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 χ^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 (ΛCDM) 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 $\sim$ 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 ($\lesssim$ 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 χ^2 approach when dealing with parameters in the expression for the variance.

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

References in corpus (20)

• Five-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Interpretation
• Improved Cosmological Constraints from New, Old and Combined Supernova Datasets
• Spectra and Light Curves of Six Type Ia Supernovae at 0.511 < z < 1.12 and the Union2 Compilation
• Observational Constraints on the Nature of the Dark Energy: First Cosmological Results from the ESSENCE Supernova Survey
• Improved Dark Energy Constraints from ~100 New CfA Supernova Type Ia Light Curves
• Supernova Constraints and Systematic Uncertainties from the First 3 Years of the Supernova Legacy Survey
• Improved Distances to Type Ia Supernovae with Multicolor Light Curve Shapes: MLCS2k2
• ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization
• The Supernova Legacy Survey 3-year sample: Type Ia Supernovae photometric distances and cosmological constraints
• The Carnegie Supernova Project: Light Curve Fitting with SNooPy
• SiFTO: An Empirical Method for Fitting SNe Ia Light Curves
• Type Ia Supernovae as Stellar Endpoints and Cosmological Tools
• The effect of peculiar velocities on supernova cosmology
• Supernova cosmology: legacy and future
• Improved constraints on cosmological parameters from SNIa data
• A Critique of Supernova Data Analysis in Cosmology
• Constraining dust and color variations of high-z SNe using NICMOS on Hubble Space Telescope
• Reducing Zero-point Systematics in Dark Energy Supernova Experiments
• Type-Ia supernovae: new clues to their progenitors from the delay-time distribution
• Foundations of Supernova Cosmology

Cited by in corpus (14)

• Marginal evidence for cosmic acceleration from Type Ia supernovae
• A More General Model for the Intrinsic Scatter in Type Ia Supernova Distance Moduli
• Model-independent determination of $H_0$ and ${\Omega }_{K0}$ from strong lensing and type Ia supernovae
• Does Chaplygin gas have salvation?
• Accurate Weak Lensing of Standard Candles. II. Measuring sigma8 with Supernovae
• Internal Robustness: systematic search for systematic bias in SN Ia data
• Cosmology with Ricci dark energy
• A Redshift Dependent Color-Luminosity Relation in Type 1a Supernovae
• Application of Bayesian graphs to SN Ia data analysis and compression
• Backreaction and FRW consistency conditions
• Testing the mutual consistency of different supernovae surveys
• ASTROMLSKIT: A New Statistical Machine Learning Toolkit: A Platform for Data Analytics in Astronomy
• Simple inhomogeneous cosmological (toy) models
• Constraining LTB models with JLA supernovae and BAO