  Ground and space-based sky surveys enable powerful cosmological probes based
on measurements of galaxy properties and the distribution of galaxies in the
Universe. These probes include weak lensing, baryon acoustic oscillations,
abundance of galaxy clusters, and redshift space distortions; they are
essential to improving our knowledge of the nature of dark energy. On the
theory and modeling front, large-scale simulations of cosmic structure
formation play an important role in interpreting the observations and in the
challenging task of extracting cosmological physics at the needed precision.
These simulations must cover a parameter range beyond the standard six
cosmological parameters and need to be run at high mass and force resolution.
One key simulation-based task is the generation of accurate theoretical
predictions for observables, via the method of emulation. Using a new sampling
technique, we explore an 8-dimensional parameter space including massive
neutrinos and a variable dark energy equation of state. We construct trial
emulators using two surrogate models (the linear power spectrum and an
approximate halo mass function). The new sampling method allows us to build
precision emulators from just 26 cosmological models and to increase the
emulator accuracy by adding new sets of simulations in a prescribed way. This
allows emulator fidelity to be systematically improved as new observational
data becomes available and higher accuracy is required. Finally, using one LCDM
cosmology as an example, we study the demands imposed on a simulation campaign
to achieve the required statistics and accuracy when building emulators for
dark energy investigations.
