Galaxy clustering from the bottom up: A Streaming Model emulator I

Abstract

In this series of papers, we present a simulation-based model for the non-linear clustering of galaxies based on separate modelling of clustering in real space and velocity statistics. In the first paper, we present an emulator for the real-space correlation function of galaxies, whereas the emulator of the real-to-redshift space mapping based on velocity statistics is presented in the second paper. Here, we show that a neural network emulator for real-space galaxy clustering trained on data extracted from the Dark Quest suite of N-body simulations achieves sub-per cent accuracies on scales $1<r<30$ $h^{-1}\mathrm{Mpc}$, and better than $3\%$ on scales $r<1$ $h^{-1}\mathrm{Mpc}$ in predicting the clustering of dark-matter haloes with number density $10^{-3.5}$ $(h^{-1}\mathrm{Mpc}{)}^{-3}$, close to that of SDSS LOWZ-like galaxies. The halo emulator can be combined with a galaxy-halo connection model to predict the galaxy correlation function through the halo model. We demonstrate that we accurately recover the cosmological and galaxy-halo connection parameters when galaxy clustering depends only on the mass of the galaxies' host halos. Furthermore, the constraining power in ${\sigma }_8$ increases by about a factor of $2$ when including scales smaller than $5$ $h^{-1}\mathrm{Mpc}$. However, when mass is not the only property responsible for galaxy clustering, as observed in hydrodynamical or semi-analytic models of galaxy formation, our emulator gives biased constraints on ${\sigma }_8$. This bias disappears when small scales ($r<10$ $h^{-1}\mathrm{Mpc}$) are excluded from the analysis. This shows that a vanilla halo model could introduce biases into the analysis of future datasets.

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• SHAMe-SF: Predicting the clustering of star-forming galaxies with an enhanced abundance matching model
• Revisiting Vainshtein Screening for fast N-body simulations
• Investigating the galaxy-halo connection of DESI Emission-Line Galaxies with SHAMe-SF
• A new test of gravity -- I: Introduction to the method
• An emulation-based model for the projected correlation function