A New Insight into the Classification of Type Ia Supernovae

TL;DR

This study uses wavelet analysis of Type Ia Supernova spectra to identify subgroups with different properties, which could impact their use in precise cosmological measurements.

Contribution

It introduces a wavelet-based method to classify SNe Ia subgroups and disentangle intrinsic color from dust extinction effects, improving cosmological distance estimates.

Findings

Identified two distinct SNe Ia subgroups based on wavelet coefficients.

Demonstrated how wavelet analysis can separate intrinsic color from dust reddening.

Proposed a technique to estimate extinction using wavelength-dependent wavelet coefficients.

Abstract

Type Ia Supernovae (SNe Ia) spectra are compared regarding the coefficient of the largest wavelet scale in their decomposition. Two distinct subgroups were identified and their occurrence is discussed in light of use of SNe Ia as cosmological probes. Apart from the group of normal SNe, another trend characterised by intrinsically redder colours is consisted of many different SN events that exhibit diverse properties, including the interaction with the circumstellar material, the existence of specific shell-structure in or surrounding the SN ejecta or super-Chandrasekhar mass progenitors. Compared with the normal objects, these SNe may violate the standard width-luminosity correction, which could influence the cosmological results if they were all calibrated equally, since their fraction among SNe Ia is not negligible when performing precision cosmology. Using largest wavelet scale coefficient in combination with long-baseline B-I colours, we show how to disentangle SN intrinsic colour from the part that corresponds to the reddening due to dust extinction in the host galaxy in the SALT2 colour parameter c, discussing how the intrinsic colour differences may explain the different reddening laws for two subsamples. There are wavelength intervals for which the measured largest scale coefficient is invariant to the additional extinction applied to a spectrum. Combination of wavelet coefficients measured in different wavelength intervals can be used to develop a technique that allows for estimation of extinction.