UC Berkeley

We estimate systematic errors due to K-corrections in standard photometric analyses of high-redshift Type Iasupernovae. Errors due to K-correction occur when the spectral template model underlying the light curve fitterpoorly represents the actual supernova spectral energy distribution, meaning that the distance modulus cannot berecovered accurately. In order to quantify this effect, synthetic photometry is performed on artificially redshiftedspectrophotometric data from 119 low-redshift supernovae from the Nearby Supernova Factory, and the resultinglight curves are fit with a conventional light curve fitter. We measure the variation in the standardized magnitudethat would be fit for a given supernova if located at a range of redshifts and observed with various filter setscorresponding to current and future supernova surveys. We find significant variation in the measurements of thesame supernovae placed at different redshifts regardless of filters used, which causes dispersion greater than?0.05 mag for measurements of photometry using the Sloan-like filters and a bias that corresponds to a 0.03 shift inw when applied to an outside data set. To test the result of a shift in supernova population or environment at higherredshifts, we repeat our calculations with the addition of a reweighting of the supernovae as a function of redshiftand find that this strongly affects the results and would have repercussions for cosmology. We discuss possiblemethods to reduce the contribution of the K-correction bias and uncertainty.