Cosmological Parameter Uncertainties from SALT-II Type Ia Supernova Light Curve Models

Abstract

We use simulated SN Ia samples, including both photometry and spectra, to perform the first direct validation of cosmology analysis using the SALT-II light curve model. This validation includes residuals from the light curve training process, systematic biases in SN Ia distance measurements, and the bias on the dark energy equation of state parameter w. Using the SN-analysis package SNANA, we simulate and analyze realistic samples corresponding to the data samples used in the SNLS3 analysis: 120 low-redshift (z < 0.1) SNe Ia, 255 SDSS SNe Ia (z < 0.4), and 290 SNLS SNe Ia (z <= 1). To probe systematic uncertainties in detail, we vary the input spectral model, the model of intrinsic scatter, and the smoothing (i.e., regularization) parameters used during the SALT-II model training. Using realistic intrinsic scatter models results in a slight bias in the ultraviolet portion of the trained SALT-II model, and w biases (winput - wrecovered) ranging from -0.005 +/- 0.012 to -0.024 +/- 0.010. These biases are indistinguishable from each other within uncertainty; the average bias on w is -0.014 +/- 0.007.

Accepted by ApJ

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