Extending the halo mass resolution of N-body simulations (original) (raw)

An accurate tool for the fast generation of dark matter halo catalogues

Monthly Notices of the Royal Astronomical Society, 2013

We present a new parallel implementation of the PINpointing Orbit Crossing-Collapsed HIerarchical Objects (PINOCCHIO) algorithm, a quick tool, based on Lagrangian Perturbation Theory, for the hierarchical build-up of Dark Matter (DM) halos in cosmological volumes. To assess its ability to predict halo correlations on large scales, we compare its results with those of an N-body simulation of a 3 h −1 Gpc box sampled with 2048 3 particles taken from the MICE suite, matching the same seeds for the initial conditions. Thanks to the FFTW libraries and to the relatively simple design, the code shows very good scaling properties. The CPU time required by PINOCCHIO is a tiny fraction (∼ 1/2000) of that required by the MICE simulation. Varying some of PINOCCHIO numerical parameters allows one to produce a universal mass function that lies in the range allowed by published fits, although it underestimates the MICE mass function of Friends-of-Friends (FoF) halos in the high mass tail. We compare the matter-halo and the halo-halo power spectra with those of the MICE simulation and find that these 2-point statistics are well recovered on large scales. In particular, when catalogs are matched in number density, agreement within ten per cent is achieved for the halo power spectrum. At scales k > 0.1 h Mpc −1 , the inaccuracy of the Zel'dovich approximation in locating halo positions causes an underestimate of the power spectrum that can be modeled as a Gaussian factor with a damping scale of d = 3 h −1 Mpc at z = 0, decreasing at higher redshift. Finally, a remarkable match is obtained for the reduced halo bispectrum, showing a good description of nonlinear halo bias. Our results demonstrate the potential of PINOCCHIO as an accurate and flexible tool for generating large ensembles of mock galaxy surveys, with interesting applications for the analysis of large galaxy redshift surveys.

nIFTy cosmology: Galaxy/halo mock catalogue comparison project on clustering statistics

Monthly Notices of the Royal Astronomical Society, 2015

We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point (power spectrum and 2-point correlation function in real-and redshift-space), and the three-point clustering statistics (bispectrum and 3-point correlation function). The reference catalogues are drawn from the BigMultiDark Nbody simulation. Both friend-of-friends (including distinct halos only) and spherical overdensity (including distinct halos and subhalos) catalogs have been used with the typical number density of a large-volume galaxy surveys. We demonstrate that a proper biasing model is essential for reproducing the power spectrum at quasilinear and even smaller scales. With respect to various clustering statistics a methodology based on perturbation theory and a realistic biasing model leads to very good agreement with N-body simulations. However, for the quadrupole of the correlation function or the power spectrum, only the method based on semi-N -body simulation could reach high accuracy (1% level) at small scales, i.e., r < 25 h −1 Mpc or k > 0.15 h Mpc −1 . For those methods that only produce distinct haloes, a halo occupation distribution (HOD) scheme is applied to generate substructures. We find however, that it is not trivial to reproduce the clustering properties of the reference SO catalogue that include E-mail: chia-hsun.chuang@uam.es, MultiDark Fellow c 0000 RAS arXiv:1412.7729v2 [astro-ph.CO] 25 Dec 2014 2 Chuang et al.

Halo mass distribution reconstruction across the cosmic web

We study the relation between halo mass and its environment from a probabilistic perspective. We find that halo mass depends not only on local dark matter density, but also on non-local quantities such as the cosmic web environment and the haloexclusion effect. Given these accurate relations, we have developed the hadron-code (Halo mAss Distribution ReconstructiON), a technique which permits us to assign halo masses to a distribution of haloes in three-dimensional space. This can be applied to the fast production of mock galaxy catalogues, by assigning halo masses, and reproducing accurately the bias for different mass cuts. The resulting clustering of the halo populations agree well with that drawn from the BigMultiDark N -body simulation: the power spectra are within 1-σ up to scales of k = 0.2 h Mpc −1 , when using augmented Lagrangian perturbation theory based mock catalogues. Only the most massive haloes show a larger deviation. For these, we find evidence of the haloexclusion effect. A clear improvement is achieved when assigning the highest masses to haloes with a minimum distance separation. We also compute the 2-and 3-point correlation functions, and find an excellent agreement with N -body results. Our work represents a quantitative application of the cosmic web classification. It can have further interesting applications in the multi-tracer analysis of the large-scale structure for future galaxy surveys.

Density profiles of dark matter halos

2010

Abstract We examine the density profiles of dark matter halos by analyzing data from the LasDamas (Large Suite of Dark Matter Simulations) project. LasDamas consists of a large suite of cosmological N-body simulations that follow the evolution of dark matter in the universe. The aim of LasDamas is to obtain adequate resolution in many large boxes, resulting in a huge volume appropriate for statistical studies of galaxies and halos.

Halo-based reconstruction of the cosmic mass density field

Monthly Notices of the Royal Astronomical Society, 2011

We present the implementation of a halo based method for the reconstruction of the cosmic mass density field. The method employs the mass density distribution of dark matter haloes and its environments computed from cosmological N-body simulations and convolves it with a halo catalog to reconstruct the dark matter density field determined by the distribution of haloes. We applied the method to the group catalog of Yang et al. built from the SDSS Data Release 4. As result we obtain reconstructions of the cosmic mass density field that are independent on any explicit assumption of bias. We describe in detail the implementation of the method, present a detailed characterization of the reconstructed density field (mean mass density distribution, correlation function and counts in cells) and the results of the classification of large scale environments (filaments, voids, peaks and sheets) in our reconstruction. Applications of the method include morphological studies of the galaxy population on large scales and the realization of constrained simulations.

Predicting the Number, Spatial Distribution, and Merging History of Dark Matter Halos

The Astrophysical Journal, 2002

We present a new algorithm (PINOCCHIO, PINpointing Orbit-Crossing Collapsed HIerarchical objects) to predict accurately the formation and evolution of individual dark matter haloes in a given realization of an initial linear density field. Compared with the halo population formed in a large (360 3 particles) collisionless simulation of a CDM universe, our method is able to predict to better than 10 per cent statistical quantities such as the mass function, two-point correlation function and progenitor mass function of the haloes. Masses of individual haloes are estimated accurately as well, with errors typically of order 30 per cent in the mass range well resolved by the numerical simulation. These results show that the hierarchical formation of dark matter haloes can be accurately predicted using local approximations to the dynamics when the correlations in the initial density field are properly taken into account. The approach allows one to automatically generate a large ensemble of accurate merging histories of haloes with complete knowledge of their spatial distribution. The construction of the full merger tree for a 256 3 realisation requires a few hours of CPU-time on a personal computer, orders of magnitude faster than the corresponding N -body simulation would take, and without needing any extensive post-processing. The technique can be efficiently used, for instance, for generating the input for galaxy formation modeling.

Modeling the Galaxy Distribution in Clusters using Halo Cores

Open Journal of Astrophysics, 2023

The galaxy distribution in dark matter-dominated halos is expected to approximately trace the details of the underlying dark matter substructure. In this paper we introduce halo 'core-tracking' as a way to efficiently follow the small-scale substructure in cosmological simulations and apply the technique to model the galaxy distribution in observed clusters. The method relies on explicitly tracking the set of particles identified as belonging to a halo's central density core, once a halo has attained a certain threshold mass. The halo cores are then followed throughout the entire evolution of the simulation. The aim of core-tracking is to simplify substructure analysis tasks by avoiding the use of subhalos and, at the same time, to more easily account for the so-called 'orphan' galaxies, which have lost substantial dark mass due to tidal stripping. We show that simple models based on halo cores can reproduce the number and spatial distribution of galaxies found in optically-selected clusters in the Sloan Digital Sky Survey. We also discuss future applications of the core-tracking methodology in studying the galaxy-halo connection.

Precision Determination of the Mass Function of Dark Matter Halos

Astrophysical Journal, 2005

The predicted mass function of dark matter halos is essential in connecting observed galaxy cluster counts and models of galaxy clustering to the properties of the primordial density field. We determine the mass function in the concordance Lambda\LambdaLambdaCDM cosmology, as well as its uncertainty, using sixteen 102431024^310243-particle nested-volume dark-matter simulations, spanning a mass range of over five orders of magnitude. Using the nested volumes and single-halo tests, we find and correct for a systematic error in the friends-of-friends halo-finding algorithm. We find a fitting form and full error covariance for the mass function that successfully describes the simulations' mass function and is well-behaved outside the simulations' resolutions. Estimated forecasts of uncertainty in cosmological parameters from future cluster count surveys have negligible contribution from remaining statistical uncertainties in the central cosmology multiplicity function. There exists a potentially non-negligible cosmological dependence (non-universality) of the halo multiplicity function.

Accurate halo-galaxy mocks from automatic bias estimation and particle mesh gravity solvers

Monthly Notices of the Royal Astronomical Society

Reliable extraction of cosmological information from clustering measurements of galaxy surveys requires estimation of the error covariance matrices of observables. The accuracy of covariance matrices is limited by our ability to generate sufficiently large number of independent mock catalogues that can describe the physics of galaxy clustering across a wide range of scales. Furthermore, galaxy mock catalogues are required to study systematics in galaxy surveys and to test analysis tools. In this investigation, we present a fast and accurate approach for generation of mock catalogues for the upcoming galaxy surveys. Our method relies on low-resolution approximate gravity solvers to simulate the large-scale dark matter field, which we then populate with haloes according to a flexible non-linear and stochastic bias model. In particular, we extend the PATCHY code with an efficient particle mesh algorithm to simulate the dark matter field (the FASTPM code), and with a robust MCMC method relying on the EMCEE code for constraining the parameters of the bias model. Using the haloes in the BigMultiDark high-resolution N-body simulation as a reference catalogue, we demonstrate that our technique can model the bivariate probability distribution function (counts-in-cells), power spectrum and bispectrum of haloes in the reference catalogue. Specifically, we show that the new ingredients permit us to reach percentage accuracy in the power spectrum up to k ∼ 0.4 h Mpc −1 (within 5 per cent up to k ∼ 0.6 h Mpc −1) with accurate bispectra improving previous results based on Lagrangian perturbation theory.

The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos

The Astrophysical Journal, 2013

We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30Mpc box with 2048 3 particles. The mass of each particle is 1.28 × 10 5 M ⊙ , which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen (1999) fitting function down to ∼ 10 7 M ⊙. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than −1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ∼ 10 8 M ⊙ .