Speaker
Description
Small-scale clustering holds a wealth of cosmological information, but also challenges us with finding models able to account for nonlinear gravitational growth, complex matter-galaxy connection, and astrophysical effects. I will present the BACCO simulations and baccoemu emulators, an approach that, by calibrating models on N-body simulations and training neural network to predict summary statistics, allows us to describe the dark matter power spectrum down to k=10 h/Mpc, including baryonic effects. Moreover, adopting a hybrid Lagrangian bias expansion based on perturbation theory and the same BACCO simulations, we can describe galaxy clustering down to scales as small as 0.7 h/Mpc. After reviewing these methods, I’ll present a novel constraint on Omega_m and sigma8 obtained by applying them to the shear angular power spectrum from a combination of weak lensing surveys, and the cross correlation between the clustering of low-redshift galaxies and CMB lensing, discussing the challenges, results, and future prospects for 3x2point analyses with Stage IV galaxy surveys.