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At least 127 records · Page 7

Covariance matrices for variance-suppressed simulations

ABSTRACT Cosmological N-body simulations provide numerical predictions of the structure of the Universe against which to compare data from ongoing and future surveys, but the growing volume of the Universe mapped by surveys requires correspondingly lower statistical uncertainties in simulations, usually achieved by increasing simulation sizes at the expense of computational power. It was recently proposed to reduce simulation variance without incurring additional computational costs by adopting fixed-amplitude initial conditions. This method has been demonstrated not to introduce bias in various statistics, including the two-point statistics of galaxy samples typically used for extracting cosmological parameters from galaxy redshift survey data, but requires us to revisit current methods for estimating covariance matrices of clustering statistics for simulations. In this work, we find that it is not trivial to construct covariance matrices analytically for fixed-amplitude simulations, but we demonstrate that ezmock (Effective Zel’dovich approximation mock catalogue), the most efficient method for constructing mock catalogues with accurate two- and three-point statistics, provides reasonable covariance matrix estimates for such simulations. We further examine how the variance suppression obtained by amplitude-fixing depends on three-point clustering, small-scale clustering, and galaxy bias, and propose intuitive explanations for the effects we observe based on the ezmock bias model.

79 ASTRONOMY AND ASTROPHYSICS↗

Smallest remnants of early matter domination

The evolution of the universe prior to Big Bang Nucleosynthesis could have gone through a phase of early matter domination which enhanced the growth of small-scale dark matter structure. If this period was long enough, self-gravitating objects formed prior to reheating. Here, we study the evolution of these dense early halos through reheating. At the end of early matter domination, the early halos undergo rapid expansion and eventually eject their matter. We find that this process washes out structure on scales much larger than naively expected from the size of the original halos. We compute the density profiles of the early halo remnants and use them to construct late-time power spectra that include these non-linear effects. We evolve the resulting power spectrum to estimate the properties of microhalos that would form after matter-radiation equality. Surprisingly, cosmologies with a short period of early matter domination lead to an earlier onset of microhalo formation compared to those with a long period. In either case, dark matter structure formation begins much earlier than in the standard cosmology, with most dark matter bound in microhalos in the late universe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Constraining Galaxy-Halo connection using machine learning

We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical fits, they often yield likelihood contours that are significantly biased in both mean values and variances relative to the true model parameters. This highlights the importance of careful data processing and algorithm selection in ML applications for galaxy clustering, as even seemingly robust methods can lead to biased results if not applied correctly. ML tools offer a promising approach to exploring the HOD parameter space with significantly reduced computational costs compared to traditional brute-force methods if their robustness is established. Using our ANN-based pipeline, we successfully recreate some standard results from recent literature. Properly restricting the HOD parameter space, transforming the training data, and carefully selecting ML algorithms are essential for achieving unbiased and robust predictions. Among the methods tested, artificial neural networks (ANNs) outperform random forests (RF) and ridge regression in predicting clustering statistics, when the HOD prior space is appropriately restricted. We demonstrate these findings using the projected two-point correlation function (w p (r p )), angular multipoles of the correlation function (ξ ℓ (r)), and the void probability function (VPF) of Luminous Red Galaxies from Dark Energy Spectroscopic Instrument mocks. Our results show that while combining w p (r p ) and VPF improves parameter constraints, adding the multipoles ξ 0 , ξ 2 , and ξ 4 to w p (r p ) does not significantly improve the constraints.

cosmology↗

Massive star-forming galaxies have converted most of their halo gas into stars

In the local Universe, the efficiency for converting baryonic gas into stars is very low. In dark matter halos where galaxies form and evolve, the average efficiency varies with galaxy stellar mass and has a maximum of about 20% for Milky-Way-like galaxies. The low efficiency at higher mass is believed to be the result of some quenching processes, such as the feedback from active galactic nuclei. We perform an analysis of weak lensing and satellite kinematics for SDSS central galaxies. Our results reveal that the efficiency is much higher, more than 60%, for a large population of massive star-forming galaxies around 10 11 M ⊙ . This suggests that these galaxies acquired most of the gas in their halos and converted it into stars without being significantly affected by quenching processes. This population of galaxies is not reproduced in current galaxy formation models, indicating that our understanding of galaxy formation is incomplete. The implications of our results on circumgalactic media, star-formation quenching, and disk galaxy rotation curves are discussed. We also examine systematic uncertainties in halo-mass and stellar-mass measurements that might influence our results.

79 ASTRONOMY AND ASTROPHYSICS↗

The DESI One-Percent Survey: Modelling the clustering and halo occupation of all four DESI tracers with U CHUU

We present results from a set of mock lightcones for the DESI One-Percent Survey, created from the UCHUU simulation. This 8 h −3 Gpc 3 N-body simulation comprises 2.1 trillion particles and provides high-resolution dark matter (sub)haloes in the framework of the Planck-based ΛCDM cosmology. Employing the subhalo abundance matching (SHAM) technique, we populated the UCHUU (sub)haloes with all four DESI tracers – Bright Galaxy Survey (BGS), luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars (QSOs) – to z = 2.1. Our method accounts for redshift evolution as well as the clustering dependence on luminosity and stellar mass. The two-point clustering statistics of the DESI One-Percent Survey generally agree with predictions from UCHUU across scales ranging from 0.3 h −1 Mpc to 100 h −1 Mpc for the BGS and across scales ranging from 5 h −1 Mpc to 100 h −1 Mpc for the other tracers. We observed some differences in clustering statistics that can be attributed to incompleteness of the massive end of the stellar mass function of LRGs, our use of a simplified galaxy-halo connection model for ELGs and QSOs, and cosmic variance. We find that at the high precision of UCHUU, the shape of the halo occupation distribution (HOD) of the BGS and LRG samples is smaller bias values, likely due to cosmic variance. The bias dependence on absolute magnitude, stellar mass, and redshift aligns with that of previous surveys. These results provide DESI with tools to generate high-fidelity lightcones for the remainder of the survey and enhance our understanding of the galaxy-halo connection.

cosmology↗

Simulations and symmetries

ABSTRACT We investigate the range of applicability of a model for the real-space power spectrum based on N-body dynamics and a (quadratic) Lagrangian bias expansion. This combination uses the highly accurate particle displacements that can be efficiently achieved by modern N-body methods with a symmetries-based bias expansion which describes the clustering of any tracer on large scales. We show that at low redshifts, and for moderately biased tracers, the substitution of N-body-determined dynamics improves over an equivalent model using perturbation theory by more than a factor of two in scale, while at high redshifts and for highly biased tracers the gains are more modest. This hybrid approach lends itself well to emulation. By removing the need to identify haloes and subhaloes, and by not requiring any galaxy-formation-related parameters to be included, the emulation task is significantly simplified at the cost of modelling a more limited range in scale.

79 ASTRONOMY AND ASTROPHYSICS↗

Limitations to the ‘basic’ HOD model and beyond

ABSTRACT We use the IllustrisTNG cosmological, hydrodynamical simulations to test fundamental assumptions of the mass-based halo occupation distribution (HOD) approach to modelling the galaxy–halo connection. By comparing the clustering of galaxies measured in the 300 Mpc TNG box (TNG300) with that predicted by the standard (basic) HOD model, we find that, on average, the ‘basic’ HOD model underpredicts the real-space correlation function in the TNG300 box by ∼15 per cent on scales of $1 \,\,\lt\,\, r \,\,\lt\,\, 20 \ {\rm Mpc}\, h^{-1}$, which is well beyond the target precision demanded of next-generation galaxy redshift surveys. We perform several tests to establish the robustness of our findings to systematic effects, including the effect of finite box size and the choice of halo finder. In our exploration of ‘secondary’ parameters with which to augment the ‘basic’ HOD, we find that the local environment of the halo, the velocity dispersion anisotropy, β, and the product of the half-mass radius and the velocity dispersion, σ2Rhalfmass, are the three most effective measures of assembly bias that help reconcile the ‘basic’ HOD-predicted clustering with that in TNG300. In addition, we test other halo properties such as halo spin, formation epoch, and halo concentration. We also find that at fixed halo mass, galaxies in one type of environment cluster differently from galaxies in another. We demonstrate that a more complete model of the galaxy–halo connection can be constructed if we combine both mass and local environment information about the halo.

42 ENGINEERING↗

The galaxy–halo connection of emission-line galaxies in IllustrisTNG

ABSTRACT We employ the hydrodynamical simulation IllustrisTNG-300-1 to explore the halo occupation distribution (HOD) and environmental dependence of luminous star-forming emission-line galaxies (ELGs) at z ∼ 1. Such galaxies are key targets for current and upcoming cosmological surveys. We select model galaxies through cuts in colour–colour space allowing for a direct comparison with the Extended Baryon Oscillation Spectroscopic Survey and the Dark Energy Spectroscopic Instrument (DESI) surveys and then compare them with galaxies selected based on specific star formation rate (sSFR) and stellar mass. We demonstrate that the ELG populations are twice more likely to reside in lower density regions (sheets) compared with the mass-selected populations and twice less likely to occupy the densest regions of the cosmic web (knots). We also show that the colour-selected and sSFR-selected ELGs exhibit very similar occupation and clustering statistics, finding that the agreement is best for lower redshifts. In contrast with the mass-selected sample, the occupation of haloes by a central ELG peaks at ∼20 per cent. We furthermore explore the dependence of the HOD and the autocorrelation on environment, noticing that at fixed halo mass, galaxies in high-density regions cluster about 10 times more strongly than low-density ones. This result suggests that we should model carefully the galaxy–halo relation and implement assembly bias effects into our models (estimated at ∼4 per cent of the clustering of the DESI colour-selected sample at z = 0.8). Finally, we apply a simple mock recipe to recover the clustering on large scales (r ≳ 1 Mpc h−1) to within 1 per cent by augmenting the HOD model with an environment dependence, demonstrating the power of adopting flexible population models.

79 ASTRONOMY AND ASTROPHYSICS↗

The COMBS Survey – III. The chemodynamical origins of metal-poor bulge stars

The characteristics of the stellar populations in the Galactic bulge inform and constrain the Milky Way’s formation and evolution. The metal-poor population is particularly important in light of cosmological simulations, which predict that some of the oldest stars in the Galaxy now reside in its centre. The metal-poor bulge appears to consist of multiple stellar populations that require dynamical analyses to disentangle. In this work, we undertake a detailed chemodynamical study of the metal-poor stars in the inner Galaxy. Using R ~ 20000 VLT/GIRAFFE spectra of 319 metal-poor (-2.55 dex ≤ [Fe/H] ≤ 0.83 dex, with $\overline{[Fe/H]}$ = -0.84 dex) stars, we perform stellar parameter analysis and report 12 elemental abundances (C, Na, Mg, Al, Si, Ca, Sc, Ti, Cr, Mn, Zn, Ba, and Ce) with precisions of ≈0.10 dex. Based on kinematic and spatial properties, we categorize the stars into four groups, associated with the following Galactic structures: the inner bulge, the outer bulge, the halo, and the disc. We find evidence that the inner and outer bulge population is more chemically complex (i.e. higher chemical dimensionality and less correlated abundances) than the halo population. This result suggests that the older bulge population was enriched by a larger diversity of nucleosynthetic events. We also find one inner bulge star with a [Ca/Mg] ratio consistent with theoretical pair-instability supernova yields and two stars that have chemistry consistent with globular cluster stars.

79 ASTRONOMY AND ASTROPHYSICS↗

COMPASO : A new halo finder for competitive assignment to spherical overdensities

We describe a new method (compaso) for identifying groups of particles in cosmological N-body simulations. compaso builds upon existing spherical overdensity (SO) algorithms by taking into consideration the tidal radius around a smaller halo before competitively assigning halo membership to the particles. In this way, the compaso finder allows for more effective deblending of haloes in close proximity as well as the formation of new haloes on the outskirts of larger ones. This halo-finding algorithm is used in the abacussummit suite of N-body simulations, designed to meet the cosmological simulation requirements of the Dark Energy Spectroscopic Instrument (DESI) survey. compaso is developed as a highly efficient on-the-fly group finder, which is crucial for enabling good load-balancing between the GPU and CPU and the creation of high-resolution merger trees. In this paper, we describe the halo-finding procedure and its particular implementation in abacus, accompanying it with a qualitative analysis of the finder. We test the robustness of the compaso catalogues before and after applying the cleaning method described in an accompanying paper and demonstrate its effectiveness by comparing it with other validation techniques. We then visualize the haloes and their density profiles, finding that they are well fit by the NFW formalism. Finally, we compare other properties such as radius–mass relationships and two-point correlation functions with that of another widely used halo finder, rockstar.

79 ASTRONOMY AND ASTROPHYSICS↗

The halo light-cone catalogues of ABACUSSUMMIT

We describe a method for generating halo catalogues on the light-cone using the AbacusSummit suite of N-body simulations. The main application of these catalogues is the construction of realistic mock galaxy catalogues and weak lensing maps on the sky. Our algorithm associates the haloes from a set of coarsely spaced snapshots with their positions at the time of light-cone crossing by matching halo particles to on-the-fly light-cone particles. It then records the halo and particle information into an easily accessible product, which we call the AbacusSummit halo light-cone catalogues. Our recommended use of this product is in the halo mass regime of M halo > 2.1 x 10 11 M ⊙ h -1 for the base resolution simulations, i.e. haloes containing at least 100 particles, where the interpolated halo properties are most reliable. To test the validity of the obtained catalogues, we perform various visual inspections and consistency checks. In particular, we construct galaxy mock catalogues of emission-line galaxies (ELGs) at z ~ 1 by adopting a modified version of the AbacusHOD script, which builds on the standard halo occupation distribution (HOD) method by including various extensions. We find that the multipoles of the autocorrelation function are consistent with the predictions from the full-box snapshot, implicitly validating our algorithm. In addition, we compute and output CMB convergence maps and find that the auto- and cross-power spectrum agrees with the theoretical prediction at the sub-per-cent level.

79 ASTRONOMY AND ASTROPHYSICS↗

First measurement of the characteristic depletion radius of dark matter haloes from weak lensing

ABSTRACT We use weak lensing observations to make the first measurement of the characteristic depletion radius, one of the three radii that characterize the region where matter is being depleted by growing haloes. The lenses are taken from the halo catalogue produced by the extended halo-based group/cluster finder applied to DESI Legacy Imaging Surveys DR9, while the sources are extracted from the DECaLS DR8 imaging data with the fourier_quad pipeline. We study halo masses $12 \lt \log (M_{\rm grp} \,[{\rm M_{\odot }}\, h^{-1}]) \le 15.3$ within redshifts 0.2 ≤ z ≤ 0.3. The virial and splashback radii are also measured and used to test the original findings on the depletion region. When binning haloes by mass, we find consistency between most of our measurements and predictions from the cosmicgrowth simulation, with exceptions to the lowest mass bins. The characteristic depletion radius is found to be roughly 2.5 times the virial radius and 1.7–3 times the splashback radius, in line with an approximately universal outer density profile, and the average enclosed density within the characteristic depletion radius is found to be roughly 29 times the mean matter density of the Universe in our sample. When binning haloes by both mass and a proxy for halo concentration, we do not detect a significant variation of the depletion radius with concentration, on which the simulation prediction is also sensitive to the choice of concentration proxy. We also confirm that the measured splashback radius varies with concentration differently from simulation predictions.

79 ASTRONOMY AND ASTROPHYSICS↗

The DESI N -body Simulation Project – II. Suppressing sample variance with fast simulations

ABSTRACT Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim 20\, h^{-3}\, \mathrm{Gpc}^{3}$. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with $200\, h^{-3}\, \mathrm{Gpc}^{3}$ (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi-N-body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. $k \lt 0.3\, h\, \mathrm{Mpc}^{-1}$ for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data.

cosmology: theory↗

Stringent σ8 constraints from small-scale galaxy clustering using a hybrid MCMC + emulator framework

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.

79 ASTRONOMY AND ASTROPHYSICS↗

Insights into the origin of halo mass profiles from machine learning

ABSTRACT The mass distribution of dark matter haloes is the result of the hierarchical growth of initial density perturbations through mass accretion and mergers. We use an interpretable machine-learning framework to provide physical insights into the origin of the spherically-averaged mass profile of dark matter haloes. We train a gradient-boosted-trees algorithm to predict the final mass profiles of cluster-sized haloes, and measure the importance of the different inputs provided to the algorithm. We find two primary scales in the initial conditions (ICs) that impact the final mass profile: the density at approximately the scale of the haloes’ Lagrangian patch RL ($R\sim 0.7\, R_L$) and that in the large-scale environment (R ∼ 1.7 RL). The model also identifies three primary time-scales in the halo assembly history that affect the final profile: (i) the formation time of the virialized, collapsed material inside the halo, (ii) the dynamical time, which captures the dynamically unrelaxed, infalling component of the halo over its first orbit, (iii) a third, most recent time-scale, which captures the impact on the outer profile of recent massive merger events. While the inner profile retains memory of the ICs, this information alone is insufficient to yield accurate predictions for the outer profile. As we add information about the haloes’ mass accretion history, we find a significant improvement in the predicted profiles at all radii. Our machine-learning framework provides novel insights into the role of the ICs and the mass assembly history in determining the final mass profile of cluster-sized haloes.

79 ASTRONOMY AND ASTROPHYSICS↗

The DESI N -body simulation project – I. Testing the robustness of simulations for the DESI dark time survey

ABSTRACT Analysis of large galaxy surveys requires confidence in the robustness of numerical simulation methods. The simulations are used to construct mock galaxy catalogues to validate data analysis pipelines and identify potential systematics. We compare three N-body simulation codes, abacus, gadget-2, and swift, to investigate the regimes in which their results agree. We run N-body simulations at three different mass resolutions, 6.25 × 108, 2.11 × 109, and 5.00 × 109 h−1 M⊙, matching phases to reduce the noise within the comparisons. We find systematic errors in the halo clustering between different codes are smaller than the Dark Energy Spectroscopic Instrument (DESI) statistical error for $s\ \gt\ 20\ h^{-1}$ Mpc in the correlation function in redshift space. Through the resolution comparison we find that simulations run with a mass resolution of 2.1 × 109 h−1 M⊙ are sufficiently converged for systematic effects in the halo clustering to be smaller than the DESI statistical error at scales larger than $20\ h^{-1}$ Mpc. These findings show that the simulations are robust for extracting cosmological information from large scales which is the key goal of the DESI survey. Comparing matter power spectra, we find the codes agree to within 1 per cent for k ≤ 10 h Mpc−1. We also run a comparison of three initial condition generation codes and find good agreement. In addition, we include a quasi-N-body code, FastPM, since we plan use it for certain DESI analyses. The impact of the halo definition and galaxy–halo relation will be presented in a follow-up study.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraining galaxy–halo connection with high-order statistics

ABSTRACT We investigate using three-point statistics in constraining the galaxy–halo connection. We show that for some galaxy samples, the constraints on the halo occupation distribution parameters are dominated by the three-point function signal (over its two-point counterpart). We demonstrate this on mock catalogues corresponding to the Luminous red galaxies (LRGs), Emission-line galaxies (ELGs), and quasars (QSOs) targeted by the Dark Energy Spectroscopic Instrument (DESI) Survey. The projected three-point function for triangle sides less up to 20 h−1 Mpc measured from a cubic Gpc of data can constrain the characteristic minimum mass of the LRGs with a preci sion of 0.46 per cent. For comparison, similar constraints from the projected two-point function are 1.55 per cent. The improvements for the ELGs and QSOs targets are more modest. In the case of the QSOs, it is caused by the high shot-noise of the sample, and in the case of the ELGs, it is caused by the range of halo masses of the host haloes. The most time-consuming part of our pipeline is the measurement of the three-point functions. We adopt a tabulation method, proposed in earlier works for the two-point function, to significantly reduce the required compute time for the three-point analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Model BOSS and eBOSS luminous red galaxies at 0.2< z<1.0 using SubHalo Abundance Matching with three parameters

SubHalo Abundance Matching (SHAM) is an empirical method for constructing galaxy catalogues based on high-resolution N-body simulations. Here, we apply SHAM on the UNIT simulation to simulate SDSS BOSS/eBOSS luminous red galaxies (LRGs) within a wide redshift range of 0.2 < $z$ < 1.0. Besides the typical SHAM scatter parameter σ, we include $v$ smear and V ceil to take into account the redshift uncertainty and the galaxy incompleteness, respectively. These two additional parameters are critical for reproducing the observed 2PCF multipoles on 5–25$\, h^{-1}\, {\rm Mpc}$. The redshift uncertainties obtained from the best-fitting $v$ smear agree with those measured from repeat observations for all SDSS LRGs except for the LOWZ sample. We explore several potential systematics but none of them can explain the discrepancy found in LOWZ. Our explanation is that the LOWZ galaxies might contain another type of galaxies that needs to be treated differently. The evolution of the measured σ and Vceil also reveals that the incompleteness of eBOSS galaxies decreases with the redshift. This is the consequence of the magnitude lower limit applied in eBOSS LRG target selection. Our SHAM also set upper limits for the intrinsic scatter of the galaxy–halo relation, given a complete galaxy sample: σ int < 0.31 for LOWZ at 0.2 < $z$ < 0.33, σ int < 0.36 for LOWZ at 0.33 < $z$ < 0.43, and σ int < 0.46 for CMASS at 0.43 < $z$ < 0.51. The projected 2PCFs of our SHAM galaxies also agree with the observational ones on the 2PCF fitting range.

79 ASTRONOMY AND ASTROPHYSICS↗