The Quijote simulations are a set of 44,100 full N-body simulations spanning more than 7000 cosmological models in the hyperplane. At a single redshift, the simulations contain more than 8.5 trillion particles over a combined volume of 44,100 each simulation follows the evolution of 256³, 512³, or 1024³ particles in a box of 1 h ⁻¹ Gpc length. Billions of dark matter halos and cosmic voids have been identified in the simulations, whose runs required more than 35 million core hours. The Quijote simulations have been designed for two main purposes: (1) to quantify the information content on cosmological observables and (2) to provide enough data to train machine-learning algorithms. In this paper, we describe the simulations and show a few of their applications. We also release the petabyte of data generated, comprising hundreds of thousands of simulation snapshots at multiple redshifts; halo and void catalogs; and millions of summary statistics, such as power spectra, bispectra, correlation functions, marked power spectra, and estimated probability density functions.

Current and upcoming radio telescopes will map the spatial distribution of cosmic neutral hydrogen (H i) through its 21 cm emission. In order to extract the maximum information from these surveys, accurate theoretical predictions are needed. We study the abundance and clustering properties of H i at redshifts z ≤ 5 using TNG100, a large state-of-the-art magnetohydrodynamic simulation of a 75 h ⁻¹ Mpc box size, which is part of the IllustrisTNG Project. We show that most of the H i lies within dark matter halos, and we provide fits for the halo H i mass function, i.e., the mean H i mass hosted by a halo of mass M at redshift z. We find that only halos with circular velocities larger than ≃30 km s⁻¹ contain H i. While the density profiles of H i exhibit a large halo-to-halo scatter, the mean profiles are universal across mass and redshift. The H i in low-mass halos is mostly located in the central galaxy, while in massive halos the H i is concentrated in the satellites. Our simulation reproduces the bias value of damped Lyα systems from observations. We show that the H i and matter density probability distribution functions differ significantly. Our results point out that for small halos, the H i bulk velocity goes in the same direction and has the same magnitude as the halo peculiar velocity, while in large halos, differences show up. We find that halo H i velocity dispersion follows a power law with halo mass. We find a complicated H i bias, with H i already becoming nonlinear at k = 0.3 h Mpc⁻¹ at z ≳ 3. The clustering of H i can, however, be accurately reproduced by perturbative methods. We find a new secondary bias by showing that the clustering of halos depends not only on mass but also on H i content. We compute the amplitude of the H i shot noise and find that it is small at all redshifts, verifying the robustness of BAO measurements with 21 cm intensity mapping. We study the clustering of H i in redshift space and show that linear theory can explain the ratio between the monopoles in redshift and real space down to 0.3, 0.5, and 1 h Mpc⁻¹ at redshifts 3, 4, and 5, respectively. We find that the amplitude of the Fingers-of-God effect is larger for H i than for matter, since H i is found only in halos above a certain mass. We point out that 21 cm maps can be created from N-body simulations rather than full hydrodynamic simulations. Modeling the one-halo term is crucial for achieving percent accuracy with respect to a full hydrodynamic treatment. Although our results are not converged against resolution, they are, however, very useful as we work at the resolution where the model parameters have been calibrated to reproduce galaxy properties.

We present the one-loop 2-point function of biased tracers in redshift space computed with Lagrangian perturbation theory, including a full resummation of both long-wavelength (infrared) displacements and associated velocities. The resulting model accurately predicts the power spectrum and correlation function of halos and mock galaxies from two different sets of N-body simulations at the percent level for quasi-linear scales, including the damping of the baryon acoustic oscillation signal due to the bulk motions of galaxies. We compare this full resummation with other, approximate, techniques including the moment expansion and Gaussian streaming model. We discuss infrared resummation in detail and compare our Lagrangian formulation with the Eulerian theory augmented by an infrared resummation based on splitting the input power spectrum into “wiggle” and “no-wiggle” components. We show that our model is able to recover unbiased cosmological parameters in mock data encompassing a volume much larger than what will be available to future galaxy surveys. We demonstrate how to efficiently compute the resulting expressions numerically, making available a fast Python code capable of rapidly computing these statistics in both configuration and Fourier space.