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 hal
o 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.
Several direct detection experiments, including recently CDMS-II, have reported signals consistent with 5 to 10 GeV dark matter (DM) that appear to be in tension with null results from XENON and LUX experiments; these indicate a careful review of the
theoretical basis, including the galactic DM velocity distribution function (VDF). We establish a VDF parameter space from DM-only cosmological simulations and illustrate that seemingly contradictory experimental results can be made consistent within this parameter space. Future experimental limits should be reported after they are marginalized over a range of VDF parameters.
Using reconstructed galaxy star formation histories, we calculate the instantaneous efficiency of galaxy star formation (i.e., the star formation rate divided by the baryon accretion rate) from $z=8$ to the present day. This efficiency exhibits a cle
ar peak near a characteristic halo mass of 10^11.7 Msun, which coincides with longstanding theoretical predictions for the mass scale relevant to virial shock heating of accreted gas. Above the characteristic halo mass, the efficiency falls off as the mass to the minus four-thirds power; below the characteristic mass, the efficiency falls off at an average scaling of mass to the two-thirds power. By comparison, the shape and normalization of the efficiency change very little since z=4. We show that a time-independent star formation efficiency simply explains the shape of the cosmic star formation rate since z=4 in terms of dark matter accretion rates. The rise in the cosmic star formation from early times until z=2 is especially sensitive to galaxy formation efficiency. The mass dependence of the efficiency strongly limits where most star formation occurs, with the result that two-thirds of all star formation has occurred inside halos within a factor of three of the characteristic mass, a range that includes the mass of the Milky Way.
We investigate unbound dark matter particles in halos by tracing particle trajectories in a simulation run to the far future (a = 100). We find that the traditional sum of kinetic and potential energies is a very poor predictor of which dark matter p
articles will eventually become unbound from halos. We also study the mass fraction of unbound particles, which increases strongly towards the edges of halos, and decreases significantly at higher redshifts. We discuss implications for dark matter detection experiments, precision calibrations of the halo mass function, the use of baryon fractions to constrain dark energy, and searches for intergalactic supernovae.
We present a robust method to constrain average galaxy star formation rates, star formation histories, and the intracluster light as a function of halo mass. Our results are consistent with observed galaxy stellar mass functions, specific star format
ion rates, and cosmic star formation rates from z=0 to z=8. We consider the effects of a wide range of uncertainties on our results, including those affecting stellar masses, star formation rates, and the halo mass function at the heart of our analysis. As they are relevant to our method, we also present new calibrations of the dark matter halo mass function, halo mass accretion histories, and halo-subhalo merger rates out to z=8. We also provide new compilations of cosmic and specific star formation rates; more recent measurements are now consistent with the buildup of the cosmic stellar mass density at all redshifts. Implications of our work include: halos near 10^12 Msun are the most efficient at forming stars at all redshifts, the baryon conversion efficiency of massive halos drops markedly after z ~ 2.5 (consistent with theories of cold-mode accretion), the ICL for massive galaxies is expected to be significant out to at least z ~ 1-1.5, and dwarf galaxies at low redshifts have higher stellar mass to halo mass ratios than previous expectations and form later than in most theoretical models. Finally, we provide new fitting formulae for star formation histories that are more accurate than the standard declining tau model. Our approach places a wide variety of observations relating to the star formation history of galaxies into a self-consistent framework based on the modern understanding of structure formation in LCDM. Constraints on the stellar mass-halo mass relationship and star formation rates are available for download at http://www.peterbehroozi.com/data.html .
We present a new algorithm for generating merger trees and halo catalogs which explicitly ensures consistency of halo properties (mass, position, and velocity) across timesteps. Our algorithm has demonstrated the ability to improve both the completen
ess (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. In addition, our method is able to robustly measure the self-consistency of halo finders; it is the first to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistency between snapshots in cosmological simulations. We use this algorithm to generate merger trees for two large simulations (Bolshoi and Consuelo) and evaluate two halo finders (ROCKSTAR and BDM). We find that both the ROCKSTAR and BDM halo finders track halos extremely well; in both, the number of halos which do not have physically consistent progenitors is at the 1-2% level across all halo masses. Our code is publicly available at http://code.google.com/p/consistent-trees . Our trees and catalogs are publicly available at http://hipacc.ucsc.edu/Bolshoi/ .
We calculate the probability that a Milky-Way-like halo in the standard cosmological model has the observed number of Magellanic Clouds (MCs). The statistics of the number of MCs in the LCDM model are in good agreement with observations of a large sa
mple of SDSS galaxies. Under the sub-halo abundance matching assumption of a relationship with small scatter between galaxy r-band luminosities and halo internal velocities v_max, we make detailed comparisons to similar measurements using SDSS DR7 data by Liu et al. (2010). Models and observational data give very similar probabilities for having zero, one, and two MC-like satellites. In both cases, Milky Way-luminosity hosts have just a sim 10% chance of hosting two satellites similar to the Magellanic Clouds. In addition, we present a prediction for the probability for a host galaxy to have Nsats satellite galaxies as a function of the magnitudes of both the host and satellite. This probability and its scaling with host properties is significantly different from that of mass-selected objects because of scatter in the mass- luminosity relation and because of variations in the star formation efficiency with halo mass.
We conduct a comprehensive analysis of the relationship between central galaxies and their host dark matter halos, as characterized by the stellar mass-halo mass (SM-HM) relation, with rigorous consideration of uncertainties. Our analysis focuses on
results from the abundance matching technique, which assumes that every dark matter halo or subhalo above a specific mass threshold hosts one galaxy. We discuss the quantitative effects of uncertainties in observed galaxy stellar mass functions (GSMFs) (including stellar mass estimates and counting uncertainties), halo mass functions (including cosmology and uncertainties from substructure), and the abundance matching technique used to link galaxies to halos (including scatter in this connection). Our analysis results in a robust estimate of the SM-HM relation and its evolution from z=0 to z=4. The shape and evolution are well constrained for z < 1. The largest uncertainties at these redshifts are due to stellar mass estimates; however, failure to account for scatter in stellar masses at fixed halo mass can lead to errors of similar magnitude in the SM-HM relation for central galaxies in massive halos. We also investigate the SM-HM relation to z=4, although the shape of the relation at higher redshifts remains fairly unconstrained when uncertainties are taken into account. These results will provide a powerful tool to inform galaxy evolution models. [Abridged]
We study the impact of theoretical uncertainty in the dark matter halo mass function and halo bias on dark energy constraints from imminent galaxy cluster surveys. We find that for an optical cluster survey like the Dark Energy Survey, the accuracy r
equired on the predicted halo mass function to make it an insignificant source of error on dark energy parameters is ~ 1%. The analogous requirement on the predicted halo bias is less stringent (~ 5%), particularly if the observable-mass distribution can be well constrained by other means. These requirements depend upon survey area but are relatively insensitive to survey depth. The most stringent requirements are likely to come from a survey over a significant fraction of the sky that aims to observe clusters down to relatively low mass, Mth ~ 10^13.7 Msun/h; for such a survey, the mass function and halo bias must be predicted to accuracies of ~ 0.5% and ~ 1%, respectively. These accuracies represent a limit on the practical need to calibrate ever more accurate halo mass and bias functions. We find that improving predictions for the mass function in the low-redshift and low-mass regimes is the most effective way to improve dark energy constraints.
The precision of cosmological parameters derived from galaxy cluster surveys is limited by uncertainty in relating observable signals to cluster mass. We demonstrate that a small mass-calibration follow-up program can significantly reduce this uncert
ainty and improve parameter constraints, particularly when the follow-up targets are judiciously chosen. To this end, we apply a simulated annealing algorithm to maximize the dark energy information at fixed observational cost, and find that optimal follow-up strategies can reduce the observational cost required to achieve a specified precision by up to an order of magnitude. Considering clusters selected from optical imaging in the Dark Energy Survey, we find that approximately 200 low-redshift X-ray clusters or massive Sunyaev-Zeldovich clusters can improve the dark energy figure of merit by 50%, provided that the follow-up mass measurements involve no systematic error. In practice, the actual improvement depends on (1) the uncertainty in the systematic error in follow-up mass measurements, which needs to be controlled at the 5% level to avoid severe degradation of the results; and (2) the scatter in the optical richness-mass distribution, which needs to be made as tight as possible to improve the efficacy of follow-up observations.
