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We report evidence of galaxy assembly bias—the correlation between galaxy properties and biased secondary halo properties at fixed halo mass ( M _H )—in the stellar-to-halo mass relation for red central galaxies from the Sloan Digital Sky Survey. In the M _H = 10 ^11.5 –10 ^13.5 h ^−1 M _⊙ range, central galaxy stellar mass ( M _* ) is correlated with the number density of galaxies within 10 h ^−1 Mpc ( δ _10 ), a common proxy for halo formation time. This galaxy assembly bias signal is also present when M _H , M _* , and δ _10 are substituted with group luminosity, galaxy luminosity, and metrics of the large-scale density field. To associate differences in δ _10 with variations in halo formation time, we fitted a model that accounts for (1) errors in the M _H measured by the J. L. Tinker group catalog and (2) the level of correlation between halo formation time and M _* at fixed M _H . Fitting of this model yields that (1) errors in M _H are ∼0.15 dex and (2) halo formation time and M _* are strongly correlated (Spearman’s rank correlation coefficient ∼0.85). At fixed M _H , variations of ∼0.4 dex in M _* are associated with ∼1–3 Gyr variations in halo formation time and galaxy formation time (from stellar population fitting). These results are indicative that halo properties other than M _H can impact central galaxy assembly.

There is untapped cosmological information in galaxy redshift surveys in the nonlinear regime. In this work, we use the Aemulus suite of cosmological N -body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales (0.1–50 h ^−1 Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation function w _p ( r _p ), the redshift-space monopole of the correlation function ξ _0 ( s ), and the quadrupole ξ _2 ( s )—we emulate statistics that include information about the local environment, namely the underdensity probability function P _U ( s ) and the density-marked correlation function M ( s ). This extends the model of Aemulus III for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: including P _U ( s ) and M ( s ) improves the precision of our constraints on Ω _m by 27%, σ _8 by 19%, and the growth of structure parameter, f σ _8 , by 12% compared to standard statistics. We additionally find that scales below ∼6 h ^−1 Mpc contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy–halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.

Over the next 5 yr, the Dark Energy Spectroscopic Instrument (DESI) will use 10 spectrographs with 5000 fibers on the 4 m Mayall Telescope at Kitt Peak National Observatory to conduct the first Stage IV dark energy galaxy survey. At z < 0.6, the DESI Bright Galaxy Survey (BGS) will produce the most detailed map of the universe during the dark-energy-dominated epoch with redshifts of >10 million galaxies spanning 14,000 deg ^2 . In this work, we present and validate the final BGS target selection and survey design. From the Legacy Surveys, BGS will target an r < 19.5 mag limited sample (BGS Bright), a fainter 19.5 < r < 20.175 color-selected sample (BGS Faint), and a smaller low- z quasar sample. BGS will observe these targets using exposure times scaled to achieve homogeneous completeness and cover the footprint three times. We use observations from the Survey Validation programs conducted prior to the main survey along with simulations to show that BGS can complete its strategy and make optimal use of “bright” time. BGS targets have stellar contamination 80% fiber assignment efficiency. Finally, BGS Bright and BGS Faint will achieve >95% redshift success over any observing condition. BGS meets the requirements for an extensive range of scientific applications. BGS will yield the most precise baryon acoustic oscillation and redshift-space distortion measurements at z < 0.4. It presents opportunities for new methods that require highly complete and dense samples (e.g., N -point statistics, multitracers). BGS further provides a powerful tool to study galaxy populations and the relations between galaxies and dark matter.

We analyze clustering measurements of BOSS galaxies using a simulation-based emulator of two-point statistics. We focus on the monopole and quadrupole of the redshift-space correlation function, and the projected correlation function, at scales of 0.1 ∼ 60 h ^−1 Mpc. Although our simulations are based on w CDM with general relativity (GR), we include a scaling parameter of the halo velocity field, γ _f , defined as the amplitude of the halo velocity field relative to the GR prediction. We divide the BOSS data into three redshift bins. After marginalizing over other cosmological parameters, galaxy bias parameters, and the velocity scaling parameter, we find f σ _8 ( z = 0.25) = 0.413 ± 0.031, f σ _8 ( z = 0.4) = 0.470 ± 0.026, and f σ _8 ( z = 0.55) = 0.396 ± 0.022. Compared with Planck observations using a flat Lambda cold dark matter model, our results are lower by 1.9 σ , 0.3 σ , and 3.4 σ , respectively. These results are consistent with other recent simulation-based results at nonlinear scales, including weak lensing measurements of BOSS LOWZ galaxies, two-point clustering of eBOSS LRGs, and an independent clustering analysis of BOSS LOWZ. All these results are generally consistent with a combination of ${\gamma }_{f}^{1/2}{\sigma }_{8}\approx 0.75$ . We note, however, that the BOSS data is well fit assuming GR, i.e., γ _f = 1. We cannot rule out an unknown systematic error in the galaxy bias model at nonlinear scales, but near-future data and modeling will enhance our understanding of the galaxy–halo connection, and provide a strong test of new physics beyond the standard model.

The PRObabilistic Value-added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ( M _* ), star formation rate (SFR), stellar metallicity ( Z ), and stellar age ( t _age ), for >10 million galaxies of the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, the neural emulator for the model, and the Bayesian inference framework of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-Galaxies semi-analytic model. We compare the inferred galaxy properties to the true values of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M _* , SFR, Z , and t _age of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors, which we characterize in detail. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses. https://github.com/changhoonhahn/provabgs/

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. [ABSTRACT FROM AUTHOR]

Using the N-body simulations of the Aemulus Project, we construct an emulator for the nonlinear clustering of galaxies in real and redshift space. We construct our model of galaxy bias using the halo occupation framework, accounting for possible velocity bias. The model includes 15 parameters, including both cosmological and galaxy bias parameters. We demonstrate that our emulator achieves ∼1% precision at the scales of interest, 0.1 h−1 Mpc < r < 10 h−1 Mpc, and recovers the true cosmology when tested against independent simulations. Our primary parameters of interest are related to the growth rate of structure, f, and its degenerate combination, fσ8. Using this emulator, we show that the constraining power on these parameters monotonically increases as smaller scales are included in the analysis, all the way down to 0.1 h−1 Mpc. For a BOSS-like survey, the constraints on fσ8 from r < 30 h−1 Mpc scales alone are nearly a factor of two tighter than those from the fiducial BOSS analysis of redshift-space clustering using perturbation theory at larger scales. The combination of real- and redshift-space clustering allows us to break the degeneracy between f and σ8, yielding an 11% constraint on f alone for a BOSS-like analysis. The current Aemulus simulations limit this model to surveys of massive galaxies. Future simulations will allow this framework to be extended to all galaxy target types, including emission-line galaxies. [ABSTRACT FROM AUTHOR]

A tightly correlated star formation rate (SFR)–stellar mass relation of star-forming galaxies, or star-forming sequence (SFS), is a key feature in galaxy property-space that is predicted by modern galaxy formation models. We present a flexible data-driven approach for identifying this SFS over a wide range of SFRs and stellar masses using Gaussian mixture modeling (GMM). Using this method, we present a consistent comparison of the z = 0 SFSs of central galaxies in the Illustris, Evolution and Assembly of GaLaxies and their Environment, and Mufasa hydrodynamic simulations and the Santa Cruz semianalytic model (SC-SAM), alongside data from the Sloan Digital Sky Survey. We find, surprisingly, that the amplitude of the SFS varies by up to ∼0.7 dex (factor of ∼5) among the simulations with power-law slopes ranging from 0.7 to 1.2. In addition to the SFS, our GMM method also identifies subcomponents in the SFR–stellar mass plane corresponding to starburst, transitioning, and quiescent subpopulations. The hydrodynamic simulations are similarly dominated by SFS and quiescent subpopulations unlike the SC-SAM, which predicts substantial fractions of transitioning and starburst galaxies at stellar masses above and below , respectively. All of the simulations also produce an abundance of low mass quiescent central galaxies in apparent tension with observations. These results illustrate that, even among models that well reproduce many observables of the galaxy population, the z = 0 SFS and other subpopulations still show marked differences that can provide strong constraints on galaxy formation models. [ABSTRACT FROM AUTHOR]

Existing models for the dependence of the halo mass function on cosmological parameters will become a limiting source of systematic uncertainty for cluster cosmology in the near future. We present a halo mass function emulator and demonstrate improved accuracy relative to state-of-the-art analytic models. In this work, mass is defined using an overdensity criteria of 200 relative to the mean background density. Our emulator is constructed from the Aemulus simulations, a suite of 40 N-body simulations with snapshots from z = 3 to z = 0. These simulations cover the flat wCDM parameter space allowed by recent cosmic microwave background, baryon acoustic oscillation and SNe Ia results, varying the parameters w, Ωm, Ωb, σ8, Neff, ns, and H0. We validate our emulator using five realizations of seven different cosmologies, for a total of 35 test simulations. These test simulations were not used in constructing the emulator, and were run with fully independent initial conditions. We use our test simulations to characterize the modeling uncertainty of the emulator, and introduce a novel way of marginalizing over the associated systematic uncertainty. We confirm nonuniversality in our halo mass function emulator as a function of both cosmological parameters and redshift. Our emulator achieves better than 1% precision over much of the relevant parameter space, and we demonstrate that the systematic uncertainty in our emulator will remain a negligible source of error for cluster abundance studies through at least the LSST Year 1 data set. [ABSTRACT FROM AUTHOR]

We present the first scientific results from the luminous red galaxy (LRG) sample of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) combined with the high-redshift galaxies of the previous BOSS sample. We measure the small- and intermediate-scale clustering from a sample of more than 97,000 galaxies in the redshift range . We interpret these measurements in the framework of the Halo Occupation Distribution. The bias of this sample of LRGs is 2.30 ± 0.03, with a satellite fraction of 13% ± 3% and a mean halo mass of . These results are consistent with expectations, demonstrating that these LRGs will be reliable tracers of large-scale structure at . The galaxy bias implies a scatter of luminosity at fixed halo mass, , of 0.19 dex. Using the clustering of massive galaxies from BOSS CMASS, BOSS LOWZ, and SDSS, we find that is consistent with observations over the full redshift range that these samples cover. The addition of eBOSS to previous surveys allows the investigation of the evolution of massive galaxies over the past ∼7 Gyr. [ABSTRACT FROM AUTHOR]

Central galaxies make up the majority of the galaxy population, including the majority of the quiescent population at . Thus, the mechanism(s) responsible for quenching central galaxies play a crucial role in galaxy evolution as whole. We combine a high-resolution cosmological N-body simulation with observed evolutionary trends of the “star formation main sequence,” quiescent fraction, and stellar mass function at to construct a model that statistically tracks the star formation histories and quenching of central galaxies. Comparing this model to the distribution of central galaxy star formation rates in a group catalog of the SDSS Data Release 7, we constrain the timescales over which physical processes cease star formation in central galaxies. Over the stellar mass range we infer quenching e-folding times that span 1.5–0.5 Gyr with more massive central galaxies quenching faster. For , this implies a total migration time of from the star formation main sequence to quiescence. Compared to satellites, central galaxies take longer to quench their star formation, suggesting that different mechanisms are responsible for quenching centrals versus satellites. Finally, the central galaxy quenching timescale we infer provides key constraints for proposed star formation quenching mechanisms. Our timescale is generally consistent with gas depletion timescales predicted by quenching through strangulation. However, the exact physical mechanism(s) responsible for this remain unclear. [ABSTRACT FROM AUTHOR]

We present measurements of the clustering of galaxies as a function of their stellar mass in the Baryon Oscillation Spectroscopic Survey. We compare the clustering of samples using 12 different methods for estimating stellar mass, isolating the method that has the smallest scatter at fixed halo mass. In this test, the stellar mass estimate with the smallest errors yields the highest amplitude of clustering at fixed number density. We find that the PCA stellar masses of Chen et al. clearly have the tightest correlation with halo mass. The PCA masses use the full galaxy spectrum, differentiating them from other estimates that only use optical photometric information. Using the PCA masses, we measure the large-scale bias as a function of for galaxies with , correcting for incompleteness at the low-mass end of our measurements. Using the abundance matching ansatz to connect dark matter halo mass to stellar mass, we construct theoretical models of that match the same stellar mass function but have different amounts of scatter in stellar mass at fixed halo mass, . Using this approach, we find . This value includes both intrinsic scatter as well as random errors in the stellar masses. To partially remove the latter, we use repeated spectra to estimate statistical errors on the stellar masses, yielding an upper limit to the intrinsic scatter of 0.16 dex. [ABSTRACT FROM AUTHOR]

We present a cosmic void catalog using the large-scale structure galaxy catalog from the Baryon Oscillation Spectroscopic Survey (BOSS). This galaxy catalog is part of the Sloan Digital Sky Survey (SDSS) Data Release 12 and is the final catalog of SDSS-III. We take into account the survey boundaries, masks, and angular and radial selection functions, and apply the ZOBOV void finding algorithm to the Galaxy catalog. We identify a total of 10,643 voids. After making quality cuts to ensure that the voids represent real underdense regions, we obtain 1,228 voids with effective radii spanning the range 20–100 and with central densities that are, on average, 30% of the mean sample density. We release versions of the catalogs both with and without quality cuts. We discuss the basic statistics of voids, such as their size and redshift distributions, and measure the radial density profile of the voids via a stacking technique. In addition, we construct mock void catalogs from 1000 mock galaxy catalogs, and find that the properties of BOSS voids are in good agreement with those in the mock catalogs. We compare the stellar mass distribution of galaxies living inside and outside of the voids, and find no large difference. These BOSS and mock void catalogs are useful for a number of cosmological and galaxy environment studies. [ABSTRACT FROM AUTHOR]

We apply the Alcock–Paczyński (AP) test to stacked voids identified using the final data release (DR12) of the Baryon Oscillation Spectroscopic Survey (BOSS). We also use 1000 mock galaxy catalogs that match the geometry, density, and clustering properties of the BOSS sample in order to characterize the statistical uncertainties of our measurements and take into account systematic errors such as redshift space distortions. For both BOSS data and mock catalogs, we use the ZOBOV algorithm to identify voids, we stack together all voids with effective radii of in the redshift range of 0.43–0.7, and we accurately measure the shape of the stacked voids. Our tests with the mock catalogs show that we measure the stacked void ellipticity with a statistical precision of 2.6%. The stacked voids in redshift space are slightly squashed along the line of sight, consistent with previous studies. We repeat this measurement of stacked void shape in the BOSS data, assuming several values of within the flat model, and we compare this to the mock catalogs in redshift space to perform the AP test. We obtain a constraint of at the 68% confidence level from the AP test. We discuss the sources of statistical and systematic noise that affect the constraining power of this method. In particular, we find that the measured ellipticity of stacked voids changes more weakly with cosmology than the standard AP prediction, leading to significantly weaker constraints. We discuss how constraints will improve in future surveys with larger volumes and densities. [ABSTRACT FROM AUTHOR]