Information Gain in Cosmology: From the Discovery of Expansion to Future   Surveys
  Facing the advent of the next generation cosmological surveys we present a method to forecast knowledge gain on cosmological models. We propose this as a well defined and general tool to quantify the performance of different experiments in relation to different theoretical models. In particular, the assessment of experimental performance will benefit enormously from the fact that this method is invariant under re-parametrization of the model. We apply this to future surveys and compare expected knowledge advancements to the most relevant experiments performed over the history of modern cosmology. When considering the standard cosmological model, we show that it will rapidly reach knowledge saturation in the near future and forthcoming improvements will not match the past ones. On the contrary, we find that new observations have the potential for unprecedented knowledge jumps when extensions of the standard scenario are considered. 
Marco Raveri, Matteo Martinelli, Gongbo Zhao, Yuting Wang
astro-ph.CO gr-qc physics.data-an