Redshift evolution of the underlying type Ia supernova stretch
  distribution
  The detailed nature of type Ia supernovae (SNe Ia) remains uncertain, and as
survey statistics increase, the question of astrophysical systematic
uncertainties arises, notably that of the evolution of SN Ia populations. We
study the dependence on redshift of the SN Ia light-curve stretch, a purely
intrinsic SN property, to probe its potential redshift drift. The SN stretch
has been shown to be strongly correlated with the SN environment, notably with
stellar age tracers. We modeled the underlying stretch distribution as a
function of redshift, using the evolution of the fraction of young and old SNe
Ia as predicted using the SNfactory dataset, and assuming a constant underlying
stretch distribution for each age population consisting of Gaussian mixtures.
We tested our prediction against published samples that were cut to have
marginal magnitude selection effects so that any observed change is indeed
astrophysical and not observational in origin. In this first study, there are
indications that the underlying SN Ia stretch distribution evolves as a
function of redshift, and that the age drifting model is a better description
of the data than any time-constant model, including the sample-based asymmetric
distributions that are often used to correct Malmquist bias at a significance
higher than 5 $\sigma$. The favored underlying stretch model is a bimodal one,
composed of a high-stretch mode shared by both young and old environments, and
a low-stretch mode that is exclusive to old environments. The precise effect of
the redshift evolution of the intrinsic properties of a SN Ia population on
cosmology remains to be studied. The astrophysical drift of the SN stretch
distribution does affect current Malmquist bias corrections and hence the
distances that are derived using SNe that are affected by observational
selection effects. This bias increases with surveys covering larger redshift
ranges.
