Abstract
Observations of Type Ia supernovae used to map the expansion history of theUniverse suffer from systematic uncertainties that need to be propagated intothe estimates of cosmological parameters. We propose an iterative MonteCarlo simulation and cosmology fitting technique (SMOCK) to investigate theimpact of sources of error upon fits of the dark energy equation of state. Thisapproach is especially useful to track the impact of non-Gaussian, correlatedeffects, e.g. reddening correction errors, brightness evolution of the supernovae,K-corrections, gravitational lensing, etc. While the tool is primarily aimed at studiesand optimization of future instruments, we use the Gold data-set in Riess et al (2007 Astrophys. J. 659 98) to show examples of potential systematic uncertainties thatcould exceed the quoted statistical uncertainties.
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