ABSTRACT
We present a method to flexibly and self-consistently determine individual galaxies’ star formation rates (SFRs) from their host haloes’ potential well depths, assembly histories, and ...redshifts. The method is constrained by galaxies’ observed stellar mass functions, SFRs (specific and cosmic), quenched fractions, ultraviolet (UV) luminosity functions, UV–stellar mass relations, IRX–UV relations, auto- and cross-correlation functions (including quenched and star-forming subsamples), and quenching dependence on environment; each observable is reproduced over the full redshift range available, up to 0 < z < 10. Key findings include the following: galaxy assembly correlates strongly with halo assembly; quenching correlates strongly with halo mass; quenched fractions at fixed halo mass decrease with increasing redshift; massive quenched galaxies reside in higher-mass haloes than star-forming galaxies at fixed galaxy mass; star-forming and quenched galaxies’ star formation histories at fixed mass differ most at z < 0.5; satellites have large scatter in quenching time-scales after infall, and have modestly higher quenched fractions than central galaxies; Planck cosmologies result in up to 0.3 dex lower stellar – halo mass ratios at early times; and, none the less, stellar mass–halo mass ratios rise at z > 5. Also presented are revised stellar mass – halo mass relations for all, quenched, star-forming, central, and satellite galaxies; the dependence of star formation histories on halo mass, stellar mass, and galaxy SSFR; quenched fractions and quenching time-scale distributions for satellites; and predictions for higher-redshift galaxy correlation functions and weak lensing surface densities. The public data release (DR1) includes the massively parallel (>105 cores) implementation (the UniverseMachine), the newly compiled and remeasured observational data, derived galaxy formation constraints, and mock catalogues including lightcones.
In our modern understanding of galaxy formation, every galaxy forms within a dark matter halo. The formation and growth of galaxies over time is connected to the growth of the halos in which they ...form. The advent of large galaxy surveys as well as high-resolution cosmological simulations has provided a new window into the statistical relationship between galaxies and halos and its evolution. Here, we define this galaxy-halo connection as the multivariate distribution of galaxy and halo properties that can be derived from observations and simulations. This galaxy-halo connection provides a key test of physical galaxy-formation models; it also plays an essential role in constraints of cosmological models using galaxy surveys and in elucidating the properties of dark matter using galaxies. We review techniques for inferring the galaxy-halo connection and the insights that have arisen from these approaches. Some things we have learned are that galaxy-formation efficiency is a strong function of halo mass; at its peak in halos around a pivot halo mass of 10
12
M
, less than 20% of the available baryons have turned into stars by the present day; the intrinsic scatter in galaxy stellar mass is small, less than 0.2 dex at a given halo mass above this pivot mass; below this pivot mass galaxy stellar mass is a strong function of halo mass; the majority of stars over cosmic time were formed in a narrow region around this pivot mass. We also highlight key open questions about how galaxies and halos are connected, including understanding the correlations with secondary properties and the connection of these properties to galaxy clustering.
Abstract
Secondary halo bias, commonly known as ‘assembly bias’, is the dependence of halo clustering on a halo property other than mass. This prediction of the Λ Cold Dark Matter cosmology is ...essential to modelling the galaxy distribution to high precision and interpreting clustering measurements. As the name suggests, different manifestations of secondary halo bias have been thought to originate from halo assembly histories. We show conclusively that this is incorrect for cluster-size haloes. We present an up-to-date summary of secondary halo biases of high-mass haloes due to various halo properties including concentration, spin, several proxies of assembly history, and subhalo properties. While concentration, spin, and the abundance and radial distribution of subhaloes exhibit significant secondary biases, properties that directly quantify halo assembly history do not. In fact, the entire assembly histories of haloes in pairs are nearly identical to those of isolated haloes. In general, a global correlation between two halo properties does not predict whether or not these two properties exhibit similar secondary biases. For example, assembly history and concentration (or subhalo abundance) are correlated for both paired and isolated haloes, but follow slightly different conditional distributions in these two cases. This results in a secondary halo bias due to concentration (or subhalo abundance), despite the lack of assembly bias in the strict sense for cluster-size haloes. Due to this complexity, caution must be exercised in using any one halo property as a proxy to study the secondary bias due to another property.
We present a robust-method to constrain average galaxy star formation rates (SFRs), star formation histories (SFHs), and the intracluster light (ICL) as a function of halo mass. Our results are ...consistent with observed galaxy stellar mass functions, specific star formation rates (SSFRs), and cosmic star formation rates (CSFRs) from z = 0 to z = 8. We consider the effects of a wide range of uncertainties on our results, including those affecting stellar masses, SFRs, and the halo mass function at the heart of our analysis. Our approach places a wide variety of observations relating to the SFH of galaxies into a self-consistent framework based on the modern understanding of structure formation in LambdaCDM. Constraints on the stellar mass-halo mass relationship and SFRs are available for download online.
Abstract
We perform a measurement of the mass–richness relation of the redMaPPer galaxy cluster catalogue using weak lensing data from the Sloan Digital Sky Survey (SDSS). We have carefully ...characterized a broad range of systematic uncertainties, including shear calibration errors, photo-z biases, dilution by member galaxies, source obscuration, magnification bias, incorrect assumptions about cluster mass profiles, cluster centring, halo triaxiality and projection effects. We also compare measurements of the lensing signal from two independently produced shear and photometric redshift catalogues to characterize systematic errors in the lensing signal itself. Using a sample of 5570 clusters from 0.1 ≤ z ≤ 0.33, the normalization of our power-law mass versus λ relation is log10M
200m
/h
−1 M⊙ = 14.344 ± 0.021 (statistical) ±0.023 (systematic) at a richness λ = 40, a 7 per cent calibration uncertainty, with a power-law index of
$1.33^{+0.09}_{-0.10}$
(1σ). The detailed systematics characterization in this work renders it the definitive weak lensing mass calibration for SDSS redMaPPer clusters at this time.
A simple, observationally motivated model is presented for understanding how halo masses, galaxy stellar masses, and star formation rates are related, and how these relations evolve with time. The ...relation between halo mass and galaxy stellar mass is determined by matching the observed spatial abundance of galaxies to the expected spatial abundance of halos at multiple epochs, i.e., more massive galaxies are assigned to more massive halos at each epoch. This 'abundance matching' technique has been shown previously to reproduce the observed luminosity and scale dependence of galaxy clustering over a range of epochs. Halos at different epochs are connected by halo mass accretion histories estimated from N-body simulations. The halo-galaxy connection at fixed epochs in conjunction with the connection between halos across time provides a connection between observed galaxies across time. With approximations for the impact of merging and accretion on the growth of galaxies, one can then directly infer the star formation histories of galaxies as a function of stellar and halo mass. This model is tuned to match both the observed evolution of the stellar mass function and the normalization of the observed star formation rate (SFR)-stellar mass relation to z ~ 1. The data demands, for example, that the star formation rate density is dominated by galaxies with M star 1010.0-10.5 M from 0 < z < 1, and that such galaxies over these epochs reside in halos with M vir 1011.5-12.5 M . The SFR-halo mass relation is approximately Gaussian over the range 0 < z < 1 with a mildly evolving mean and normalization. This model is then used to shed light on a number of issues, including (1) a clarification of 'downsizing', (2) the lack of a sharp characteristic halo mass at which star formation is truncated, and (3) the dominance of star formation over merging to the stellar buildup of galaxies with M star 1011 M at z < 1.
ABSTRACT
We present a novel simulation-based hybrid emulator approach that maximally derives cosmological and Halo Occupation Distribution (HOD) information from non-linear galaxy clustering, with ...sufficient precision for DESI Year 1 (Y1) analysis. Our hybrid approach first samples the HOD space on a fixed cosmological simulation grid to constrain the high-likelihood region of cosmology + HOD parameter space, and then constructs the emulator within this constrained region. This approach significantly reduces the parameter volume emulated over, thus achieving much smaller emulator errors with fixed number of training points. We demonstrate that this combined with state-of-the-art simulations result in tight emulator errors comparable to expected DESI Y1 LRG sample variance. We leverage the new abacussummit simulations and apply our hybrid approach to CMASS non-linear galaxy clustering data. We infer constraints on σ8 = 0.762 ± 0.024 and fσ8(zeff = 0.52) = 0.444 ± 0.016, the tightest among contemporary galaxy clustering studies. We also demonstrate that our fσ8 constraint is robust against secondary biases and other HOD model choices, a critical first step towards showcasing the robust cosmology information accessible in non-linear scales. We speculate that the additional statistical power of DESI Y1 should tighten the growth rate constraints by at least another 50–60 ${{\ \rm per\ cent}}$, significantly elucidating any potential tension with Planck. We also address the ‘lensing is low’ tension, which we find to be in the same direction as a potential tension in fσ8. We show that the combined effect of a lower fσ8 and environment-based bias accounts for approximately $50{{\ \rm per\ cent}}$ of the discrepancy.
ABSTRACT 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 that 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.
The rapidly growing statistical precision of galaxy surveys has led to a need for ever more precise predictions of the observables used to constrain cosmological and galaxy formation models. The ...primary avenue through which such predictions will be obtained is suites of numerical simulations. These simulations must span the relevant model parameter spaces, be large enough to obtain the precision demanded by upcoming data, and be thoroughly validated in order to ensure accuracy. In this paper, we present one such suite of simulations, forming the basis for the Aemulus Project, a collaboration devoted to precision emulation of galaxy survey observables. We have run a set of 75 (1.05 h−1 Gpc)3 simulations with mass resolution and force softening of and 20 h−1 kpc, respectively, in 47 different wCDM cosmologies spanning the range of parameter space allowed by the combination of recent cosmic microwave background, baryon acoustic oscillation, and Type Ia supernova results. We present convergence tests of several observables including spherical overdensity halo mass functions, galaxy projected correlation functions, galaxy clustering in redshift space, and matter and halo correlation functions and power spectra. We show that these statistics are converged to 1% (2%) or to the sample variance of the statistic, whichever is larger, for halos with more than 500 (200) particles, respectively, and scales of r > 200 h−1 kpc in real space or k ∼ 3 h Mpc−1 in harmonic space for z ≤ 1. We find that the dominant source of uncertainty comes from varying the particle loading of the simulations. This leads to large systematic errors for statistics using halos with fewer than 200 particles and scales smaller than k ∼ 4 h Mpc−1. We provide the halo catalogs and snapshots detailed in this work to the community at https://AemulusProject.github.io.
The Tully–Fisher relation (TFR) expresses the connection between rotating galaxies and the dark matter haloes they inhabit, and therefore contains a wealth of information about galaxy formation. We ...construct a general framework to investigate whether models based on halo abundance matching are able to reproduce the observed stellar mass TFR and mass–size relation (MSR), and use the data to constrain galaxy formation parameters. Our model tests a range of plausible scenarios, differing in the response of haloes to disc formation, the relative angular momentum of baryons and dark matter, the impact of selection effects, and the abundance matching parameters. We show that agreement with the observed TFR puts an upper limit on the scatter between galaxy and halo properties, requires weak or reversed halo contraction, and favours selection effects that preferentially eliminate fast-rotating galaxies. The MSR constrains the ratio of the disc to halo specific angular momentum to be approximately in the range 0.6–1.2. We identify and quantify two problems that models of this nature face. (1) They predict too large an intrinsic scatter for the MSR, and (2) they predict too strong an anticorrelation between the TFR and MSR residuals. We argue that resolving these problems requires introducing a correlation between stellar surface density and enclosed dark matter mass. Finally, we explore the expected difference between the TFRs of central and satellite galaxies, finding that in the favoured models this difference should be detectable in a sample of ∼700 galaxies.
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