The Mira-Titan Universe: Precision Predictions for Dark Energy Surveys

TL;DR

This paper develops a new efficient sampling and emulation method for high-precision cosmological predictions across an 8-dimensional parameter space, aiding dark energy research.

Contribution

It introduces a novel sampling technique and constructs accurate emulators for complex cosmological observables using minimal simulations.

Findings

Achieved high-accuracy emulators with only 26 models.

Systematically improved emulator fidelity with additional simulations.

Demonstrated emulator application for dark energy parameter estimation.

Abstract

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.