Bayesian model selection for dark energy using weak lensing forecasts
  The next generation of weak lensing probes can place strong constraints on
cosmological parameters by measuring the mass distribution and geometry of the
low redshift universe. We show that a future all-sky tomographic cosmic shear
survey with design properties similar to Euclid can provide the statistical
accuracy required to distinguish between different dark energy models. Using a
fiducial cosmological model which includes cold dark matter, baryons, massive
neutrinos (hot dark matter), a running primordial spectral index and possible
spatial curvature as well as dark energy perturbations, we calculate Fisher
matrix forecasts for different dynamical dark energy models. Using a Bayesian
evidence calculation we show how well a future weak lensing survey could do in
distinguishing between a cosmological constant and dynamical dark energy.
