Prof. Matt Jarvis

Abstract:

The Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) is a wide-field, integral-field spectroscopic survey designed to map the large-scale distribution of Lyα-emitting galaxies (LAEs) at 1.88 < z < 3.52 and constrain dark energy at cosmic noon. Using the 10 m Hobby–Eberly Telescope and the Visible Integral-Field Replicable Unit (IFU) Spectrograph, HETDEX obtains >35,000 spectra per exposure over 3500–5500 Å at R ∼ 800 with ∼1.″8 image quality, enabling an untargeted census of emission-line galaxies across 540 deg2. We present HETDEX Public Data Release 1 (PDR1), comprising 431,713 IFU observations covering 86.67 deg2 of noncontiguous sky in the Spring (13h, +51°) and Fall (1 .h 5, 0°) fields, along with legacy regions (Cosmic Evolution Survey, Great Observations Origins Deep Survey North, North Ecliptic Pole, SA22). PDR1 includes the HETDEX Public Source Catalog 2 (HPSC2), an expanded and reprocessed version of E. Mentuch Cooper et al. (2023) incorporating four additional years of data, improved quality control, and new machine learning classifiers. HPSC2 contains 426,654 LAEs, 491,411 [O II] emitters, 19,457 low-z galaxies, 18,303 active galactic nuclei, and 150,608 stars, providing coordinates, redshifts or stellar velocities, and 1D spectra for each source. Because the data cubes use local sky subtraction optimized for faint emission-line detection, they are not suited for absolute surface-brightness measurements or very extended nearby galaxies. Appendix materials include the full detection catalog, the 1.6 million–candidate LAE sample, and raw detection databases. All products are publicly accessible through the HETDEX data portal (https://hetdex.org/data-results/), including access to a public JupyterLab. HPSC2 is also publicly available via Zenodo (doi:10.5281/zenodo.19581262).

Abstract:

Type Ia supernova (SN Ia) standardization parameters exhibit evidence for systematic variation across the host galaxy star formation rate–stellar mass (SFR) plane, motivating the incorporation of galaxy SFR information in cosmological inference. SFRs are commonly estimated via spectral energy distribution (SED) fitting with far-infrared (FIR) measurements to account for dust-obscured star formation. Such FIR coverage will, however, be limited for upcoming time-domain surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST), necessitating the use of alternative SFR tracers. Here, we reconstruct the SFR– plane using 1.4 GHz diagnostics, to test the consistency of host classifications against FIR-constrained SED-based estimates. Within this plane, SN Ia host galaxies are divided into three regions: Region 1 (low mass), Region 2 (high-mass star forming), and Region 3 (high-mass passive). We find that per cent of SN hosts retain identical region assignments when using radio versus FIR-constrained SED-derived SFRs. Measuring SN Ia nuisance parameters () within each subregion, we find consistent values between the two SFR– plane reconstructions, indicating limited sensitivity to SFR estimator choice, with the largest deviations in Region 3 at . Across the three 1.4 GHz SFR– subregions, we confirm the region-dependent variation in SN Ia standardization parameters – particularly – reported in our earlier SED-based analysis. With near-complete radio coverage of the LSST footprint anticipated from current and forthcoming radio continuum surveys (e.g. Square Kilometre Array), radio SFR calibrations will become an increasingly useful and scalable approach to host galaxy classification, supporting the construction of robust SN Ia subsamples for precision cosmology.

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:

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.