Stringent $\sigma_8$ constraints from small-scale galaxy clustering using a hybrid MCMC+emulator framework

Understand

We present a novel simulation-based hybrid emulator approach that maximally derives cosmological and Halo Occupation Distribution (HOD) information from non-linear galaxy clustering, with sufficient precision for DESI Year 1 (Y1) analysis.

• Our hybrid approach first samples the HOD space on a fixed cosmological simulation grid to constrain the high-likelihood region of cosmology+HOD parameter space, and then constructs the emulator within this constrained region.
• This approach significantly reduces the parameter volume emulated over, thus achieving much smaller emulator errors with fixed number of training points.
• We demonstrate that this combined with state-of-the-art simulations result in tight emulator errors comparable to expected DESI Y1 LRG sample variance.