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Register a new userDark Quest. I. Fast and Accurate Emulation of Halo Clustering Statistics and Its Application to Galaxy Clustering
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Added by
Takahiro Nishimichi
Publication date
2018
fields
Physics
and research's language is
English
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We perform an ensemble of $N$-body simulations with $2048^3$ particles for 101 flat $w$CDM cosmological models sampled based on a maximin-distance Sliced Latin Hypercube Design. By using the halo catalogs extracted at multiple redshifts in the range of $z=[0,1.48]$, we develop Dark Emulator, which enables fast and accurate computations of the halo mass function, halo-matter cross-correlation, and halo auto-correlation as a function of halo masses, redshift, separations and cosmological models, based on the Principal Component Analysis and the Gaussian Process Regression for the large-dimensional input and output data vector. We assess the performance of the emulator using a validation set of $N$-body simulations that are not used in training the emulator. We show that, for typical halos hosting CMASS galaxies in the Sloan Digital Sky Survey, the emulator predicts the halo-matter cross correlation, relevant for galaxy-galaxy weak lensing, with an accuracy better than $2%$ and the halo auto-correlation, relevant for galaxy clustering correlation, with an accuracy better than $4%$. We give several demonstrations of the emulator. It can be used to study properties of halo mass density profiles such as the mass-concentration relation and splashback radius for different cosmologies. The emulator outputs can be combined with an analytical prescription of halo-galaxy connection such as the halo occupation distribution at the equation level, instead of using the mock catalogs, to make accurate predictions of galaxy clustering statistics such as the galaxy-galaxy weak lensing and the projected correlation function for any model within the $w$CDM cosmologies, in a few CPU seconds.
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Small- and intermediate-scale galaxy clustering can be used to establish the galaxy-halo connection to study galaxy formation and evolution and to tighten constraints on cosmological parameters. With the increasing precision of galaxy clustering measurements from ongoing and forthcoming large galaxy surveys, accurate models are required to interpret the data and extract relevant information. We introduce a method based on high-resolution N-body simulations to accurately and efficiently model the galaxy two-point correlation functions (2PCFs) in projected and redshift spaces. The basic idea is to tabulate all information of haloes in the simulations necessary for computing the galaxy 2PCFs within the framework of halo occupation distribution or conditional luminosity function. It is equivalent to populating galaxies to dark matter haloes and using the mock 2PCF measurements as the model predictions. Besides the accurate 2PCF calculations, the method is also fast and therefore enables an efficient exploration of the parameter space. As an example of the method, we decompose the redshift-space galaxy 2PCF into different components based on the type of galaxy pairs and show the redshift-space distortion effect in each component. The generalizations and limitations of the method are discussed.
Within the standard paradigm, dark energy is taken as a homogeneous fluid that drives the accelerated expansion of the universe and does not contribute to the mass of collapsed objects such as galaxies and galaxy clusters. The abundance of galaxy clusters -- measured through a variety of channels -- has been extensively used to constrain the normalization of the power spectrum: it is an important probe as it allows us to test if the standard $Lambda$CDM model can indeed accurately describe the evolution of structures across billions of years. It is then quite significant that the Planck satellite has detected, via the Sunyaev-Zeldovich effect, less clusters than expected according to the primary CMB anisotropies. One of the simplest generalizations that could reconcile these observations is to consider models in which dark energy is allowed to cluster, i.e., allowing its sound speed to vary. In this case, however, the standard methods to compute the abundance of galaxy clusters need to be adapted to account for the contributions of dark energy. In particular, we examine the case of clustering dark energy -- a dark energy fluid with negligible sound speed -- with a redshift-dependent equation of state. We carefully study how the halo mass function is modified in this scenario, highlighting corrections that have not been considered before in the literature. We address modifications in the growth function, collapse threshold, virialization densities and also changes in the comoving scale of collapse and mass function normalization. Our results show that clustering dark energy can impact halo abundances at the level of 10%--30%, depending on the halo mass, and that cluster counts are modified by about 30% at a redshift of unity.
We use a large dark matter simulation of a LambdaCDM model to investigate the clustering and environmental dependence of the number of substructures in a halo. Focusing on redshift z=1, we find that the halo occupation distribution is sensitive at the tens of percent level to the surrounding density and to a lesser extent to asymmetry of the surrounding density distribution. We compute the autocorrelation function of halos as a function of occupation, building on the finding of Wechsler et al. (2006) and Gao and White (2007) that halos (at fixed mass) with more substructure are more clustered. We compute the relative bias as a function of occupation number at fixed mass, finding a strong relationship. At fixed mass, halos in the top 5% of occupation can have an autocorrelation function ~ 1.5-2 times higher than the mean. We also compute the bias as a function of halo mass, for fixed halo occupation. We find that for group and cluster sized halos, when the number of subhalos is held fixed, there is a strong anticorrelation between bias and halo mass. Such a relationship represents an additional challenge to the halo model.
We present a comparison of major methodologies of fast generating mock halo or galaxy catalogues. The comparison is done for two-point and the three-point clustering statistics. The reference catalogues are drawn from the BigMultiDark N-body 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 Mpc/h or k>0.15 h/Mpc. Full N-body solutions will remain indispensable to produce reference catalogues. Nevertheless, we have demonstrated that the far more efficient approximate solvers can reach a few percent accuracy in terms of clustering statistics at the scales interesting for the large-scale structure analysis after calibration with a few reference N-body calculations. This makes them useful for massive production aimed at covariance studies, to scan large parameter spaces, and to estimate uncertainties in data analysis techniques, such as baryon acoustic oscillation reconstruction, redshift distortion measurements, etc.
LCDM cosmological models with Early Dark Energy (EDE) have been proposed to resolve tensions between the Hubble constant H0 = 100h km/s/Mpc measured locally, giving h ~ 0.73, and H0 deduced from Planck cosmic microwave background (CMB) and other early universe measurements plus LCDM, giving h ~ 0.67. EDE models do this by adding a scalar field that temporarily adds dark energy equal to about 10% of the cosmological energy density at the end of the radiation-dominated era at redshift z ~ 3500. Here we compare linear and nonlinear predictions of a Planck-normalized LCDM model including EDE giving h = 0.728 with those of standard Planck-normalized LCDM with h = 0.678. We find that nonlinear evolution reduces the differences between power spectra of fluctuations at low redshifts. As a result, at z = 0 the halo mass functions on galactic scales are nearly the same, with differences only 1-2%. However, the differences dramatically increase at high redshifts. The EDE model predicts 50% more massive clusters at z = 1 and twice more galaxy-mass halos at z = 4. Even greater increases in abundances of galaxy-mass halos at higher redshifts may make it easier to reionize the universe with EDE. Predicted galaxy abundances and clustering will soon be tested by JWST observations. Positions of baryonic acoustic oscillations (BAOs) and correlation functions differ by about 2% between the models -- an effect that is not washed out by nonlinearities. Both standard LCDM and the EDE model studied here agree well with presently available acoustic-scale observations, but DESI and Euclid measurements will provide stringent new tests.
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