We use simulated type Ia supernova ( 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 a 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 : \sim 120 low-redshift ( z < 0.1 ) SNe Ia , \sim 255 SDSS SNe Ia ( z < 0.4 ) , and \sim 290 SNLS SNe Ia ( z \leq 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 ( w _ { input } - w _ { recovered } ) ranging from -0.005 \pm 0.012 to -0.024 \pm 0.010 .
These biases are indistinguishable from each other within the uncertainty ; the average bias on w is -0.014 \pm 0.007 .