The BACCO simulation project: biased tracers in real space
Abstract
We present an emulator for the twopoint clustering of biased tracers in real space. We construct this emulator using neural networks calibrated with more than 400 cosmological models in a 8D 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 cosmologydependence is captured thanks to a cosmologyrescaling algorithm. We show that our emulator is capable of describing the power spectrum of galaxy formation simulations for a sample mimicking that of a typical EmissionLine survey at z ~ 1 with an accuracy of $12~{{\ \rm per\ cent}}$ up to nonlinear scales $k\sim 0.7 h\, {\rm Mpc}^{1}$.
 Publication:

Monthly Notices of the Royal Astronomical Society
 Pub Date:
 September 2023
 DOI:
 10.1093/mnras/stad2008
 arXiv:
 arXiv:2101.12187
 Bibcode:
 2023MNRAS.524.2407Z
 Keywords:

 methods: observational;
 methods: statistical;
 largescale structure of Universe;
 cosmology: theory;
 Astrophysics  Cosmology and Nongalactic Astrophysics
 EPrint:
 14 pages, 8 figures