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Register a new userThe Dependence of Halo Clustering on Halo Formation History, Concentration, and Occupation
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Risa H. Wechsler
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We investigate the dependence of dark matter halo clustering on halo formation time, density profile concentration, and subhalo occupation number, using high-resolution numerical simulations of a LCDM cosmology. We confirm results that halo clustering is a function of halo formation time, and that this trend depends on halo mass. For the first time, we show unequivocally that halo clustering is a function of halo concentration and show that the dependence of halo bias on concentration, mass, and redshift can be accurately parameterized in a simple way: b(c,M|z) = b(M|z) b(c|M/M*). The scaling between bias and concentration changes sign with the value of M/M*: high concentration (early forming) objects cluster more strongly for M <~ M* while low concentration (late forming) objects cluster more strongly for rare high-mass halos, M >~ M*. We show the first explicit demonstration that host dark halo clustering depends on the halo occupation number (of dark matter subhalos) and discuss implications for halo model calculations of dark matter power spectra and galaxy clustering statistics. The effect of these halo properties on clustering is strongest for early-forming dwarf-mass halos, which are significantly more clustered than typical halos of their mass. Our results suggest that isolated low-mass galaxies (e.g. low surface-brightness dwarfs) should have more slowly-rising rotation curves than their clustered counterparts, and may have consequences for the dearth of dwarf galaxies in voids. They also imply that self calibrating richness-selected cluster samples with their clustering properties might overestimate cluster masses and bias cosmological parameter estimation.
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We study the dependence of the galaxy contents within halos on the halo formation time using two galaxy formation models, one being a semianalytic model utilizing the halo assembly history from a high resolution N-body simulation and the other being a smoothed particle hydrodynamics simulation including radiative cooling, star formation, and energy feedback from galactic winds. We confirm the finding by Gao et al. that at fixed mass, the clustering of halos depends on the halo formation time, especially for low-mass halos. This age dependence of halo clustering makes it desirable to study the correlation between the occupation of galaxies within halos and the halo age. We find that, in halos of fixed mass, the number of satellite galaxies has a strong dependence on halo age, with fewer satellites in older halos. The youngest one-third of the halos can have an order of magnitude more satellites than the oldest one-third. For central galaxies, in halos that form earlier, they tend to have more stars and thus appear to be more luminous, and the dependence of their luminosity on halo age is not as strong as that of stellar mass. The results can be understood through the star formation history in halos and the merging of satellites onto central galaxies. The age dependence of the galaxy contents within halos would constitute an important ingredient in a more accurate halo-based model of galaxy clustering.
Hierarchical structure formation implies that the number of subhalos within a dark matter halo depends not only on halo mass, but also on the formation history of the halo. This dependence on the formation history, which is highly correlated with halo concentration, can account for the super-Poissonian scatter in subhalo occupation at a fixed halo mass that has been previously measured in simulations. Here we propose a model to predict the subhalo abundance function for individual host halos, that incorporates both halo mass and concentration. We combine results of cosmological simulations with a new suite of zoom-in simulations of Milky Way-mass halos to calibrate our model. We show the model can successfully reproduce the mean and the scatter of subhalo occupation in these simulations. The implications of this correlation between subhalo abundance and halo concentration are further investigated. We also discuss cases in which inferences about halo properties can be affected if this correlation between subhalo abundance and halo concentration is ignored; in these cases our model would give a more accurate inference. We propose that with future deep surveys, satellite occupation in the low-mass regime can be used to verify the existence of halo assembly bias.
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.
Halo bias is the main link between the matter distribution and dark matter halos. In its simplest form, halo bias is determined by halo mass, but there are known additional dependencies on other halo properties which are of consequence for accurate modeling of galaxy clustering. Here we present the most precise measurement of these secondary-bias dependencies on halo age, concentration, and spin, for a wide range of halo masses spanning from 10$^{10.7}$ to 10$^{14.7}$ $h^{-1}$ M$_{odot}$. At the high-mass end, we find no strong evidence of assembly bias for masses above M$_{vir}$ $sim10^{14}$ $h^{-1}$ M$_{odot}$. Secondary bias exists, however, for halo concentration and spin, up to cluster-size halos, in agreement with previous findings. For halo spin, we report, for the first time, two different regimes: above M$_{vir}sim$10$^{11.5}$ $h^{-1}$ M$_{odot}$, halos with larger values of spin have larger bias, at fixed mass, with the effect reaching almost a factor 2. This trend reverses below this characteristic mass. In addition to these results, we test, for the first time, the performance of a multi-tracer method for the determination of the relative bias between different subsets of halos. We show that this method increases significantly the signal-to-noise of the secondary-bias measurement as compared to a traditional approach. This analysis serves as the basis for follow-up applications of our multi-tracer method to real data.
A generic prediction of hierarchical gravitational clustering models is that the distribution of halo formation times should depend relatively strongly on halo mass, massive haloes forming more recently, and depend only weakly, if at all, on the large scale environment of the haloes. We present a novel test of this assumption which uses a statistic that proves to be particularly well-suited to detecting and quantifying weak correlations with environment. We find that close pairs of haloes form at slightly higher redshifts than do more widely separated halo pairs, suggesting that haloes in dense regions form at slightly earlier times than do haloes of the same mass in less dense regions. The environmental trends we find are useful for models which relate the properties of galaxies to the formation histories of the haloes which surround them.
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