Redshift evolution of the underlying type Ia supernova stretch distribution
N. Nicolas, M. Rigault, Y. Copin, R. Graziani, G. Aldering, M. Briday,, J. Nordin, Y.-L. Kim, S. Perlmutter, M. Smith

TL;DR
This study investigates how the intrinsic stretch distribution of Type Ia supernovae evolves with redshift, revealing that a bimodal, age-dependent model better explains observed data and impacts cosmological distance measurements.
Contribution
It introduces a redshift-dependent, bimodal model of SN Ia stretch distribution based on stellar age, improving understanding of supernova evolution and its effect on cosmology.
Findings
Evidence for redshift evolution of SN Ia stretch distribution
Bimodal model with age-dependent high and low stretch modes fits data better
Implications for bias correction in cosmological distance measurements
Abstract
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…
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