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We explore full-shape analysis with simulation-based priors, which is the simplest approach to galaxy clustering data analysis that combines effective field theory (EFT) on large scales and numerical simulations on small scales. The core ingredient of our approach is the prior density of EFT parameters which we extract from a suite of 10, 500 galaxy simulations based on the halo occupation distribution (HOD) model. We measure the EFT parameters with the field-level forward model, which enables us to cancel cosmic variance. On the theory side, we develop a new efficient approach to calculate field-level transfer functions using time-sliced perturbation theory and the logarithmic fast Fourier transform. We find that the cosmology dependence of EFT parameters of galaxies is approximately degenerate with the HOD parameters, and hence it can be ignored for the purpose of prior generation. We use neural density estimation to model the measured distribution of EFT parameters. Our distribution model is then used as a prior in a reanalysis of the Baryon Oscillation Spectroscopic Survey (BOSS) full-shape galaxy power spectrum data. Assuming the model, we find significant (30% and 60%) improvements for the matter density fraction and the mass fluctuation amplitude, which are constrained to ₌=0. 3150. 010 and ₈=0. 6710. 027. The value of the Hubble constant does not change, H₀=68. 71. 1 km/s/Mpc. This reaffirms earlier reports of the structure growth tension from the BOSS data. Finally, we use the measured EFT parameters to constrain the galaxy-dark matter connection.
Ivanov et al. (Fri,) studied this question.