Search

Weak gravitational lensing is a powerful tool for precision tests of cosmology. As the expected deflection angles are small, predictions based on non-linear N -body simulations are commonly computed with the Born approximation. Here, we examine this assumption using DORIAN, a newly developed full-sky ray-tracing scheme applied to high-resolution mass-shell outputs of the two largest simulations in the MillenniumTNG suite, each with a 3000 Mpc box containing almost 1.1 trillion cold dark matter particles in addition to 16.7 billion particles representing massive neutrinos. We examine simple two-point statistics like the angular power spectrum of the convergence field, as well as statistics sensitive to higher order correlations such as peak and minimum statistics, void statistics, and Minkowski functionals of the convergence maps. Overall, we find only small differences between the Born approximation and a full ray-tracing treatment. While these are negligibly small at power-spectrum level, some higher order statistics show more sizeable effects; ray-tracing is necessary to achieve per cent level precision. At the resolution reached here, full-sky maps with 0.8 billion pixels and an angular resolution of 0.43 arcmin, we find that interpolation accuracy can introduce appreciable errors in ray-tracing results. We therefore implemented an interpolation method based on non-uniform fast Fourier transforms (NUFFT) along with more traditional methods. Bilinear interpolation introduces significant smoothing, while nearest grid point sampling agrees well with NUFFT, at least for our fiducial source redshift, |$z_s=1.0$|⁠ , and for the 1 arcmin smoothing we use for higher order statistics. [ABSTRACT FROM AUTHOR]

For decades, the boundary of cosmic filaments has been a subject of debate. In this work, we determine the physically motivated radii of filaments by constructing stacked galaxy number density profiles around the filament spines. We find that the slope of the profile changes with distance to the filament spine, reaching its minimum at approximately 1 Mpc at |$z=0$| in both state-of-the-art hydrodynamical simulations and observational data. This can be taken as the average value of the filament radius. Furthermore, we note that the average filament radius rapidly decreases from |$z=4$| to 1, and then slightly increases. Moreover, we find that the radius of the filament depends on the length of the filament, the distance from the connected clusters, and the masses of the clusters. These results suggest a two-phase formation scenario of cosmic filaments. The filaments experienced rapid contraction before |$z=1$|⁠ , but their density distribution has remained roughly stable since then. The subsequent mass transport along the filaments to the connected clusters is likely to have contributed to the formation of the clusters themselves. [ABSTRACT FROM AUTHOR]

Dwarf satellites in galaxy groups are distributed in an anisotropic and asymmetric manner, which is called the 'lopsided satellite distribution'. This lopsided signal has been observed not only in galaxy pairs but also in isolated systems. However, the physical origin of the lopsided signal in isolated systems is still unknown. In this work, we investigate this in the state-of-the-art hydrodynamical simulation of the MillenniumTNG Project by tracing each system back to high redshift. We find that the lopsided signal is dominated by satellites located in the outer regions of the halo and is also dominated by recently accreted satellites. The lopsided signal originates from the anisotropic accretion of galaxies from the surrounding large-scale structure and that, after accretion, the non-linear evolution of satellites inside the dark matter halo weakens the lopsidedness. The signal decreases as cosmic time passes because of a competition between anisotropic accretion and internal evolution within dark matter haloes. Our findings provide a useful perspective for the study of galaxy evolution, especially for the origin of the spatial satellite galaxy distributions. [ABSTRACT FROM AUTHOR]

In this series of papers, we present an emulator-based halo model for the non-linear clustering of galaxies in modified gravity cosmologies. In the first paper, we present emulators for the following halo properties: the halo mass function, concentration–mass relation and halo-matter cross-correlation function. The emulators are trained on data extracted from the forge and bridge suites of N -body simulations, respectively, for two modified gravity (MG) theories: f (R) gravity, and the DGP model, varying three standard cosmological parameters Ωm0, H 0, σ8, and one MG parameter, either |$\bar{f}_{R0}$| or r c. Our halo property emulators achieve an accuracy of |${\lesssim}1\ \hbox{per cent}$| on independent test data sets. We demonstrate that the emulators can be combined with a galaxy–halo connection prescription to accurately predict the galaxy–galaxy and galaxy–matter correlation functions using the halo model framework. [ABSTRACT FROM AUTHOR]

Sunyaev–Zel'dovich (SZ) measurements can dramatically improve our understanding of the intergalactic medium and the role of feedback processes in galaxy formation, allowing us to calibrate important astrophysical systematics in cosmological constraints from weak lensing galaxy clustering surveys. However, the signal is only measured in a two-dimensional projection, and its correct interpretation relies on understanding the connection between observable quantities and the underlying intrinsic properties of the gas, in addition to the relation between the gas and the underlying matter distribution. One way to address these challenges is through the use of hydrodynamical simulations such as the high-resolution, large-volume MillenniumTNG suite. We find that measurements of the optical depth, τ, and the Compton- y parameter, Y , receive large line-of-sight contributions that can be removed effectively by applying a compensated aperture photometry filter. In contrast with other τ probes (e.g. X-rays and fast radio bursts), the kinematic SZ-inferred τ receives most of its signal from a confined cylindrical region around the halo due to the velocity decorrelation along the line of sight. Additionally, we perform fits to the Y – M and τ– M scaling relations and report best-fitting parameters adopting the smoothly broken power law formalism. We note that subgrid physics modelling can broaden the error bar on these by 30 per cent for intermediate-mass haloes (⁠|${\sim }10^{13} \, {\rm M}_{\odot }$|⁠). The scatter of the scaling relations can be captured by an intrinsic dependence on concentration and an extrinsic dependence on tidal shear. Finally, we comment on the effect of using galaxies rather than haloes in observations, which can bias the inferred profiles by ∼20 per cent for L * galaxies. [ABSTRACT FROM AUTHOR]

Upcoming large galaxy surveys will subject the standard cosmological model, Lambda Cold Dark Matter, to new precision tests. These can be tightened considerably if theoretical models of galaxy formation are available that can predict galaxy clustering and galaxy–galaxy lensing on the full range of measurable scales, throughout volumes as large as those of the surveys, and with sufficient flexibility that uncertain aspects of the underlying astrophysics can be marginalized over. This, in particular, requires mock galaxy catalogues in large cosmological volumes that can be directly compared to observation, and can be optimized empirically by Monte Carlo Markov Chains or other similar schemes, thus eliminating or estimating parameters related to galaxy formation when constraining cosmology. Semi-analytic galaxy formation methods implemented on top of cosmological dark matter simulations offer a computationally efficient approach to construct physically based and flexibly parametrized galaxy formation models, and as such they are more potent than still faster, but purely empirical models. Here, we introduce an updated methodology for the semi-analytic L-Galaxies code, allowing it to be applied to simulations of the new MillenniumTNG project, producing galaxies directly on fully continuous past lightcones, potentially over the full sky, out to high redshift, and for all galaxies more massive than |$\sim 10^8\, {\rm M}_\odot$|⁠. We investigate the numerical convergence of the resulting predictions, and study the projected galaxy clustering signals of different samples. The new methodology can be viewed as an important step towards more faithful forward-modelling of observational data, helping to reduce systematic distortions in the comparison of theory to observations. [ABSTRACT FROM AUTHOR]

We study weak gravitational lensing convergence maps produced from the MillenniumTNG simulations by direct projection of the mass distribution on the past backwards lightcone of a fiducial observer. We explore the lensing maps over a large dynamic range in simulation mass and angular resolution, allowing us to establish a clear assessment of numerical convergence. By comparing full physics hydrodynamical simulations with corresponding dark-matter-only runs, we quantify the impact of baryonic physics on the most important weak lensing statistics. Likewise, we predict the impact of massive neutrinos reliably far into the non-linear regime. We also demonstrate that the 'fixed & paired' variance suppression technique increases the statistical robustness of the simulation predictions on large scales not only for time slices but also for continuously output lightcone data. We find that both baryonic and neutrino effects substantially impact weak lensing shear measurements, with the latter dominating over the former on large angular scales. Thus, both effects must explicitly be included to obtain sufficiently accurate predictions for stage IV lensing surveys. Reassuringly, our results agree accurately with other simulation results where available, supporting the promise of simulation modelling for precision cosmology far into the non-linear regime. [ABSTRACT FROM AUTHOR]

Approximate methods to populate dark-matter haloes with galaxies are of great utility to galaxy surveys. However, the limitations of simple halo occupation models (HODs) preclude a full use of small-scale galaxy clustering data and call for more sophisticated models. We study two galaxy populations, luminous red galaxies (LRGs) and star-forming emission-line galaxies (ELGs), at two epochs, z  = 1 and z  = 0, in the large-volume, high-resolution hydrodynamical simulation of the MillenniumTNG project. In a partner study we concentrated on the small-scale, one-halo regime down to r ∼ 0.1  h −1 Mpc, while here we focus on modelling galaxy assembly bias in the two-halo regime, r ≳ 1  h −1 Mpc. Interestingly, the ELG signal exhibits scale dependence out to relatively large scales (r ∼ 20  h −1 Mpc), implying that the linear bias approximation for this tracer is invalid on these scales, contrary to common assumptions. The 10–15 per cent discrepancy is only reconciled when we augment our halo occupation model with a dependence on extrinsic halo properties ('shear' being the best-performing one) rather than intrinsic ones (e.g. concentration, peak mass). We argue that this fact constitutes evidence for two-halo galaxy conformity. Including tertiary assembly bias (i.e. a property beyond mass and 'shear') is not an essential requirement for reconciling the galaxy assembly bias signal of LRGs, but the combination of external and internal properties is beneficial for recovering ELG the clustering. We find that centrals in low-mass haloes dominate the assembly bias signal of both populations. Finally, we explore the predictions of our model for higher order statistics such as nearest neighbour counts. The latter supplies additional information about galaxy assembly bias and can be used to break degeneracies between halo model parameters. [ABSTRACT FROM AUTHOR]

Luminous red galaxies (LRGs) and blue star-forming emission-line galaxies (ELGs) are key tracers of large-scale structure used by cosmological surveys. Theoretical predictions for such data are often done via simplistic models for the galaxy–halo connection. In this work, we use the large, high-fidelity hydrodynamical simulation of the MillenniumTNG project (MTNG) to inform a new phenomenological approach for obtaining an accurate and flexible galaxy-halo model on small scales. Our aim is to study LRGs and ELGs at two distinct epochs, z  = 1 and z  = 0, and recover their clustering down to very small scales, |$r \sim 0.1 \ h^{-1}\, {\rm Mpc}$|⁠ , i.e. the one-halo regime, while a companion paper extends this to a two-halo model for larger distances. The occupation statistics of ELGs in MTNG inform us that (1) the satellite occupations exhibit a slightly super-Poisson distribution, contrary to commonly made assumptions, and (2) that haloes containing at least one ELG satellite are twice as likely to host a central ELG. We propose simple recipes for modelling these effects, each of which calls for the addition of a single free parameter to simpler halo occupation models. To construct a reliable satellite population model, we explore the LRG and ELG satellite radial and velocity distributions and compare them with those of subhaloes and particles in the simulation. We find that ELGs are anisotropically distributed within haloes, which together with our occupation results provides strong evidence for cooperative galaxy formation (manifesting itself as one-halo galaxy conformity); i.e. galaxies with similar properties form in close proximity to each other. Our refined galaxy-halo model represents a useful improvement of commonly used analysis tools and thus can be of help to increase the constraining power of large-scale structure surveys. [ABSTRACT FROM AUTHOR]

We introduce a novel technique for constraining cosmological parameters and galaxy assembly bias using non-linear redshift-space clustering of galaxies. We scale cosmological N -body simulations and insert galaxies with the SubHalo Abundance Matching extended (SHAMe) empirical model to generate over 175 000 clustering measurements spanning all relevant cosmological and SHAMe parameter values. We then build an emulator capable of reproducing the projected galaxy correlation function at the monopole, quadrupole, and hexadecapole level for separations between |$0.1\, h^{-1}\, {\rm Mpc}$| and |$25\, h^{-1}\, {\rm Mpc}$|⁠. We test this approach by using the emulator and Monte Carlo Markov Chain (MCMC) inference to jointly estimate cosmology and assembly bias parameters both for the MTNG740 hydrodynamic simulation and for a semi-analytical model (SAM) galaxy formation built on the MTNG740-DM dark matter-only simulation, obtaining unbiased results for all cosmological parameters. For instance, for MTNG740 and a galaxy number density of |$n\sim 0.01 h^{3}\, {\rm Mpc}^{-3}$|⁠ , we obtain |$\sigma _{8}=0.799^{+0.039}_{-0.044}$| and |$\Omega _\mathrm{M}h^2= 0.138^{+ 0.025}_{- 0.018}$| (which are within 0.4 and 0.2σ of the MTNG cosmology). For fixed Hubble parameter (h), the constraint becomes |$\Omega _\mathrm{M}h^2= 0.137^{+ 0.011}_{- 0.012}$|⁠. Our method performs similarly well for the SAM and for other tested sample densities. We almost always recover the true amount of galaxy assembly bias within 1σ. The best constraints are obtained when scales smaller than |$2\, h^{-1}\, {\rm Mpc}$| are included, as well as when at least the projected correlation function and the monopole are incorporated. These methods offer a powerful way to constrain cosmological parameters using galaxy surveys. [ABSTRACT FROM AUTHOR]

Cosmological inference with large galaxy surveys requires theoretical models that combine precise predictions for large-scale structure with robust and flexible galaxy formation modelling throughout a sufficiently large cosmic volume. Here, we introduce the millenniumTNG (MTNG) project which combines the hydrodynamical galaxy formation model of illustrisTNG with the large volume of the millennium simulation. Our largest hydrodynamic simulation, covering |$(500 \, h^{-1}{\rm Mpc})^3 \simeq (740\, {\rm Mpc})^3$|⁠ , is complemented by a suite of dark-matter-only simulations with up to 43203 dark matter particles (a mass resolution of |$1.32\times 10^8 \, h^{-1}{\rm M}_\odot$|⁠) using the fixed-and-paired technique to reduce large-scale cosmic variance. The hydro simulation adds 43203 gas cells, achieving a baryonic mass resolution of |$2\times 10^7 \, h^{-1}{\rm M}_\odot$|⁠. High time-resolution merger trees and direct light-cone outputs facilitate the construction of a new generation of semi-analytic galaxy formation models that can be calibrated against both the hydro simulation and observation, and then applied to even larger volumes – MTNG includes a flagship simulation with 1.1 trillion dark matter particles and massive neutrinos in a volume of |$(3000\, {\rm Mpc})^3$|⁠. In this introductory analysis we carry out convergence tests on basic measures of non-linear clustering such as the matter power spectrum, the halo mass function and halo clustering, and we compare simulation predictions to those from current cosmological emulators. We also use our simulations to study matter and halo statistics, such as halo bias and clustering at the baryonic acoustic oscillation scale. Finally we measure the impact of baryonic physics on the matter and halo distributions. [ABSTRACT FROM AUTHOR]

In this series of papers, we present a simulation-based model for the non-linear clustering of galaxies based on separate modelling of clustering in real space and velocity statistics. In the first paper, we present an emulator for the real-space correlation function of galaxies, whereas the emulator of the real-to-redshift space mapping based on velocity statistics is presented in the second paper. Here, we show that a neural network emulator for real-space galaxy clustering trained on data extracted from the dark quest suite of N-body simulations achieves sub-per cent accuracies on scales 1 < r < 30 |$h^{-1} \, \mathrm{Mpc}$|⁠ , and better than 3 per cent on scales r < 1 |$h^{-1}\, \mathrm{Mpc}$| in predicting the clustering of dark-matter haloes with number density 10−3.5 |$(h^{-1}\, \mathrm{Mpc})^{-3}$|⁠ , close to that of SDSS LOWZ-like galaxies. The halo emulator can be combined with a galaxy–halo connection model to predict the galaxy correlation function through the halo model. We demonstrate that we accurately recover the cosmological and galaxy–halo connection parameters when galaxy clustering depends only on the mass of the galaxies' host halos. Furthermore, the constraining power in σ8 increases by about a factor of 2 when including scales smaller than 5 |$h^{-1} \, \mathrm{Mpc}$|⁠. However, when mass is not the only property responsible for galaxy clustering, as observed in hydrodynamical or semi-analytic models of galaxy formation, our emulator gives biased constraints on σ8. This bias disappears when small scales (r < 10 |$h^{-1}\, \mathrm{Mpc}$|⁠) are excluded from the analysis. This shows that a vanilla halo model could introduce biases into the analysis of future data sets. [ABSTRACT FROM AUTHOR]

To extract information from the clustering of galaxies on non-linear scales, we need to model the connection between galaxies and haloes accurately and in a flexible manner. Standard halo occupation distribution (HOD) models make the assumption that the galaxy occupation in a halo is a function of only its mass, however, in reality; the occupation can depend on various other parameters including halo concentration, assembly history, environment, and spin. Using the IllustrisTNG hydrodynamical simulation as our target, we show that machine learning tools can be used to capture this high-dimensional dependence and provide more accurate galaxy occupation models. Specifically, we use a random forest regressor to identify which secondary halo parameters best model the galaxy–halo connection and symbolic regression to augment the standard HOD model with simple equations capturing the dependence on those parameters, namely the local environmental overdensity and shear, at the location of a halo. This not only provides insights into the galaxy formation relationship but also, more importantly, improves the clustering statistics of the modelled galaxies significantly. Our approach demonstrates that machine learning tools can help us better understand and model the galaxy–halo connection, and are therefore useful for galaxy formation and cosmology studies from upcoming galaxy surveys. [ABSTRACT FROM AUTHOR]

We employ the hydrodynamical simulation illustrisTNG to inform the galaxy–halo connection of the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples of the Dark Energy Spectroscopic Instrument (DESI) survey at redshift z ∼ 0.8. Specifically, we model the galaxy colours of illustrisTNG and apply sliding DESI colour–magnitude cuts, matching the DESI target densities. We study the halo occupation distribution (HOD) model of the selected samples by matching them to their corresponding dark matter haloes in the illustrisTNG dark matter run. We find the HOD of both the LRG and ELG samples to be consistent with their respective baseline models, but also we find important deviations from common assumptions about the satellite distribution, velocity bias, and galaxy secondary biases. We identify strong evidence for concentration-based and environment-based occupational variance in both samples, an effect known as 'galaxy assembly bias'. The central and satellite galaxies have distinct dependencies on secondary halo properties, showing that centrals and satellites have distinct evolutionary trajectories and should be modelled separately. These results serve to inform the necessary complexities in modelling galaxy–halo connection for DESI analyses and also prepare for building high-fidelity mock galaxies. Finally, we present a shuffling-based clustering analysis that reveals a 10–15  |${{\ \rm per\ cent}}$| excess in the LRG clustering of modest statistical significance due to secondary galaxy biases. We also find a similar excess signature for the ELGs, but with much lower statistical significance. When a larger hydrodynamical simulation volume becomes available, we expect our analysis pipeline to pinpoint the exact sources of such excess clustering signatures. [ABSTRACT FROM AUTHOR]

We introduce the AbacusHOD model and present two applications of AbacusHOD and the AbacusSummit simulations to observations. AbacusHOD is a Halo Occupation Distribution (HOD) framework written in Python that is particle-based, multitracer, highly generalized, and highly efficient. It is designed specifically with multitracer/cosmology analyses for next-generation large-scale structure surveys in mind, and takes advantage of the volume and precision offered by the new state-of-the-art AbacusSummit cosmological simulations. The model is also highly customizable and should be broadly applicable to any upcoming surveys and a diverse range of cosmological analyses. In this paper, we demonstrate the capabilities of the AbacusHOD framework through two example applications. The first example demonstrates the high efficiency and the large HOD extension feature set through an analysis of full-shape redshift-space clustering of BOSS galaxies at intermediate to small scales (⁠|$\lt 30\, h^{-1}$|  Mpc), assessing the necessity of introducing secondary galaxy biases (assembly bias). We find strong evidence for using halo environment instead of concentration to trace secondary galaxy bias, a result which also leads to a moderate reduction in the 'lensing is low' tension. The second example demonstrates the multitracer capabilities of the AbacusHOD package through an analysis of the extended Baryon Oscillation Spectroscopic Survey cross-correlation measurements between three different galaxy tracers: luminous red galaxies, emission-line galaxies, and quasi-stellar objects. We expect the AbacusHOD framework, in combination with the AbacusSummit simulation suite, to play an important role in a simulation-based analysis of the upcoming Dark Energy Spectroscopic Instrument data sets. [ABSTRACT FROM AUTHOR]

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 × 1011  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. Halo light-cone catalogues for 25 base and 2 huge simulations at the fiducial cosmology are available at DOI:10.13139/OLCF/1825069 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Building accurate and flexible galaxy–halo connection models is crucial in modelling galaxy clustering on non-linear scales. Recent studies have found that halo concentration by itself cannot capture the full galaxy assembly bias effect and that the local environment of the halo can be an excellent indicator of galaxy assembly bias. In this paper, we propose an extended halo occupation distribution (HOD) model that includes both a concentration-based assembly bias term and an environment-based assembly bias term. We use this model to achieve a good fit (χ2/degrees of freedom = 1.35) on the 2D redshift-space two-point correlation function (2PCF) of the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxy sample. We find that the inclusion of both assembly bias terms is strongly favoured by the data and the standard five-parameter HOD model is strongly rejected. More interestingly, the redshift-space 2PCF drives the assembly bias parameters in a way that preferentially assigns galaxies to lower mass haloes. This results in galaxy–galaxy lensing predictions that are within 1σ agreement with the observation, alleviating the perceived tension between galaxy clustering and lensing. We also showcase a consistent 3σ–5σ preference for a positive environment-based assembly bias that persists over variations in the fit. We speculate that the environmental dependence might be driven by underlying processes such as mergers and feedback, but might also be indicative of a larger halo boundaries such as the splashback radius. Regardless, this work highlights the importance of building flexible galaxy–halo connection models and demonstrates the extra constraining power of the redshift-space 2PCF. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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, σ2 R halfmass, 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. [ABSTRACT FROM AUTHOR]

We investigate the accuracy of weak lensing simulations by comparing the results of five independently developed lensing simulation codes run on the same input N -body simulation. Our comparison focuses on the lensing convergence maps produced by the codes, and in particular on the corresponding PDFs, power spectra, and peak counts. We find that the convergence power spectra of the lensing codes agree to |$\lesssim 2{{\ \rm per\ cent}}$| out to scales ℓ ≈ 4000. For lensing peak counts, the agreement is better than |$5{{\ \rm per\ cent}}$| for peaks with signal-to-noise ≲ 6. We also discuss the systematic errors due to the Born approximation, line-of-sight discretization, particle noise, and smoothing. The lensing codes tested deal in markedly different ways with these effects, but they none-the-less display a satisfactory level of agreement. Our results thus suggest that systematic errors due to the operation of existing lensing codes should be small. Moreover their impact on the convergence power spectra for a lensing simulation can be predicted given its numerical details, which may then serve as a validation test. [ABSTRACT FROM AUTHOR]

We use the IllustrisTNG (TNG) simulations to explore the galaxy–halo connection as inferred from state-of-the-art cosmological, magnetohydrodynamical simulations. With the high-mass resolution and large volume achieved by combining the 100 Mpc (TNG100) and 300 Mpc (TNG300) volumes, we establish the mean occupancy of central and satellite galaxies and their dependence on the properties of the dark matter haloes hosting them. We derive best-fitting HOD parameters from TNG100 and TNG300 for target galaxy number densities of |$\bar{n}_g = 0.032\,$|   and |$\bar{n}_g = 0.016\, h^3$|  Mpc−3, respectively, corresponding to a minimum galaxy stellar mass of |$M_\star \sim 1.9\times 10^9\, $| and |$M_\star \sim 3.5\times 10^9\, {\rm M}_\odot$|⁠ , respectively, in hosts more massive than |$10^{11}\, {\rm M}_\odot$|⁠. Consistent with previous work, we find that haloes located in dense environments, with low concentrations, later formation times, and high angular momenta are richest in their satellite population. At low mass, highly concentrated haloes and those located in overdense regions are more likely to contain a central galaxy. The degree of environmental dependence is sensitive to the definition adopted for the physical boundary of the host halo. We examine the extent to which correlations between galaxy occupancy and halo properties are independent and demonstrate that HODs predicted by halo mass and present-day concentration capture the qualitative dependence on the remaining halo properties. At fixed halo mass, concentration is a strong predictor of the stellar mass of the central galaxy, which may play a defining role in the fate of the satellite population. The radial distribution of satellite galaxies, which exhibits a universal form across a wide range of host halo mass, is described accurately by the best-fitting NFW density profile of their host haloes. [ABSTRACT FROM AUTHOR]

We study cosmic voids in the normal-branch Dvali–Gabadadze–Porrati (nDGP) braneworld models that are representative of a class of modified gravity theories where deviations from General Relativity are usually hidden by the Vainshtein screening in high-density environments. This screening is less efficient away from these environments, which makes voids ideally suited for testing this class of models. We use N -body simulations of Λ-cold dark matter (ΛCDM) and nGDP universes, where dark matter haloes are populated with mock galaxies that mimic the clustering and number densities of the boss cmass galaxy sample. We measure the force, density, and weak lensing profiles around voids identified with six different algorithms. Compared to ΛCDM, voids in nDGP are more underdense due to the action of the fifth force that arises in these models, which leads to a faster evacuation of matter from voids. This leaves an imprint on the weak lensing tangential shear profile around nDGP voids, an effect that is particularly strong for 2D underdensities that are identified in the plane of the sky. We make predictions for the feasibility of distinguishing between nDGP and ΛCDM using void lensing in upcoming large-scale surveys such as lsst and euclid. We compare with the analysis of voids in chameleon gravity theories and find that the weak lensing signal for 3D voids is similar to nDGP, whereas for 2D voids the differences with ΛCDM are much stronger for the chameleon gravity case, a direct consequence of the different screening mechanisms operating in these theories. [ABSTRACT FROM AUTHOR]

We present a systematic comparison of several existing and new void-finding algorithms, focusing on their potential power to test a particular class of modified gravity models – chameleon f (R) gravity. These models deviate from standard general relativity (GR) more strongly in low-density regions and thus voids are a promising venue to test them. We use halo occupation distribution (HOD) prescriptions to populate haloes with galaxies, and tune the HOD parameters such that the galaxy two-point correlation functions are the same in both f (R) and GR models. We identify both three-dimensional (3D) voids and two-dimensional (2D) underdensities in the plane of the sky to find the same void abundance and void galaxy number density profiles across all models, which suggests that they do not contain much information beyond galaxy clustering. However, the underlying void dark matter density profiles are significantly different, with f (R) voids being more underdense than GR ones, which leads to f (R) voids having a larger tangential shear signal than their GR analogues. We investigate the potential of each void finder to test f (R) models with near-future lensing surveys such as euclid and lsst. The 2D voids have the largest power to probe f (R) gravity, with an lsst analysis of tunnel (which is a new type of 2D underdensity introduced here) lensing distinguishing at 80 and 11σ (statistical error) f (R) models with parameters, | f R 0| = 10−5 and 10−6, from GR. [ABSTRACT FROM AUTHOR]

Self-consistent N-body simulations of modified gravity models are a key ingredient to obtain rigorous constraints on deviations from general relativity using large-scale structure observations. This paper provides the first detailed comparison of the results of different N-body codes for the f (R), Dvali-Gabadadze-Porrati and Symmetron models, starting from the same initial conditions. We find that the fractional deviation of the matter power spectrum from ? cold dark matter agrees to better than 1 per cent up to k ~ 5-10 h Mpc-1 between the different codes. These codes are thus able to meet the stringent accuracy requirements of upcoming observational surveys. All codes are also in good agreement in their results for the velocity divergence power spectrum, halo abundances and halo profiles. We also test the quasi-static limit, which is employed in most modified gravity N-body codes, for the Symmetron model for which the most significant non-static effects among the models considered are expected. We conclude that this limit is a very good approximation for all of the observables considered here. [ABSTRACT FROM AUTHOR]