Applications of 1.4 GHz diagnostics to Type Ia Supernova host galaxies

TL;DR

This study assesses the use of 1.4 GHz radio diagnostics as an alternative to FIR-based SFR estimates for classifying Type Ia supernova host galaxies, finding consistent results and supporting future radio-based surveys.

Contribution

It demonstrates that 1.4 GHz radio diagnostics reliably classify SN Ia host galaxies, aligning with FIR-based methods, and highlights their potential for upcoming large-scale surveys.

Findings

84% of SN hosts have consistent classifications between radio and FIR methods.

SN Ia standardisation parameters show region-dependent variation, especially in $eta$.

Radio SFR calibrations are promising for future large-scale host galaxy classification.

Abstract

Type Ia supernova (SN Ia) standardisation parameters exhibit evidence for systematic variation across the host galaxy star-formation rate - stellar mass (SFR$-M_\star$) 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 - $M_\star$ 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 ${\sim}84$ per cent of SN hosts retain identical region assignments when using radio versus FIR-constrained SED-derived SFRs. Measuring SN Ia nuisance parameters ($\alpha,\beta, M$) within each subregion, we find consistent values between the two SFR - $M_\star$ plane reconstructions, indicating limited sensitivity to SFR estimator choice, with the largest deviations in Region 3 at ${\sim}1.1\sigma$. Across the three 1.4 GHz SFR - $M_\star$ subregions, we confirm the region-dependent variation in SN Ia standardisation parameters - particularly $\beta$ - 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.