The study of Type Ia supernovae spectral diversity using principal component analysis

Abstract

In order to use supernovae (SNe) as cosmological probes, a good understanding of their properties and diversity is necessary. Here we investigate whether principal component analysis (PCA) can be used to improve the calibration of Type Ia SNe. We apply PCA to two different cases: a small data set of supernova spectra taken at maximum light and a larger data set with more spectra taken at various epochs. On the SN Ia luminosity scale, the supernova SN 1991T appears at the upper end and SN 1991bg at the lower end. While 91bg-like SNe seem to form a distinct group, 91T-like SNe show a continuum of properties with normal SNe. The differences are mainly explained by line shifts in the spectra. However, we do not find that PCA is able to distinguish trends or subsets in the supernova data beyond what has already been found using specific spectral features.