arXiv subjects

Sergio Contreras

Publications and source records attributed to Sergio Contreras.

At least 19 recordsLinked to original sources

arXiv2026

The Impact of Splashback Galaxies on Galaxy Assembly Bias

The clustering of galaxies is affected by the assembly history of their underlying dark matter halos. This complex phenomenon, known as galaxy assembly bias, has been extensively studied, but the exact physical origin remains unclear. Splashback halos, typically low-mass halos that have traversed larger neighboring halos, have been suggested to be associated with halo assembly bias. Using a semi-analytic galaxy-formation model applied to the Millennium simulation, we explicitly explore the role that splasback galaxies play in galaxy assembly bias. We identify splashbacks as present-day central galaxies that were formerly satellites of a more massive host, and construct stellar-mass selected galaxy samples with the splashbacks either removed or reclassified as satellites of their former host halo. We find that splashbacks tend to reside in low-mass, highly concentrated halos and in dense environments, and that they have relatively high stellar-to-halo mass ratios. Splashbacks appear to be largely responsible for the low-mass tail of the occupancy variation for highly concentrated halos and for halos in dense environments. Finally, when computing the impact of assembly bias on galaxy clustering, we find that while removing the splashbacks significantly reduces the signal, reassigning them has little effect on its amplitude but shifts the transition scale. We repeat the analysis with the hydrodynamical simulation TNG300, confirming the robustness of our results. Our results provide insight into assembly bias and have potential implications for modeling the galaxy-halo connection.

astro-ph.CO↗

arXiv2026

Validation of the Hybrid Bias Expansion model for the galaxy bispectrum

The Hybrid Bias Expansion model (also known as Hybrid Effective Field Theory, HEFT) provides a promising way to extend the range of validity of perturbative large-scale structure modelling by replacing perturbative gravitational evolution with the nonlinear displacement field measured from $N$-body simulations. While this approach has already been shown to improve the modelling of the power spectrum, its validity at the bispectrum level has not yet been established. In this work we perform a first systematic real-space validation of the Hybrid bispectrum model using DESI-like LRG and ELG mock catalogues constructed at fixed cosmology on volumes similar to those of DESI's LRG samples. We find that the model remains self-consistent up to $k_{\rm max}^B \simeq 0.25\,h\,{\rm Mpc}^{-1}$, while clear signs of breakdown appear for a similar EFT tree-level bispectrum approach at $k_{\rm max}^B \gtrsim 0.13\,h\,{\rm Mpc}^{-1}$. We also show that adding matter cross-statistics significantly improves the precision of the recovered bias parameters, while a partial third-order extension including only the $\delta^3$ operator does not extend the validity range. Finally, we find a strong hierarchy among the bispectrum basis terms when grouped by total bias-operator order, with the lowest-order sectors dominating the total amplitude, which has important implications in emulation strategies.

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arXiv2026

Learning the Universe with cosmological rescaling of merger trees and semi-analytic galaxy formation models

Learning cosmology from galaxy surveys requires large suites of simulations spanning the cosmological and astrophysical parameter space, yet hydrodynamical simulations of galaxy formation remain prohibitively expensive. Semi-analytic models offer an inexpensive, physically grounded alternative, but still require halo merger trees from $N$-body simulations, and densely sampling cosmological parameters in sufficient volume remains expensive. We address this by extending cosmological rescaling to operate directly on merger trees and applying it in the $\Omega_{\rm m}$-$\sigma_8$ plane, running the Santa Cruz semi-analytic model for galaxy formation on the rescaled trees to produce galaxy populations across new cosmological and astrophysical parameters at negligible additional cost. A novel halo-profile-based correction, controlled by a single free parameter, suppresses systematic bias in rescaled halo masses to below the per cent level. We apply the method to parameter estimation of $\Omega_{\rm m}$ and $\sigma_8$ given either the stellar mass function or the two-point correlation function, finding that as few as 64, and potentially fewer, base $N$-body simulations, rescaled to $\sim1000$ training samples, match the accuracy of 750 dedicated $N$-body simulations; rescaling to 3200 realisations improves the prediction of $\Omega_{\rm m}$ by $\sim25\%$. Rescaling all merger trees from a single CAMELS-SAM $N$-body simulation costs $\sim0.1$ CPUh, compared to several thousand CPUh to run the simulation itself. We demonstrate a practical route to obtaining predictions of galaxy summary statistics across cosmological and astrophysical parameters, even with a relatively small number of base $N$-body simulations.

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arXiv2026

Secondary Dependence of Baryonic Effects on the Density Profile of Dark Matter Halos

Baryonic physics is anticipated to be a major source of systematic uncertainty in current and future large-scale cosmological surveys. We investigate how baryonic effects on halo density profiles vary with secondary halo properties at fixed halo mass, using the large-volume MillenniumTNG hydrodynamical simulation and its dark matter-only counterpart. We focus on the impact of halo concentration and large-scale environment on the ratio of density profiles of matched halos in the hydrodynamical and dark matter-only simulations. At redshift $z = 0.0$, we find a strong dependence on halo concentration, especially at lower halo mass ($12.5 < \log(M_h/h^{-1}M_{\odot}) < 13.0$), where more concentrated halos exhibit weaker inner enhancement and stronger intermediate-radius suppression at fixed halo mass, with variations reaching $\sim 15\%$ at small scales and decreasing toward larger scales. This trend weakens and reverses at higher halo mass. In contrast, the secondary dependence on large-scale environment is weaker ($\sim 2\%$) and largely scale-independent, with halos in denser regions exhibiting slightly weaker intermediate suppression. By separating internal profile redistribution from total mass suppression, we show that concentration impacts both components, whereas the environmental dependence is primarily associated with an overall mass shift. These secondary dependencies persist at $ z = 0.5$ and correlate with variations in internal baryonic properties. We examine additional halo properties, including halo spin and velocity dispersion, and find significant secondary dependence. Overall, our results highlight the important role of secondary halo properties in modulating baryonic effects on halo density profiles, with potential implications for future modeling efforts.

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arXiv2026

The evolution of the baryonic content and mass profiles of satellite galaxies in the MTNG simulations

Empirical models often rely on key relations from the galaxy--halo connection to construct mock galaxy catalogues. These relations typically describe central galaxies more accurately than satellite galaxies, which are generally less massive and orbit within larger haloes. Satellite galaxies are affected by a variety of physical processes that pose significant challenges for modelling. In this work, we use \MTNG, a state-of-the-art cosmological hydrodynamic simulation, to study the evolution of the baryonic component of satellites. Using the merger trees from this simulation, we follow the evolution of all $z=0$ satellite galaxies, tracking their stellar mass, gas mass, and $r$- and $U$-band magnitudes. We characterise this evolution using proxies including the fraction of subhalo mass and maximum circular velocity remaining relative to infall, the pericentric distance, and the time since infall. All of these quantities are commonly available in gravity-only simulations and can therefore be used to model these trends in simpler galaxy population models. We find that the gas mass, which is well described by the remaining subhalo mass fraction, declines much more rapidly than the other components, with satellites losing $\sim 80\%$ of their gas by the time the subhalo has lost half of its total mass. By contrast, the evolution of stellar mass and magnitudes is overall slower and is better described by the reduction of the host subhalo $v_{\rm max}$. We then examine the evolution of satellite mass profiles. We find that, although stripping is strongest in the outer regions, the intermediate and inner parts of satellites experience mass loss at early times. The results of this work can be used by empirical models and galaxy formation models built on gravity-only simulations to improve their descriptions of satellite galaxies.

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arXiv2026

Cosmological constraints from the small scale clustering of Emission Line Galaxies

Spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI) and Euclid are mapping the spatial distribution of millions of galaxies, with Emission Line Galaxies (ELGs) serving as the dominant tracer in the redshift range $0.8<z<1.6$. Standard approaches for extracting cosmological information from galaxy clustering, however, typically discard highly constraining measurements from the nonlinear regime. We apply SHAMe-SF - a modification of Subhalo Abundance Matching tailored for star-forming galaxy samples - to analyse the three-dimensional clustering of DESI ELGs from the One-Percent data release, extending their cosmological analysis deep into the nonlinear regime. We validate our pipeline using two mock ELG samples drawn from the state-of-the-art cosmological hydrodynamical simulation MillenniumTNG, demonstrating that our model yields unbiased constraints on $\sigma_8$ and $\Omega_{\rm m}h^2$ down to scales of $0.3~h^{-1}$Mpc on both samples. We find that including scales below $0.8~h^{-1}$Mpc is critical for mitigating projection effects and obtaining unbiased constraints on $\sigma_8$. Applied to the DESI One-Percent measurements, our analysis yields $\sim6$% constraints on $\sigma_8 = 0.81^{+0.05}_{-0.06}$ and $\Omega_{\rm m}h^2=0.146^{+0.009}_{-0.009}$. Remarkably, the accuracy of these constraints is similar to that obtained from the combined full-shape analysis of all DESI DR1 tracers, yet using only 1% of the survey volume. A naive extrapolation of our results from the One-Percent to the full survey area suggests that the complete survey could deliver roughly an order-of-magnitude improvement in precision - a prospect that, while subject to significant practical challenges, illustrates the cosmological potential encoded in the nonlinear regime.

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arXiv2025

The effect of baryons on the positions and velocities of satellite galaxies in the MTNG simulation

Mock galaxy catalogues are often constructed from dark-matter-only simulations based on the galaxy-halo connection. Although modern mocks can reproduce galaxy clustering to some extent, the absence of baryons affects the spatial and kinematic distributions of galaxies in ways that remain insufficiently quantified. We compare the positions and velocities of satellite galaxies in the MTNG hydrodynamic simulation with those in its dark-matter-only counterpart, assessing how baryonic effects influence galaxy clustering and contrasting them with the impact of galaxy selection, i.e. the dependence of clustering on sample definition. Using merger trees from both runs, we track satellite subhaloes until they become centrals, allowing us to match systems even when their z=0 positions differ. We then compute positional and velocity offsets as functions of halo mass and distance from the halo centre, and use these to construct a subhalo catalogue from the dark-matter-only simulation that reproduces the galaxy distribution in the hydrodynamic run. Satellites in the hydrodynamic simulation lie 3-4% closer to halo centres than in the dark-matter-only case, with an offset that is nearly constant with halo mass and increases toward smaller radii. Satellite velocities are also systematically higher in the dark-matter-only run. At scales of 0.1 Mpc/h, these spatial and kinematic differences produce 10-20% variations in clustering amplitude -- corresponding to 1-3$\sigma$ assuming DESI-like errors -- though the impact decreases at larger scales. These baryonic effects are relevant for cosmological and lensing analyses and should be accounted for when building high-fidelity mocks. However, they remain smaller than the differences introduced by galaxy selection, which thus represents the dominant source of uncertainty when constructing mocks based on observable quantities.

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arXiv2025

Cosmological constraints from galaxy clustering and galaxy-galaxy lensing with extended SubHalo Abundance Matching

We present the first cosmological constraints from a joint analysis of galaxy clustering and galaxy-galaxy lensing using extended SubHalo Abundance Matching (SHAMe). We analyse stellar mass-selected Galaxy And Mass Assembly (GAMA) galaxy clustering and Kilo-Degree Survey (KiDS-1000) galaxy-galaxy lensing and find constraints on $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3}=0.793^{+0.025}_{-0.024}$, in agreement with Planck at 1.7$\sigma$, with $\sigma_8$ the mass density fluctuation amplitude in 8 $h^{-1}{\rm Mpc}$ sphere at present and $\Omega_{\rm m}$ the density parameter in total matter. These results are in agreement with the Cosmic Microwave Background results from Planck. We are able to constrain all 5 SHAMe parameters, which describe the galaxy-subhalo connection. We validate our methodology by first applying it to simulated catalogues, generated from the TNG300 simulation, which mimic the stellar mass selection of our real data. We show that we are able to recover the input cosmology for both our fiducial and all-scale analyses. Our all-scale analysis extends to scales of galaxy-galaxy lensing below $r_\mathrm{p}<1.4\,\mathrm{Mpc}/h$, which we exclude in our fiducial analysis to avoid baryonic effects. When including all scales, we find a value of $S_8$, which is 1.26$\sigma$ higher than our fiducial result (against naive expectations where baryonic feedback should lead to small-scale power suppression), and in agreement with Planck at 0.9$\sigma$. We also find a 21% tighter constraint on $S_8$ and a 29% tighter constraint on $\Omega_\mathrm{m}$ compared to our fiducial analysis. This work shows the power and potential of joint small-scale galaxy clustering and galaxy-galaxy lensing analyses using SHAMe.

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arXiv2025

A New Measure of Assembly Bias using the Environment Dependence of the Luminosity Function

Assembly bias is the variation in the clustering of dark matter halos and galaxies that arises from correlations between the halo assembly history and the large-scale environment at fixed halo mass. In this work, we use the cosmological magneto-hydrodynamical simulation TNG300 to investigate how assembly bias affects the environment-dependent galaxy luminosity function. We measure the luminosity functions in bins of large-scale environment for the original simulated galaxy sample and for a shuffled sample, where the galaxies are randomly reassigned among halos of similar mass to remove assembly bias. By comparing them, we find distinct signatures, showing variations in the number of galaxies at the $\sim10\%$ level across all luminosities. Assembly bias increases the tendency of galaxies to reside in denser environments and further dilutes underdense regions, beyond the trends governed by halo mass. When separating by color, we see that assembly bias has a much bigger effect on red galaxies fainter than $\mathrm{M_r} - 5 \log{h} = -18.5$, which accounts for a $\sim20\%$ increase in the number of galaxies in the densest environment and a remarkable $50\%$ decrease in the least dense regions. The ratio of these measurements for the densest and least dense regions provides a significant assembly bias signal for the faint red galaxies, larger than a factor of two. Overall, our results provide a novel sensitive measure of assembly bias, offering valuable insight for modeling the effect and a potential new route to detect it in observations.

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arXiv2024

A 1% accurate method to include baryonic effects in galaxy-galaxy lensing models

Galaxy clustering and galaxy-galaxy lensing are two of the main observational probes in Stage-IV large-scale structure surveys. Unfortunately, the complicated relationship between galaxies and matter limits the exploitation of this data. Galaxy bias models -- such as the hybrid Lagrangian bias expansion -- allow describing galaxy clustering down to scales as small as $k = 0.7h$/Mpc. However, the galaxy-matter cross-power spectra are already affected by baryons on these scales, directly impacting the modelling of galaxy-galaxy lensing. We propose to extend models of the galaxy-matter cross-power spectrum $P_{\rm gm}(k)$ (currently only accounting for dark matter) by including a baryonic correction inferred from the matter component ($S_{\rm mm}(k)$), so that $P_{\rm gm, full \, physics} (k) = \sqrt{S_{\rm mm}} P_{\rm gm, gravity \, only}$. We use the FLAMINGO simulations to measure the effect of baryons on the galaxy-matter cross-power spectrum and to assess the performance of our model. We perform a Bayesian analysis of synthetic data, implementing a model based on BACCO's hybrid Lagrangian bias expansion (for the nonlinear galaxy bias) and Baryon Correction Model. Ignoring baryons in the galaxy-matter cross-power spectrum leads to a biased inference of the galaxy bias, while ignoring baryons in both the galaxy-matter and matter-matter power spectra leads to a biased inference of both the galaxy bias and cosmological parameters. In contrast, our method is 1% accurate compared to all physics variations in FLAMINGO and on all scales described by hybrid perturbative models ($k < 0.7h$/Mpc). Moreover, our model leads to inferred bias and cosmological parameters compatible within 1$\sigma$ with their reference values. We anticipate that our method will be a promising candidate for analysing forthcoming Stage-IV survey data.

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arXiv2024

Galaxy formation physics behind bar formation: A view from cosmological hydrodynamical simulations

We present a suite of zoom-in cosmological simulations of Milky Way-like galaxies with a prominent disc component and a strong bar in their centre, based on a subsample of barred galaxies from the TNG50 magneto-hydrodynamic simulation. We modify the physical models that regulate star formation, namely, supernova feedback and black hole quasar feedback, to examine how they affect the disc and bar formation. We find that, independently of the feedback prescriptions, all galaxies show a similar morphology, which is dominant in comparison with the bulge mass. The black hole quasar feedback models used in this study do not affect bar formation, although they can affect the bar strength and length. The energy released by the supernovae causes a delay in the time of bar formation and, in models with the strongest feedback, galaxies form stable discs against bar formation. This could be understood since supernova feedback influences disc and bulge assembly, resulting in discs with lower mass content, radial velocity dispersion and larger size as the supernova feedback strength increases. We study disc stability using three bar instability criteria proposed in the literature. We find that galaxies with varied supernovae and black hole quasar feedback satisfy these criteria at the moment of bar formation, except in extreme cases where the galaxy lacks or has weak supernova feedback. In these models, two of three criteria fail to forecast the existence (or absence) of a bar, probably because they do not account for the influence of a massive and compact bulge. Our findings provide insights into the physical processes behind bar formation and highlight the importance of additional conditions, other than a massive and compact disc that promote bar formation.

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arXiv2024

Investigating the galaxy-halo connection of DESI Emission-Line Galaxies with SHAMe-SF

The Dark Energy Spectroscopic Instrument (DESI) survey is mapping the large-scale distribution of millions of Emission Line Galaxies (ELGs) over vast cosmic volumes to measure the growth history of the Universe. However, compared to Luminous Red Galaxies (LRGs), very little is known about the connection of ELGs with the underlying matter field. In this paper, we employ a novel theoretical model, SHAMe-SF, to infer the connection between ELGs and their host dark matter subhaloes. SHAMe-SF is a version of subhalo abundance matching that incorporates prescriptions for multiple processes, including star formation, tidal stripping, environmental correlations, and quenching. We analyse the public measurements of the projected and redshift-space ELGs correlation functions at $z=1.0$ and $z=1.3$ from DESI One Percent data release, which we fit over a broad range of scales $r \in [0.1, 30]/h^{-1}$Mpc to within the statistical uncertainties of the data. We also validate the inference pipeline using two mock DESI ELG catalogues built from hydrodynamical (TNG300) and semi-analytical galaxy formation models (\texttt{L-Galaxies}). SHAMe-SF is able to reproduce the clustering of DESI-ELGs and the mock DESI samples within statistical uncertainties. We infer that DESI ELGs typically reside in haloes of $\sim 10^{11.8}h^{-1}$M$_{\odot}$ when they are central, and $\sim 10^{12.5}h^{-1}$M$_{\odot}$ when they are a satellite, which occurs in $\sim$30 \% of the cases. In addition, compared to the distribution of dark matter within halos, satellite ELGs preferentially reside both in the outskirts and inside haloes, and have a net infall velocity towards the centre. Finally, our results show evidence of assembly bias and conformity.

astro-ph.CO↗

arXiv2024

Exploring the physical origins of halo assembly bias from early times

The large-scale linear halo bias encodes the relation between the clustering of dark-matter (DM) halos and that of the underlying matter density field. Although the primary dependence of bias on halo mass is well understood in the context of structure formation, the physical origins of the multiple additional relations at fixed halo mass, commonly known as secondary halo bias, have not been fully elucidated. Of particular relevance is the secondary dependence on halo assembly history, known as halo assembly bias. Our goal is to determine whether the properties of the initial regions from which $z=0$ halos originate produce any secondary bias at $z=0$. By analyzing these initial dependencies in connection with halo assembly bias, we intend to provide insight on the physical origins of the effect. To this end, we select halos at $z=0$ in the IllustrisTNG DM-only simulation and trace back the positions and velocities of their DM particles to $z=12$. The resulting initial regions are characterized according to several shape-related and kinematic properties. The secondary bias signal produced by these properties at $z=0$ is measured using an object-by-object bias estimator, which offers significant analytical advantages. We show that, when split by the properties of their initial DM clouds, $z=0$ halos display significant secondary bias, clearly exceeding the amplitude of the well-known halo assembly bias signal produced by concentration and age. The maximum bias segregation is measured for cloud velocity dispersion and radial velocity, followed by cloud concentration, sphericity, ellipticity and triaxiality. We further show that both velocity dispersion and radial velocity are also the properties of the initial clouds that most strongly correlate with halo age and concentration at fixed halo mass. Our results highlight the importance of linear effects in shaping halo assembly bias.

astro-ph.CO↗

arXiv2024

Validating the clustering predictions of empirical models with the FLAMINGO simulations

Context. Mock galaxy catalogues are essential for correctly interpreting current and future generations of galaxy surveys. Despite their significance in galaxy formation and cosmology, little to no work has been done to validate the predictions of these mocks for high-order clustering statistics. Aims. We compare the predicting power of the latest generation of empirical models used in the creation of mock galaxy catalogues: a 13-parameter Halo Occupation Distribution (HOD) and an extension of the SubHalo Abundance Matching technique (SHAMe). Methods. We build GalaxyEmu-Planck, an emulator that makes precise predictions for the two-point correlation function, galaxy-galaxy lensing (restricted to distances greater than 1 $h^{-1} {\rm Mpc}$ to avoid baryonic effects), and other high-order statistics resulting from the evaluation of SHAMe and HOD models. Results. We evaluate the precision of GalaxyEmu-Planck using two galaxy samples extracted from the FLAMINGO hydrodynamical simulation that mimic the properties of DESI-BGS and BOSS galaxies, finding that the emulator reproduces all the predicted statistics precisely. The HOD showed comparable performance when fitting galaxy clustering and galaxy-galaxy lensing. In contrast, the SHAMe model showed better predictions for higher-order statistics, especially regarding the galaxy assembly bias. We also tested the performance of the models after removing some of their extensions, finding that we can withdraw two of the HOD parameters without a loss of performance. Conclusions. The results of this paper validate the current generation of empirical models as a way to reproduce galaxy clustering, galaxy-galaxy lensing and other high-order statistics. The excellent performance of the SHAMe model with a small number of free parameters suggests that it is a valid method to extract cosmological constraints from galaxy clustering.

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arXiv2024

SHAMe-SF: Predicting the clustering of star-forming galaxies with an enhanced abundance matching model

With the advent of several galaxy surveys targeting star-forming galaxies, it is important to have models capable of interpreting their spatial distribution in terms of astrophysical and cosmological parameters. To address this need, we introduce SHAMe-SF, an extension of the subhalo abundance matching (SHAM) technique designed specifically for analyzing the redshift-space clustering of star-forming galaxies. Our model directly links a galaxy's star formation rate to the properties of its host dark-matter halo, with further modulations based on effective models of feedback and gas stripping. To quantify the accuracy of our model, we show that it simultaneously reproduces key clustering statistics such as the projected correlation function, monopole, and quadrupole of star-forming galaxy samples at various redshifts and number densities. Notably, these tests were conducted over a wide range of scales $[0.6, 30]\hMpc$, using samples from both the TNG300 magneto-hydrodynamic simulation and from a semi-analytical model. SHAMe-SF can also reproduce the clustering of simulated galaxies that fall within the colour selection criteria employed by DESI for emission line galaxies. Our model exhibits several potential applications, including the generation of covariance matrices, exploration of galaxy formation processes, and even placing constraints on the cosmological parameters of the Universe.

astro-ph.CO↗

arXiv2023

The BACCO simulation project: biased tracers in real space

We present an emulator for the two-point clustering of biased tracers in real space. We construct this emulator using neural networks calibrated with more than $400$ cosmological models in a 8-dimensional cosmological parameter space that includes massive neutrinos an dynamical dark energy. The properties of biased tracers are described via a Lagrangian perturbative bias expansion which is advected to Eulerian space using the displacement field of numerical simulations. The cosmology-dependence is captured thanks to a cosmology-rescaling algorithm. We show that our emulator is capable of describing the power spectrum of galaxy formation simulations for a sample mimicking that of a typical Emission-Line survey at $z \sim 1$ with an accuracy of $1-2\%$ up to nonlinear scales $k \sim 0.7 h \mathrm{Mpc}^{-1}$.

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arXiv2023

Consistent clustering and lensing of SDSS-III BOSS galaxies with an extended abundance matching formalism

Several analyses have shown that LCDM-based models cannot jointly describe the clustering (GC) and galaxy-galaxy lensing (GGL) of galaxies in the SDSS-III BOSS survey, which is commonly known as the 'lensing-is-low problem'. In this work, we show that an extension of Subhalo Abundance Matching, dubbed SHAMe, successfully solves this problem. First, we show that this model accurately reproduces the GC and GGL of a mock galaxy sample in the TNG300 hydrodynamic simulation with analogous properties to BOSS galaxies. Then, we switch our attention to observed BOSS galaxies at z=0.31-0.43, and we attempt to reproduce their GC and GGL by evaluating SHAMe on two different simulations: one adopting best-fitting cosmological parameters from Planck and the other from weak gravitational lensing surveys (Low S8), where the amplitude of matter fluctuations is lower for the latter. We find excellent agreement between SHAMe predictions and observations for both cosmologies, indicating that the lensing-is-low problem originates from approximations in previous theoretical descriptions of the data. The main difference between SHAMe results in these cosmologies is the level of galaxy assembly bias, which is approximately 20 and 10% for Planck and Low S8, respectively. These results highlight the dangers of employing oversimplified models to analyse current large-scale structure datasets, and the need for realistic yet flexible descriptions of the galaxy-halo connection.

astro-ph.CO↗

arXiv2023

On the origin of the evolution of the halo occupation distribution

We use the TNG300 magneto-hydrodynamic simulation and mock catalogues built using subhalo abundance matching (SHAM) to study the origin of the redshift evolution of the halo occupation distribution (HOD). We analyse stellar-mass selected galaxy samples with fixed number densities, spanning the redshift range $0 \le z \le 3$. We measure their halo occupation functions and fit the HOD parameters to study their evolution over cosmic time. The TNG300 galaxy population strongly depends on the baryonic physics implemented in the simulation. In contrast, the galaxy population predicted by a basic SHAM model without scatter is a direct result of the cosmology of the dark matter simulation. We find that the HOD evolution is similar for both models and is consistent with a previous study of the HOD evolution in semi-analytical models. Specifically, this is the case for the ratio between the characteristic halo masses for hosting central and satellite galaxies. The only HOD parameter whose evolution varies across models is $σ_{\rm logM}$, which contains information about the stellar mass-halo mass relation of the galaxies and does not strongly impact galaxy clustering. We also demonstrate that the dependence on the specific values of the cosmological parameters is small. We conclude that the cosmology of the galaxy sample, i.e. the cosmological hierarchical growth of structure, and not the baryonic physics prescriptions, governs the evolution of the HOD for stellar mass-selected samples. These results have important implications for populating simulated lightcones with galaxies and can facilitate the interpretation of clustering data at different redshifts.

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