Type Ia supernova parameter estimation: a comparison of two approaches using current datasets
Abstract
By using the Sloan Digital Sky Survey (SDSS) first year type Ia supernova (SN Ia) compilation, we compare two different approaches (traditional \chi^2 and complete likelihood) to determine parameter constraints when the magnitude dispersion is to be estimated as well. We consider cosmological constant + Cold Dark Matter (\Lambda CDM) and spatially flat, constant w Dark Energy + Cold Dark Matter (FwCDM) cosmological models and show that, for current data, there is a small difference in the best fit values and 30% difference in confidence contour areas in case the MLCS2k2 light-curve fitter is adopted. For the SALT2 light-curve fitter the differences are less significant ( 13% difference in areas). In both cases the likelihood approach gives more restrictive constraints. We argue for the importance of using the complete likelihood instead of the \chi^2 approach when dealing with parameters in the expression for the variance.
Cite
@article{arxiv.1104.2874,
title = {Type Ia supernova parameter estimation: a comparison of two approaches using current datasets},
author = {B. L. Lago and M. O. Calvão and S. E. Jorás and R. R. R. Reis and I. Waga and R. Giostri},
journal= {arXiv preprint arXiv:1104.2874},
year = {2015}
}
Comments
16 pages, 5 figures. More complete analysis by including peculiar velocities and correlations among SALT2 parameters. Use of 2D contours instead of 1D intervals for comparison. There can be now a significant difference between the approaches, around 30% in contour area for MLCS2k2 and up to 13% for SALT2. Generic streamlining of text and suppression of section on model selection