Characterising ultra-high-redshift dark matter halo demographics and assembly histories with the GUREFT simulations

arxiv(2023)

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摘要
Dark matter halo demographics and assembly histories are a manifestation of cosmological structure formation and have profound implications for the formation and evolution of galaxies. In particular, merger trees provide fundamental input for several modelling techniques, such as semi-analytic models (SAMs), sub-halo abundance matching (SHAM), and decorated halo occupation distribution models (HODs). Motivated by the new ultra-high-redshift (z > 10) frontier enabled by JWST, we present a new suite of Gadget at Ultrahigh Redshift with Extra-Fine Timesteps (GUREFT) dark matter-only cosmological simulations that are carefully designed to capture halo merger histories and structural properties in the ultra-z universe. The simulation suite consists of four 1024^3-particle simulations with box sizes of 5, 15, 35, and 90 Mpc h-1, each with 170 snapshots stored between 40 > z > 6. With the unprecedented number of available snapshots and strategically chosen dynamic range covered by these boxes, gureft uncovers the emerging dark matter halo populations and their assembly histories in the earliest epochs of cosmic history. In this work, we present the halo mass functions between z   20 to 6 down to log(Mvir/Msun)   5, and show that at high redshift, these robust halo mass functions can differ substantially from commonly used analytic approximations or older fitting functions in the literature. We also present key physical properties of the ultra-z halo population, such as concentration and spin, as well as their mass growth and merger rates, and again provide updated fitting functions.
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