The BACCO simulation project: biased tracers in real space

Understand

We present an emulator for the two-point clustering of biased tracers in real space.

• We construct this emulator using neural networks calibrated with more than $400$ cosmological models in a 8-dimensional cosmological parameter space that includes massive neutrinos an dynamical dark energy.
• The properties of biased tracers are described via a Lagrangian perturbative bias expansion which is advected to Eulerian space using the displacement field of numerical simulations.
• The cosmology-dependence is captured thanks to a cosmology-rescaling algorithm.