SALT2 Versus SALT3: Updated Model Surfaces and Their Impacts on Type Ia Supernova Cosmology

TL;DR

This study compares SALT2 and SALT3 supernova models, finding that switching models has negligible impact on dark energy measurements but improves calibration robustness, reducing uncertainties in supernova cosmology.

Contribution

The paper provides the first direct comparison of SALT2 and SALT3 models on identical data, revealing minimal impact on dark energy parameters and enhanced calibration stability with SALT3.

Findings

Switching from SALT2 to SALT3 has negligible effect on dark energy measurements.

SALT3 surfaces are less sensitive to photometric calibration uncertainties.

SALT3 reduces spectral energy density dispersion by a factor of two.

Abstract

For the past decade, SALT2 has been the most common model used to fit Type Ia supernova (SN Ia) light curves for dark energy analyses. Recently, the SALT3 model was released, which upgraded a number of model features but has not yet been used for measurements of dark energy. Here, we evaluate the impact of switching from SALT2 to SALT3 for a SN cosmology analysis. We train SALT2 and SALT3 on an identical training sample of 1083 well-calibrated Type Ia supernovae, ensuring that any differences found come from the underlying model framework. We publicly release the results of this training (the SALT "surfaces"). We then run a cosmology analysis on the public Dark Energy Survey 3-Year Supernova data sample (DES-SN3YR), and on realistic simulations of those data. We provide the first estimate of the SN+CMB systematic uncertainty arising from the choice of SALT model framework (i.e. SALT2 versus SALT3), $\Delta w = +0.001 \pm 0.005$ -- a negligible effect at the current level of dark energy analyses. We also find that the updated surfaces are less sensitive to photometric calibration uncertainties than previous SALT2 surfaces, with the average spectral energy density dispersion reduced by a factor of two over optical wavelengths. This offers an opportunity to reduce the contribution of calibration errors to SN cosmology uncertainty budgets.