Galaxy formation and evolution

Abstract:

Hot dust-obscured galaxies (Hot DOGs) are a rare population of hyperluminous dust-obscured quasars discovered by the Wide-field Infrared Survey Explorer (WISE) all-sky survey. The heavy circumnuclear dust obscuration allows only a small amount of scattered light from the obscured quasar to escape, enabling the decomposition of the stellar component from the total flux. The presence of scattered light enables the redshift of the source and the properties of the black hole to be obtained from the Sloan Digital Sky Survey (SDSS) and SDSS-related literature. From WISE and SDSS data, we select 11 hyperluminous Hot DOGs at z = 1.5–3.7 with bolometric luminosities Lbol ≳ 1047 erg s−1. We investigate the MBH–M⋆ relation in these sources using Bayesian spectral energy distribution fitting or with extra constraints from Hubble Space Telescope image decomposition. Stellar masses are successfully derived for eight Hot DOGs. We find high Eddington ratios λEdd in these Hot DOGs, with the median value of 1.05 and the maximum value close to 3. The super-Eddington accretion may be associated with the overdense environments of Hot DOGs. We find no significant differences in the MBH/M⋆ of these Hot DOGs compared to the local relation, suggesting that these dust-obscured quasars are the progenitors of massive early-type galaxies. We speculate that the subsequent evolution of Hot DOGs may be significantly influenced by active galactic nucleus feedback and remain on the local relation.

Abstract:

For the first time, we present a systematic search for galaxies with extended emission lines and potential outflow features using JWST medium-band images in the GOODS South field. This is done by comparing the morphology in medium-band images to adjacent continuum and UV bands. We look for galaxies that have a maximum extent 50% larger, an excess area 30% greater, or an axis ratio difference of more than 0.3 in the medium band compared to the reference bands. After visual inspection, we find 326 candidate galaxies at 1.4 < z < 8.4, with a peak in the population near cosmic noon, benefiting from the good coverage of the medium-band filters. By fitting their spectral energy distributions, we find that the candidate galaxies are at least 20% more bursty in their star-forming activity and have 50% more young stellar populations compared to a control sample selected based on the continuum band flux. Additionally, these candidates exhibit a significantly higher production rate of ionizing photons. We further find that candidates hosting known active galactic nuclei (AGN) produce extended emission that is more anisotropic compared to non-AGN candidates. A few of our candidates have been spectroscopically confirmed to have prominent outflow signatures through NIRSpec observations, showcasing the robustness of the photometric selection. Future spectroscopic follow-up will better help verify and characterize the kinematics and chemical properties of these systems.

Abstract:

We present the first results of the H i intensity mapping power spectrum analysis with the MeerKAT International GigaHertz Tiered Extragalactic Exploration (MIGHTEE) survey. We use data covering 4 square degrees in the COSMOS field using a frequency range of 962.5–1008.42 MHz, equivalent to H i emission in . The data consist of 15 pointings with a total of 94.2 h on-source. We verify the suitability of the MIGHTEE data for H i intensity mapping by testing for residual systematics across frequency, baselines, and pointings. We also vary the window used for H i signal measurements and find no significant improvement using stringent Fourier mode cuts. We compute the H i power spectrum at scales in autocorrelation as well as cross-correlation between observational scans using power spectrum domain averaging for pointings. We report consistent upper limits of 29.8 mK Mpc from the 2 cross-correlation measurements and 25.82 mK Mpc from autocorrelation at 2 Mpc.The low signal-to-noise ratio in this data potentially limits our ability to identify residual systematics, which will be addressed in the future by incorporating more data in the analysis.