations suggest that they are luminous, dust-obscured quasars at high redshift. Here we present the JCMT SCUBA-2 850 $\mu m$ follow-up observations of 10 Hot DOGs. Four out of ten Hot DOGs have been detected at $>3\sigma$ level. Based on the IR SED decomposition approach, we derive the IR luminosities of AGN torus and cold dust components. Hot DOGs in our sample are extremely luminous with most of them having $L_{\rm IR}^{\rm tot}>10^{14} L_\odot$. The torus emissions dominate the total IR energy output. However, the cold dust contribution is still non-negligible, with the fraction of the cold dust contribution to the total IR luminosity $(\sim 8-24\%)$ being dependent on the choice of torus model. The derived cold dust temperatures in Hot DOGs are comparable to those in UV bright quasars with similar IR luminosity, but much higher than those in SMGs. Higher dust temperatures in Hot DOGs may be due to the more intense radiation field caused by intense starburst and obscured AGN activities. Fourteen and five submillimeter serendipitous sources in the 10 SCUBA-2 fields around Hot DOGs have been detected at $>3\sigma$ and $>3.5\sigma$ levels, respectively. By estimating their cumulative number counts, we confirm the previous argument that Hot DOGs lie in dense environments. Our results support the scenario in which Hot DOGs are luminous, dust-obscured quasars lying in dense environments, and being in the transition phase between extreme starburst and UV-bright quasars.Comment: 26 pages, 7 figures, PASP accepte

BayeSED-GALAXIES I. Performance test for simultaneous photometric redshift and stellar population parameter estimation of galaxies in the CSST wide-field multiband imaging survey

The forthcoming CSST wide-field multiband imaging survey will produce seven-band photometric spectral energy distributions (SEDs) for billions of galaxies. The effective extraction of astronomical information from these massive datasets of SEDs relies on the techniques of both SED synthesis (or modeling) and analysis (or fitting). We evaluate the performance of the latest version of BayeSED code combined with SED models with increasing complexity for simultaneously determining the photometric redshifts and stellar population parameters of galaxies in this survey. By using an empirical statistics-based mock galaxy sample without SED modeling errors, we show finding that the random observational errors in photometries are more important sources of errors than the parameter degeneracies and Bayesian analysis method and tool. By using a Horizon-AGN hydrodynamical simulation-based mock galaxy sample with SED modeling errors about the star formation histories (SFHs) and dust attenuation laws (DALs), the simple typical assumptions lead to significantly worse parameter estimation with CSST photometries only. The SED models with more flexible (or complicated) forms of SFH/DAL do not necessarily lead to better estimation of redshift and stellar population parameters. We discuss the selection of the best SED model by means of Bayesian model comparison in different surveys. Our results reveal that the Bayesian model comparison with Bayesian evidence may favor SED models with different complexities when using photometries from different surveys. Meanwhile, the SED model with the largest Bayesian evidence tends to give the best performance of parameter estimation, which is more clear for photometries with larger discriminative power.Comment: Accepted for publication in ApJS (49 pages, 23 figures, 5 tables). Comments are welcome! The new version of BayeSED code, documents, and the scripts used for the performance tests presented in this work will be publicly available at https://bitbucket.org/hanyk/bayesed/, https://bayesed.readthedocs.io/, and https://github.com/hanyk/BayeSED-performance-test/, respectivel

ALMA Reveals a Gas-rich, Maximum Starburst in the Hyperluminous, Dust-obscured Quasar W0533-3401 at z similar to 2.9

We present ALMA observations and multiwavelength spectral energy distribution analysis in a Wide-field Infrared Survey Explorer-selected, hyperluminous dust-obscured quasar W0533-3401 at z = 2.9. We derive the physical properties of each of its components, such as molecular gas, stars, dust, and the central supermassive black hole (SMBH). Both the dust continuum at 3 mm and the CO (3-2) line are detected. The derived molecular gas mass M-gas = 8.4 x 10(10) M-circle dot and its fraction f(gas) = 0.7 suggest that W0533-3401 is gas-rich. The star formation rate (SFR) has been estimated to be similar to 3000-7000M(circle dot) yr(-1) by using different methods. The high values of SFR and specific SFR suggest that W0533-3401 is a maximum starburst. The corresponding gas depletion timescales are very short (t(depl) similar to 12-28 Myr). The CO (3-2) emission line is marginally resolved and has a velocity gradient, which is possibly due to a rotating gas disk, gas outflow, or merger. Finally, we infer the black hole mass growth rate of W0533-3401 ((M)over dot(BH) = 49 M-circle dot yr(-1)), which suggests a rapid growth of the central SMBH. The observed black hole to stellar mass ratio M-BH/M-* of W0533-3401, which is dependent on the adopted Eddington ratio, is over one order of magnitude higher than the local value, and is evolving toward the evolutionary trend of unobscured quasars. Our results are consistent with the scenario that W0533-3401, with both a gas-rich maximum starburst and a rapid black hole growth, is experiencing a short transition phase toward an unobscured quasar

Decoding spectral energy distributions of dust-obscured starburst-AGN

We present BayeSED, a general purpose tool for doing Bayesian analysis of SEDs by using whatever pre-existing model SED libraries or their linear combinations. The artificial neural networks (ANNs), principal component analysis (PCA) and multimodal nested sampling (MultiNest) techniques are employed to allow a highly efficient sampling of posterior distribution and the calculation of Bayesian evidence. As a demonstration, we apply this tool to a sample of hyperluminous infrared galaxies (HLIRGs). The Bayesian evidences obtained for a pure Starburst, a pure AGN, and a linear combination of Starburst+AGN models show that the Starburst+AGN model have the highest evidence for all galaxies in this sample. The Bayesian evidences for the three models and the estimated contributions of starburst and AGN to infrared luminosity show that HLIRGs can be classified into two groups: one dominated by starburst and the other dominated by AGN. Other parameters and corresponding uncertainties about starburst and AGN are also estimated by using the model with the highest Bayesian evidence. We found that the starburst region of the HLIRGs dominated by starburst tends to be more compact and has a higher fraction of OB star than that of HLIRGs dominated by AGN. Meanwhile, the AGN torus of the HLIRGs dominated by AGN tend to be more dusty than that of HLIRGs dominated by starburst. These results are consistent with previous researches, but need to be tested further with larger samples. Overall, we believe that BayeSED could be a reliable and efficient tool for exploring the nature of complex systems such as dust-obscured starburst-AGN composite systems from decoding their SEDs.Comment: 12 pages, 9 figure

Birthrates and delay times of Type Ia supernovae

Type Ia supernovae (SNe Ia) play an important role in diverse areas of astrophysics, from the chemical evolution of galaxies to observational cosmology. However, the nature of the progenitors of SNe Ia is still unclear. In this paper, according to a detailed binary population synthesis study, we obtained SN Ia birthrates and delay times from different progenitor models, and compared them with observations. We find that the Galactic SN Ia birthrate from the double-degenerate (DD) model is close to those inferred from observations, while the birthrate from the single-degenerate (SD) model accounts for only about 1/2-2/3 of the observations. If a single starburst is assumed, the distribution of the delay times of SNe Ia from the SD model is a weak bimodality, where the WD + He channel contributes to the SNe Ia with delay times shorter than 100Myr, and the WD + MS and WD + RG channels to those with age longer than 1Gyr.Comment: 11 pages, 2 figures, accepted by Science in China Series G (Dec.30, 2009