The Bacco Simulation Project: Bacco Hybrid Lagrangian Bias Expansion Model in Redshift Space

Understand

We present an emulator that accurately predicts the power spectrum of galaxies in redshift space as a function of cosmological parameters.

• Our emulator is based on a 2nd-order Lagrangian bias expansion that is displaced to Eulerian space using cosmological $N$-body simulations.
• Redshift space distortions are then imprinted using the non-linear velocity field of simulated particles and haloes.
• We build the emulator using a forward neural network trained with the simulations of the BACCO project, which covers an 8-dimensional parameter space including massive neutrinos and dynamical dark energy.