Cosmological Evidence Modelling: a new simulation-based approach to constrain cosmology on non-linear scales

Understand

Extracting accurate cosmological information from galaxy-galaxy and galaxy-matter correlation functions on non-linear scales ($\lesssim 10 h^{-1} \mathrm{Mpc}$) requires cosmological simulations.

• Additionally, one has to marginalise over several nuisance parameters of the galaxy-halo connection.
• However, the computational cost of such simulations prohibits naive implementations of stochastic posterior sampling methods like Markov chain Monte Carlo (MCMC) that would require of order $\mathcal{O}(10^6)$ samples in cosmological parameter space.
• Several groups have proposed surrogate models as a solution: a so-called emulator is trained to reproduce observables for a limited number of realisations in parameter space.