The Square Kilometre Array (SKA)

Abstract:

The interplay between atomic gas and the star formation history (SFH) of a galaxy are intrinsically linked, and we need to decouple these dependencies to understand their role in galaxy formation and evolution. In this paper, we analyse the SFH of 203 galaxies from the MIGHTEE-H i Survey Early Science Release data, cross-matched to with multiwavelength photometry across the COSMOS and XMM-LSS fields. We focus on the relationships between H i properties and star formation, with a sample which primarily traces gas-rich, star-forming systems at low redshift, extending to low stellar masses and probing regimes that are difficult to access with optically selected samples. A strong correlation emerges between a galaxy’s H i-to-stellar mass ratio and the time of formation, alongside an inverse correlation between stellar mass and time of formation, regardless of the inferred SFH. Additionally, galaxies with lower stellar masses and higher H i-to-stellar mass ratios exhibit longer gas depletion times compared to more massive galaxies, which appear to have depleted their gas and formed stars more efficiently. This suggests that smaller, gas-rich galaxies have higher depletion times due to shallower potential wells and less efficient star formation. Within this H i-selected sample, the efficiency of star formation is regulated primarily by stellar mass and gas fraction, with low-mass galaxies retaining extended atomic reservoirs due to inefficient conversion of H i into stars.

Abstract:

Upcoming cosmic microwave background (CMB) experiments aim to detect primordial gravitational waves with unprecedented sensitivity. Effective foreground removal is essential to avoid biases in the measurement of the tensor-to-scalar ratio (r) in this high-precision regime. Recent analyses highlight the unexpected complexity of synchrotron emission at low frequencies, underscoring the need for more sensitive low-frequency data. To address this challenge, the European Low-Frequency Survey (ELFS) initiative and the Simons Array collaboration propose installing two European low-frequency receivers on one of the Simons Array telescopes. These receivers will enable measurements in the Southern Hemisphere between 6 and 20 GHz, complementary to those of current and proposed experiments targeting the measurement of cosmological gravitational waves. In this work, we study the benefits of combining these low-frequency observations with a representative future CMB experiment operating from the Southern Hemisphere. We find that the extra information can improve the knowledge of the underlying synchrotron spectral energy distribution (SED), with positive impacts on the robustness of measurement of the tensor-to-scalar ratio, r, against the complexity of low-frequency foregrounds.

Abstract:

The upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will enable astronomers to discover rare and distant astrophysical transients. Host-galaxy association is crucial for selecting the most scientifically interesting transients for follow-up. LSST deep drilling field (DDF) observations will detect distant transients occurring in galaxies below the detection limits of most all-sky catalogs. Here, we investigate the use of preexisting, field-specific catalogs for host identification in the DDFs and a ranking of their usefulness. We have compiled a database of 70 deep catalogs that overlap with the Rubin DDFs and constructed thin catalogs to be homogenized and combined for transient-host matching. A systematic ranking of their utility is discussed and applied based on the inclusion of information such as spectroscopic redshifts and morphological information. Utilizing this data against a Dark Energy Survey sample of supernovae with pre-identified hosts in the XMM-Large Scale Structure and the Extended Chandra Deep Field-South fields, we evaluate different methods for transient-host association in terms of both accuracy and processing speed. We also apply light data-cleaning techniques to identify and remove contaminants within our associations, such as diffraction spikes and blended galaxies where the correct host cannot be determined with confidence. We use a lightweight machine learning approach in the form of extreme gradient boosting to generate confidence scores in our contaminant selections and associated metrics. Finally, we discuss the computational expense of implementation within the LSST transient alert brokers, which will require efficient, fast-paced processing to handle the large stream of survey data.

Abstract:

Abstract A key question in extragalactic astronomy is how the star-formation rate density (SFRD) evolves over cosmic time. A powerful way of addressing this question is using radio-continuum observations, where the radio waves are unaffected by dust and are able to reach sufficient resolution to resolve individual galaxies. We present an investigation of the 1.4 GHz radio luminosity functions (RLFs) of star-forming galaxies (SFGs) and Active Galactic Nuclei (AGN) using deep radio continuum observations in the COSMOS and XMM–LSS fields, covering a combined area of ∼4 deg2. These data enable the most accurate measurement of the evolution in the SFRD from mid-frequency radio continuum observations. We model the total RLF as the sum of evolving SFG and AGN components, negating the need for individual source classification. We find that the SFGs have systematically higher space densities at fixed luminosity than found in previous radio studies, but consistent with more recent studies with MeerKAT. We attribute this to the excellent low-surface brightness sensitivity of MeerKAT. We then determine the evolution of the SFRD. Adopting the far-infrared – radio correlation results in a significantly higher SFRD at z > 1, compared to combined UV and far-infrared measurements. However, using more recent relations for the correlation between star-formation rate and radio luminosity, based on full spectral energy distribution modelling, can resolve this apparent discrepancy. Thus radio observations provide a powerful method of determining the total SFRD, in the absence of dust-sensitive far-infrared data.