Halo Occupation Distribution Model Research Articles

Characterizing ultra-high-redshift dark matter halo demographics and assembly histories with the gureft simulations

ABSTRACT Dark matter halo demographics and assembly histories are a manifestation of cosmological structure formation and have profound implications for the formation and evolution of galaxies. In particular, merger trees provide fundamental input for several modelling techniques, such as semi-analytic models (SAMs), sub-halo abundance matching (SHAM), and decorated halo occupation distribution models. Motivated by the new ultra-high-redshift (z ≳ 10) frontier enabled by JWST, we present a new suite of Gadget at Ultrahigh Redshift with Extra-Fine Timesteps (gureft) dark matter-only cosmological simulations that are carefully designed to capture halo merger histories and structural properties in the ultra-z universe. The simulation suite consists of four 10243-particle simulations with box sizes of 5, 15, 35, and 90 Mpc h−1, each with 170 snapshots stored between 40 ≥ z ≥ 6. With the unprecedented number of available snapshots and strategically chosen dynamic range covered by these boxes, gureft uncovers the emerging dark matter halo populations and their assembly histories in the earliest epochs of cosmic history. In this work, we present the halo mass functions (HMF) between z ∼ 20 and 6 down to log (Mvir/M⊙) ∼ 5, and show that at high redshift, these robust HMFs can differ substantially from commonly used analytic approximations or older fitting functions in the literature. We also present key physical properties of the ultra-high z halo population, such as concentration and spin, as well as their mass growth and merger rates, and again provide updated fitting functions.

The star formation, dust, and abundance of galaxies with unWISE-CIB cross-correlations

The cosmic infrared background (CIB) is the accumulated infrared (IR) radiation mainly from interstellar dust heated up by early stars. In this work, we measure the cross-correlation between galaxies from the unWISE catalog and the CIB maps from the Planck satellite to simultaneously constrain the cosmic star formation rate (SFR), dust spectral energy distribution (SED), and the halo occupation distribution (HOD). The unWISE galaxy catalog is divided into three tomographic bins centered at z ∼ 0.6, 1.1, 1.5, and the CIB maps are at 353, 545, and 857 GHz. We measure the cross-correlations between these galaxy samples and CIB maps and get a 194σ signal within an angular scale 100<ℓ<2000, from which we constrain two CIB halo models from previous literature and one new model. The SFR, SED, and HOD model parameters are constrained consistently among the three models. Specifically, the dust temperature at z = 0 is constrained T 0 = 21.14+1.02 -1.34 K, which is slightly lower than T 0 = 24.4±1.9 K measured by the Planck collaboration. The halo mass that gives the most efficient star formation is around 1011.79+0.73 -0.86 M ⊙. From the model parameters, combined with the SFR density at z = 0 synthesized from multi-wavelength observations, we break the degeneracy between SED and SFR and recover the cosmic star formation history that is consistent with multi-wavelength surveys. We also constrain the graybody SED model in agreement with previous measurements from infrared flux stacking. From the HOD constraints, we derive an increasing trend of galaxy linear bias along redshifts that agrees with the results from cross- and auto-correlation with unWISE galaxies. This study indicates the power of using CIB-galaxy cross-correlation to study star formation, dust, and abundance of galaxies across cosmic time.

Halo Asymmetry in the Modeling of Galaxy Clustering

Conventional studies of galaxy clustering within the framework of halo models typically assume that the density profile of all dark matter halos can be approximated by the Navarro–Frenk–White (NFW) spherically symmetric profile. However, both modern N-body simulations and observational data suggest that most halos are either oblate or prolate, and almost never spherical. In this paper we present a modified model of the galaxy correlation function. In addition to the five “classical” halo occupation distribution (HOD) parameters proposed by Zheng et al., it includes an additional free parameter ϕ in the modified NFW density profile describing the asymmetry of the host dark matter halo. Using a subhalo abundance matching model, we populate galaxies within BolshoiP N-body simulations. We compute the projected two-point correlation function w p (r p ) for six stellar-mass volume-limited galaxy samples. We fit our model to the results and then compare the best-fit asymmetry parameter ϕ (and other halo parameters) to the asymmetry of dark matter halos measured directly from the simulations and find that they agree within 1σ. We then fit our model to the w p (r p ) results from Zehavi et al. and compare halo parameters. We show that our model accurately retrieves the halo asymmetry and other halo parameters. Additionally, we find 2%–6% differences between the halo masses ( logMmin and logM 1) estimated by our model and those estimated by “classical” HOD models. The model proposed in this paper can serve as an alternative to multiparameter HOD models, since it can be used for relatively small samples of galaxies.

The DESI one-per cent survey: exploring the halo occupation distribution of luminous red galaxies and quasi-stellar objects with AbacusSummit

ABSTRACT We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 &amp;lt; r &amp;lt; 32 h−1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 &amp;lt; z &amp;lt; 0.6, we infer a satellite fraction of $f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$, a mean halo mass of $\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$, and a linear bias of $b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$. For LRGs in 0.6 &amp;lt; z &amp;lt; 0.8, we find $f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$, $\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$, and $b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$. For QSOs, we infer $f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$, $\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$, and $b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$ in redshift range 0.8 &amp;lt; z &amp;lt; 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction.

An improved halo occupation distribution prescription from UNITsim Hα emission-line galaxies: conformity and modified radial profile

ABSTRACT Emission-line galaxies (ELGs) are targeted by the new generation of spectroscopic surveys to make unprecedented measurements in cosmology from their distribution. Accurately interpreting these data require understanding the imprints imposed by the physics of galaxy formation and evolution on galaxy clustering. In this work, we utilize a semi-analytical model of galaxy formation (sage) to explore the necessary components for accurately reproducing the clustering of ELGs. We focus on developing a halo occupation distribution (HOD) prescription able to reproduce the clustering of sage galaxies. Typically, HOD models assume that satellite and central galaxies of a given type are independent events. We investigate the need for conformity, i.e. whether the average satellite occupation depends on the existence of a central galaxy of a given type. Incorporating conformity into HOD models is crucial for reproducing the clustering in the reference galaxy sample. Another aspect we investigate is the radial distribution of satellite galaxies within haloes. The traditional density profile models, Navarro–Frenk–White (NFW) and Einasto profiles, fail to accurately replicate the small-scale clustering measured for sage satellite galaxies. To overcome this limitation, we propose a generalization of the NFW profile, thereby enhancing our understanding of galaxy clustering.

A new test of gravity – I. Introduction to the method

ABSTRACT We introduce a new scheme based on the marked correlation function to probe gravity using the large-scale structure of the Universe. We illustrate our approach by applying it to simulations of the metric-variation f(R) modified gravity theory and general relativity (GR). The modifications to the equations in f(R) gravity lead to changes in the environment of large-scale structures that could, in principle, be used to distinguish this model from GR. Applying the Monte Carlo Markov Chain algorithm, we use the observed number density and two-point clustering to fix the halo occupation distribution (HOD) model parameters and build mock galaxy catalogues from both simulations. To generate a mark for galaxies when computing the marked correlation function we estimate the local density using a Voronoi tessellation. Our approach allows us to isolate the contribution to the uncertainty in the predicted marked correlation function that arises from the range of viable HOD model parameters, in addition to the sample variance error for a single set of HOD parameters. This is critical for assessing the discriminatory power of the method. In a companion paper, we apply our new scheme to a current large-scale structure survey.

Mock observatory: Two thousand light-cone mock catalogues of luminous red galaxies from the Hyper Suprime-Cam Survey for the cosmological large-scale analysis

ABSTRACT Estimating a reliable covariance matrix for correlation functions of galaxies is a crucial task to obtain accurate cosmological constraints from galaxy surveys. We generate 2000 independent light-cone mock luminous red galaxy (LRGs) catalogues at 0.3 ≤ z ≤ 1.25, designed to cover CAMIRA LRGs observed by the Subaru Hyper Suprime-Cam Subaru Strategic Programme (HSC SSP). We first produce full-sky light-cone halo catalogues using a COmoving Lagrangian Acceleration (COLA) technique, and then trim them to match the footprints of the HSC SSP S20A Wide layers. The mock LRGs are subsequently populated on to the trimmed halo catalogues according to the halo occupation distribution model constrained by the observed CAMIRA LRGs. The stellar mass (M⋆) is assigned to each LRG by the subhalo abundance-matching technique using the observed stellar-mass functions of CAMIRA LRGs. We evaluate photometric redshifts (photo-z) of mock LRGs by incorporating the photo-z scatter, which is derived from the observed M⋆–photo-z-scatter relations of the CAMIRA LRGs. We validate the constructed full-sky halo and light-cone LRG mock catalogues by comparing their angular clustering statistics (i.e. power spectra and correlation functions) with those measured from the halo catalogues of full N-body simulations and the CAMIRA LRG catalogues from the HSC SSP, respectively. We detect clear signatures of baryon acoustic oscillations (BAOs) from our mock LRGs, whose angular scales are well consistent with theoretical predictions. These results demonstrate that our mock LRGs can be used to evaluate covariance matrices at large scales and provide predictions for the BAO detectability and cosmological constraints.

The DESI One-percent Survey: Evidence for Assembly Bias from Low-redshift Counts-in-cylinders Measurements

We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z = 0.1 to 0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey. In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab, which enables the rapid, precise prediction of CiC for any HOD model available in halotools. This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in z ∼ 0.15 samples with limiting absolute magnitude M r < −20.0 and M r < −20.5 samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter M r < −21.0 sample at z ∼ 0.25 (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at z ∼ 0.15. We provide our constraints for each threshold sample’s characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3.

A new test of gravity – II. Application of marked correlation functions to luminous red galaxy samples

ABSTRACT We apply the marked correlation function test proposed by Armijo et al. (Paper I) to samples of luminous red galaxies (LRGs) from the final data release of the Sloan Digital Sky Survey (SDSS) III. The test assigns a density-dependent mark to galaxies in the estimation of the projected marked correlation function. Two gravity models are compared: general relativity (GR) and $f(R)$ gravity. We build mock catalogues which, by construction, reproduce the measured galaxy number density and two-point correlation function of the LRG samples, using the halo occupation distribution model (HOD). A range of HOD models give acceptable fits to the observational constraints, and this uncertainty is fed through to the error in the predicted marked correlation functions. The uncertainty from the HOD modelling is comparable to the sample variance for the SDSS-III LRG samples. Our analysis shows that current galaxy catalogues are too small for the test to distinguish a popular $f(R)$ model from GR. However, upcoming surveys with a better measured galaxy number density and smaller errors on the two-point correlation function, or a better understanding of galaxy formation, may allow our method to distinguish between viable gravity models.

Differentiable stochastic halo occupation distribution

ABSTRACT In this work, we demonstrate how differentiable stochastic sampling techniques developed in the context of deep reinforcement learning can be used to perform efficient parameter inference over stochastic, simulation-based, forward models. As a particular example, we focus on the problem of estimating parameters of halo occupation distribution (HOD) models that are used to connect galaxies with their dark matter haloes. Using a combination of continuous relaxation and gradient re-parametrization techniques, we can obtain well-defined gradients with respect to HOD parameters through discrete galaxy catalogue realizations. Having access to these gradients allows us to leverage efficient sampling schemes, such as Hamiltonian Monte Carlo, and greatly speed up parameter inference. We demonstrate our technique on a mock galaxy catalogue generated from the Bolshoi simulation using a standard HOD model and find near-identical posteriors as standard Markov chain Monte Carlo techniques with an increase of ∼8× in convergence efficiency. Our differentiable HOD model also has broad applications in full forward model approaches to cosmic structure and cosmological analysis.

DESI mock challenge: constructing DESI galaxy catalogues based on FastPM simulations

ABSTRACT Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large-scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one must build realistic simulations and robust covariance matrices. We build galaxy catalogues by applying a halo occupation distribution (HOD) model upon the FastPM simulations, such that the resulting galaxy clustering reproduces high-resolution N-body simulations. While the resolution and halo finder are different from the reference simulations, we reproduce the reference galaxy two-point clustering measurements – monopole and quadrupole – to a precision required by the DESI Year 1 emission line galaxy sample down to non-linear scales, i.e. $k\lt 0.5\, h\, \mathrm{Mpc}^{-1}$ or $s\gt 10\, \mathrm{Mpc}\, h^{-1}$. Furthermore, we compute covariance matrices based on the resulting FastPM galaxy clustering – monopole and quadrupole. We study for the first time the effect of fitting on Fourier conjugate (e.g. power spectrum) on the covariance matrix of the Fourier counterpart (e.g. correlation function). We estimate the uncertainties of the two parameters of a simple clustering model and observe a maximum variation of 20 per cent for the different covariance matrices. Nevertheless, for most studied scales the scatter is between 2 and 10 per cent. Consequently, using the current pipeline we can precisely reproduce the clustering of N-body simulations and the resulting covariance matrices provide robust uncertainty estimations against HOD fitting scenarios. We expect our methodology will be useful for the coming DESI data analyses and their extension for other studies.

The contribution of faint Lyman-α emitters to extended Lyman-α halos constrained by MUSE clustering measurements

Recent detections of extended Lyman-α halos around Lyα emitters (LAEs) have been reported on a regular basis, but their origin is still under investigation. Simulation studies predict that the outer regions of the extended halos contain a major contribution from the Lyα emission of faint, individually undetected LAEs. To address this matter from an observational angle, we used halo occupation distribution (HOD) modeling to reproduce the clustering of a spectroscopic sample of 1265 LAEs at 3 &lt; z &lt; 5 from the MUSE-Wide survey. We integrated the Lyα luminosity function to estimate the background surface brightness due to discrete faint LAEs. We then extended the HOD statistics inwards towards small separations and computed the factor by which the measured Lyα surface brightness is enhanced by undetected close physical neighbors. We considered various clustering scenarios for the undetected sources and compared the corresponding radial profiles. This enhancement factor from LAE clustering depends strongly on the spectral bandwidth Δv over which the Lyα emission is integrated and this value can amount to ≈20 − 40 for small values of Δv (around 200 − 400 km s−1) as achieved by recent studies utilizing integral-field spectrographic data. The resulting inferred Lyα surface brightness of faint LAEs ranges between (0.4 − 2)×1020 erg s−1 cm−2 arcsec−2, with a very slow radial decline outwards. Our results suggest that the outer regions of observed Lyα halos (R ≳ 50 pkpc) could indeed contain a strong component from external (but physically associated) LAEs, and may even be dominated by them. It is only for a relatively shallow faint-end slope of the Lyα luminosity function that this contribution from clustered LAEs would be rendered insignificant. We also confirm that the observed emission from the inner regions (R ≤ 20 − 30 pkpc) is too bright to be substantially affected by clustering. We compare our findings with predicted profiles from simulations and find good overall agreement. We outline possible future measurements to further constrain the impact of discrete undetected LAEs on observed extended Lyα halos.

The Spatial Clustering of ROSAT All-Sky Survey Active Galactic Nuclei. V. The Evolution of Broad-line AGN Clustering Properties in the Last 6 Gyr

This is the fifth paper in a series of investigations of the clustering properties of luminous, broad-emission-line active galactic nuclei (AGNs) identified in the ROSAT All-Sky Survey (RASS) and Sloan Digital Sky Survey (SDSS). In this work we measure the cross-correlation function (CCF) between RASS/SDSS Data Release 14 AGNs with the SDSS CMASS galaxy sample at 0.44 < z < 0.64. We apply halo occupation distribution (HOD) modeling to the CCF along with the autocorrelation function of the CMASS galaxies. We find that X-ray-selected and optically selected AGNs at 0.44 < z < 0.64 reside in statistically identical halos with a typical dark matter halo (DMH) mass of . The acceptable HOD parameter space for these two broad-line AGN samples have only statistically marginal differences caused by small deviations of the CCFs in the one-halo-dominated regime on small scales. In contrast to optically selected AGNs, the X-ray AGN sample may contain a larger population of satellites at M DMH ∼ 1013 h −1 M ⊙. We compare our measurements in this work with our earlier studies at lower independent redshift ranges, spanning a lookback time of 6 Gyr. The comparison over this wider redshift range of 0.07 < z < 0.64 reveals (i) no significant difference between the typical DMH masses of X-ray-selected and optically selected AGNs, (ii) weak positive clustering dependencies of with L X and M BH, (iii) no significant dependence of on Eddington ratio, and (iv) the same DMH masses host more-massive accreting black holes at high redshift than at low redshifts.

Galaxy Clustering in the Mira-Titan Universe. I. Emulators for the Redshift Space Galaxy Correlation Function and Galaxy–Galaxy Lensing

We construct accurate emulators for the projected and redshift space galaxy correlation functions and excess surface density as measured by galaxy–galaxy lensing, based on halo occupation distribution modeling. Using the complete Mira-Titan suite of 111 N-body simulations, our emulators vary over eight cosmological parameters and include the effects of neutrino mass and dynamical dark energy. We demonstrate that our emulators are sufficiently accurate for the analysis of the Baryon Oscillation Spectroscopic Survey DR12 CMASS galaxy sample over the range 0.5 ≤ r ≤ 50 h −1 Mpc. Furthermore, we show that our emulators are capable of recovering unbiased cosmological constraints from realistic mock catalogs over the same range. Our mock catalog tests show the efficacy of combining small-scale galaxy–galaxy lensing with redshift space clustering and that we can constrain the growth rate and σ 8 to 7% and 4.5%, respectively, for a CMASS-like sample using only the measurements covered by our emulator. With the inclusion of a cosmic microwave background prior on H 0, this reduces to a 2% measurement of the growth rate.

Self-calibrating optical galaxy cluster selection bias using cluster, galaxy, and shear cross-correlations

ABSTRACT The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition to the previously known small-scale boost in projected correlation functions, we find that the projection effects also significantly boost three-dimensional correlation functions to scales of 100 $h^{-1} \, \rm Mpc$. We perform a likelihood analysis assuming survey conditions similar to the Dark Energy Survey and show that the selection bias can be self-consistently constrained at the 10 per cent level. We discuss strategies for applying this approach to real data. We expect that expanding the analysis to smaller scales and using deeper lensing data would further improve the constraints on cluster selection bias.

The cosmic web of X-ray active galactic nuclei seen through the eROSITA Final Equatorial Depth Survey (eFEDS)

Which galaxies in the general population turn into active galactic nuclei (AGNs) is a keystone of galaxy formation and evolution. Thanks to SRG/eROSITA’s contiguous 140 square degree pilot survey field, we constructed a large, complete, and unbiased soft X-ray flux-limited (FX &gt; 6.5 × 10−15 erg s−1 cm−2) AGN sample at low redshift, 0.05 &lt; z &lt; 0.55. Two summary statistics, the clustering using spectra from SDSS-V and galaxy-galaxy lensing with imaging from HSC, are measured and interpreted with halo occupation distribution and abundance matching models. Both models successfully account for the observations. We obtain an exceptionally complete view of the AGN halo occupation distribution. The population of AGNs is broadly distributed among halos with a mean mass of 3.9−2.4+2.0 × 1012 M⊙. This corresponds to a large-scale halo bias of b(z = 0.34) = 0.99−0.10+0.08. The central occupation has a large transition parameter, σlog10(M) = 1.28 ± 0.2. The satellite occupation distribution is characterized by a shallow slope, αsat = 0.73 ± 0.38. We find that AGNs in satellites are rare, with fsat &lt; 20%. Most soft X-ray-selected AGNs are hosted by central galaxies in their dark matter halo. A weak correlation between soft X-ray luminosity and large-scale halo bias is confirmed (3.3σ). We discuss the implications of environmental-dependent AGN triggering. This study paves the way toward fully charting, in the coming decade, the coevolution of X-ray AGNs, their host galaxies, and dark matter halos by combining eROSITA with SDSS-V, 4MOST, DESI, LSST, and Euclid data.

Toward Accurate Modeling of Galaxy Clustering on Small Scales: Halo Model Extensions and Lingering Tension

This paper represents an effort to provide robust constraints on the galaxy–halo connection and simultaneously test the Planck ΛCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this “decorated” HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model, we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high-luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high-luminosity galaxies may be due to a problem with our assumed cosmological model.

Halo occupation distribution of Emission Line Galaxies: fitting method with Gaussian processes

The halo occupation distribution (HOD) framework is an empirical method to describe the connection between dark matter halos and galaxies, which is constrained by small scale clustering data. Efficient fitting procedures are required to scan the HOD parameter space. This paper describes such a method based on Gaussian Processes to iteratively build a surrogate model of the posterior of the likelihood surface from a reasonable amount of likelihood computations, typically two orders of magnitude less than standard Monte Carlo Markov chain algorithms. Errors in the likelihood computation due to stochastic HOD modelling are also accounted for in the method we propose. We report results of reproducibility, accuracy and stability tests of the method derived from simulation, taking as a test case star-forming emission line galaxies, which constitute the main tracer of the Dark Energy Spectroscopic Instrument and have so far a poorly constrained galaxy-halo connection from observational data.

2D k-th nearest neighbour statistics: a highly informative probe of galaxy clustering

ABSTRACT Beyond standard summary statistics are necessary to summarize the rich information on non-linear scales in the era of precision galaxy clustering measurements. For the first time, we introduce the 2D k-th nearest neighbour (kNN) statistics as a summary statistic for discrete galaxy fields. This is a direct generalization of the standard 1D kNN by disentangling the projected galaxy distribution from the redshift-space distortion signature along the line-of-sight. We further introduce two different flavours of 2D kNNs that trace different aspects of the galaxy field: the standard flavour which tabulates the distances between galaxies and random query points, and a ‘DD’ flavour that tabulates the distances between galaxies and galaxies. We showcase the 2D kNNs’ strong constraining power both through theoretical arguments and by testing on realistic galaxy mocks. Theoretically, we show that 2D kNNs are computationally efficient and directly generate other statistics such as the popular two-point correlation function (2PCF), voids probability function, and counts-in-cell statistics. In a more practical test, we apply the 2D kNN statistics to simulated galaxy mocks that fold in a large range of observational realism and recover parameters of the underlying extended halo occupation distribution (HOD) model that includes velocity bias and galaxy assembly bias. We find unbiased and significantly tighter constraints on all aspects of the HOD model with the 2D kNNs, both compared to the standard 1D kNN, and the classical redshift-space 2PCF.

Clustering dependence on Lyα luminosity from MUSE surveys at 3 &lt; z &lt; 6

We investigate the dependence of Lyα emitter (LAE) clustering on Lyα luminosity and connect the clustering properties of ≈L⋆ LAEs with those of much fainter ones, namely, ≈0.04L⋆. We use 1030 LAEs from the MUSE-Wide survey, 679 LAEs from MUSE-Deep, and 367 LAEs from the to-date deepest ever spectroscopic survey, the MUSE Extremely Deep Field. All objects have spectroscopic redshifts of 3 &lt; z &lt; 6 and cover a large dynamic range of Lyα luminosities: 40.15 &lt; log(LLyα/erg s−1) &lt; 43.35. We apply the Adelberger et al. K-estimator as the clustering statistic and fit the measurements with state-of-the-art halo occupation distribution (HOD) models. We find that the large-scale bias factor increases weakly with an increasing line luminosity. For the low-luminosity (log⟨LLyα/[erg s−1]⟩ = 41.22) and intermediate-luminosity (log⟨LLyα/[erg s−1]⟩ = 41.64) LAEs, we compute consistent bias factors blow = 2.43−0.15+0.15 and binterm. = 2.42−0.09+0.10, whereas for the high-luminosity (log⟨LLyα/[erg s−1]⟩ = 42.34) LAEs we calculated bhigh = 2.65−0.11+0.13. Consequently, high-luminosity LAEs occupy dark matter halos (DMHs) with typical masses of log(Mh/[h−1 M⊙]) = 11.09−0.09+0.10, while low-luminosity LAEs reside in halos of log(Mh/[h−1 M⊙]) = 10.77−0.15+0.13. The minimum masses to host one central LAE, Mmin, and (on average) one satellite LAE, M1, also vary with Lyα luminosity, growing from log(Mmin/[h−1M⊙]) = 10.3−0.3+0.2 and log(M1/[h−1 M⊙]) = 11.7−0.2+0.3 to log(Mmin/[h−1 M⊙]) = 10.7−0.3+0.2 and log(M1/[h−1 M⊙]) = 12.4−0.6+0.4 from low- to high-luminosity samples, respectively. The satellite fractions are ≲10% (≲20%) at 1σ (3σ) confidence level, supporting a scenario in which DMHs typically host one single LAE. We next bisected the three main samples into disjoint subsets to thoroughly explore the dependence of the clustering properties on LLyα. We report a strong (8σ) clustering dependence on Lyα luminosity, not accounting for cosmic variance effects, where the highest luminosity LAE subsample (log(LLyα/erg s−1) ≈ 42.53) clusters more strongly (bhighest = 3.13−0.15+0.08) and resides in more massive DMHs (log(Mh/[h−1M⊙] )= 11.43−0.10+0.04) than the lowest luminosity one (log(LLyα/erg s−1) ≈ 40.97), which presents a bias of blowest = 1.79−0.06+0.08 and occupies log(Mh/[h−1M⊙]) = 10.00−0.09+0.12 halos. We discuss the implications of these results for evolving Lyα luminosity functions, halo mass dependent Lyα escape fractions, and incomplete reionization signatures.