Speaker
Description
Type Ia supernovae (SNe Ia) have played a significant role in measuring the acceleration of the Universe's expansion and the existence of dark energy. Correct characterization of systematics is crucial to accurately measuring cosmological parameters. An example of such a systematic is the potential presence of SN Ia progenitor-related sub-populations, the rates of which can change over cosmic time. In this talk, we present a novel Bayesian hierarchical two-population model of SNe Ia observables which enables us to measure the presence and properties of two sub-populations as well as the redshift evolution of their relative fractions. This allows us to investigate the impact of these elements on the precision and accuracy of constraints on cosmological parameters. Our model builds on earlier work by accounting for the potentially varying fraction of two distinct SNe Ia populations over cosmic time. By modeling the redshift dependence of the two populations, we can estimate their respective fractions at different epochs and explore the impact of these changes on cosmological constraints. We apply our model to both simulations and to observational data from Pantheon+. We show that observational data has signatures of redshift dependent fractions of the SNe populations and discuss these results in the context of current work on SNe Ia progenitors. We find that this demographic drift has potentially important implications for measuring the properties of dark energy, as it affects the derived distances and properties of Type Ia supernovae.
