Optimizing future dark energy surveys for model selection goals

We demonstrate a methodology for optimizing the ability of future dark energy surveys to answer model selection questions, such as ‘Is acceleration due to a cosmological constant or a dynamical dark energy model?’. Model selection figures of merit (FoMs) are defined, exploiting the Bayes factor, and surveys optimized over their design parameter space via a Monte Carlo method. As a specific example...