arXiv subjects

Pauline Zarrouk

Publications and source records attributed to Pauline Zarrouk.

At least 19 recordsLinked to original sources

arXiv2026

Frequentist Cosmological Constraints from Full-Shape Clustering Measurements in DESI DR1

We present a frequentist analysis of clustering measurements from Data Release 1 of the Dark Energy Spectroscopic Instrument (DESI) using the standard profile likelihood method. While Bayesian inferences for effective field theory models of galaxy clustering can be highly sensitive to prior choices for extended cosmological models, frequentist inferences are not susceptible to such effects. We compare frequentist and Bayesian constraints for the parameter set $\{σ_8, H_0, Ω_{\rm{m}}, w_0, w_a\}$ using the full-shape power spectrum multipoles, post-reconstruction baryon acoustic oscillation (BAO) measurements, and external datasets from the CMB and type Ia supernovae measurements. The frequentist confidence intervals are significantly shifted relative to the Bayesian credible intervals for the $w_0w_a$CDM model, unless supernovae data are included. When DESI full-shape and BAO data are fit jointly, we obtain the following $1σ$ frequentist confidence intervals for $Λ$CDM ($w_0w_a$CDM): $σ_8 = 0.863^{+0.048}_{-0.040} , \ H_0 = 68.96^{+0.81}_{-0.80} \ \rm{km \ s^{-1}Mpc^{-1}} , \ Ω_{\rm{m}} = 0.3034\pm0.0110$ ($σ_8 = 0.782^{+0.060}_{-0.036} , \ H_0 = 63.7^{+4.2}_{-2.0} \ \rm{km \ s^{-1}Mpc^{-1}} , \ Ω_{\rm{m}} = 0.378^{+0.024}_{-0.047} , \ w_0 = -0.16^{+0.10}_{-0.50} , \ w_a = -3.0^{+1.7}_{}$), corresponding to 0.8$σ$, 0.3$σ$, 0.7$σ$ (2.1$σ$, 4.1$σ$, 6.5$σ$, 6.3$σ$, 6.6$σ$) shifts between the maximum likelihood estimate and the Bayesian posterior mean for $Λ$CDM ($w_0w_a$CDM) respectively.

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arXiv2026

Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization

Bayesian analyses of the full-shape clustering of Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) exhibit prior-volume projection effects, whereby weakly constrained nuisance parameters of the Effective Field Theory of Large Scale Structure (EFTofLSS) shift marginalized cosmological posteriors away from the posterior maximum. We reanalyze DESI DR1 power spectrum multipoles using two complementary mitigation strategies: (i) nonlinear orthogonalization to decorrelate nuisance and cosmological parameter priors, and (ii) a fully reparameterization-invariant Jeffreys prior over all EFTofLSS coefficients, evaluated on-the-fly via closed-form Jacobians. Including data from DESI, Big-Bang Nuclesynthesis and a constraint on $n_{\mathrm{s}}$, baseline priors lead to multi-$σ$ projection in the Hubble parameter $H_{0}$ and dark energy equation of state parameters $w_{0}$ and $w_{a}$; the Jeffreys prior successfully recenters these posteriors to enclose the maximum a posteriori estimate within the 68\% credible regions, demonstrating clear mitigation of projection effects for these late-time expansion parameters. A hybrid Jeffreys+baseline-Gaussian configuration controls residual over-broad tails in the physical cold dark matter density $ω_{\mathrm{c}}$ while preserving the volume correction, and is our favoured approach. We compare the credible intervals derived using our methodology to those obtained using Halo Occupation Distribution (HOD)-informed priors and to confidence intervals derived using frequentist profile likelihood analyses, finding agreement in both central values and degeneracy directions in the $w_{0}$--$w_{a}$ plane. This demonstrates that, once projection effects are properly controlled, we can make robust inferences about the late-time cosmological expansion independent of the statistical framework adopted.

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arXiv2026

Setting SAIL: Leveraging Scientist-AI-Loops for Rigorous Visualization Tools

Scientists across all disciplines share a common challenge: the divide between their theoretical knowledge and the specialized skills and time needed to build interactive tools to communicate this expertise. While large language models (LLMs) offer unparalleled acceleration in code generation, they frequently prioritize functional syntax over scientific accuracy, risking visually convincing but scientifically invalid results. This work advocates the Scientist-AI-Loop (SAIL), a framework designed to harness this speed without compromising rigor. By separating domain logic from code syntax, SAIL enables researchers to maintain strict oversight of scientific concepts and constraints while delegating code implementation to AI. We illustrate this approach through two open-source, browser-based astrophysics tools: an interactive gravitational lensing visualization and a large-scale structure formation sandbox, both publicly available. Our methodology condensed development to mere days while maintaining scientific integrity. We specifically address failure modes where AI-generated code neglects phenomenological boundaries or scientific validity. While cautioning that research-grade code requires stringent protocols, we demonstrate through two examples that SAIL provides an effective code generation workflow for outreach, teaching, professional presentations, and early-stage research prototyping. This framework contributes to a foundation for the further development of AI-assisted scientific software.

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arXiv2025

A Unified Photometric Redshift Calibration for Weak Lensing Surveys using the Dark Energy Spectroscopic Instrument

The effective redshift distribution $n(z)$ of galaxies is a critical component in the study of weak gravitational lensing. Here, we introduce a new method for determining $n(z)$ for weak lensing surveys based on high-quality redshifts and neural network-based importance weights. Additionally, we present the first unified photometric redshift calibration of the three leading stage-III weak lensing surveys, the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey and the Kilo-Degree Survey (KiDS), with state-of-the-art spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We verify our method using a new, data-driven approach and obtain $n(z)$ constraints with statistical uncertainties of order $σ_{\bar z} \sim 0.01$ and smaller. Our analysis is largely independent of previous photometric redshift calibrations and, thus, provides an important cross-check in light of recent cosmological tensions. Overall, we find excellent agreement with previously published results on the DES Y3 and HSC Y1 data sets while there are some differences on the mean redshift with respect to the previously published KiDS-1000 results. We attribute the latter to mismatches in photometric noise properties in the COSMOS field compared to the wider KiDS SOM-gold catalog. At the same time, the new $n(z)$ estimates for KiDS do not significantly change estimates of cosmic structure growth from cosmic shear. Finally, we discuss how our method can be applied to future weak lensing calibrations with DESI data.

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arXiv2025

Cosmological Constraints from Full-Scale Clustering and Galaxy-Galaxy Lensing with DESI DR1

We present constraints on cosmic structure growth from the analysis of galaxy clustering and galaxy-galaxy lensing with galaxies from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1. We analyze four samples drawn from the Bright Galaxy Survey (BGS) and the Luminous Red Galaxy (LRG) target classes. Projected galaxy clustering measurements from DESI are supplemented with lensing measurements from the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and the Hyper Suprime-Cam (HSC) survey around the same targets. Our method relies on a simulation-based modeling framework using the AbacusSummit simulations and a complex halo occupation distribution model that incorporates assembly bias. We analyze scales down to $0.4 \, h^{-1} \, \mathrm{Mpc}$ for clustering and $2.5 \, h^{-1} \, \mathrm{Mpc}$ for lensing, leading to stringent constraints on $S_8 = σ_8 \sqrt{Ω_\mathrm{m} / 0.3}$ and $Ω_\mathrm{m}$ when fixing other cosmological parameters to those preferred by the CMB. We find $S_8 = 0.794 \pm 0.023$ and $Ω_\mathrm{m} = 0.295 \pm 0.012$ when using lensing measurements from DES and KiDS. Similarly, for HSC, we find $S_8 = 0.793 \pm 0.017$ and $Ω_\mathrm{m} = 0.303 \pm 0.010$ when assuming the best-fit photometric redshift offset suggested by the HSC collaboration. Overall, our results are in good agreement with other results in the literature while continuing to highlight the constraining power of non-linear scales.

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arXiv2025

Backlighting extended gas halos around luminous red galaxies: kinematic Sunyaev-Zel'dovich effect from DESI Y1 x ACT

The gas density profile around galaxies, shaped by feedback and affecting the galaxy lensing signal, is imprinted on the cosmic microwave background (CMB) by the kinematic Sunyaev-Zel'dovich effect (kSZ). We precisely measure this effect ($S/N\approx 10$) via velocity stacking with more than 800,000 spectroscopically confirmed luminous red galaxies (LRG) from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, which overlap with the Atacama Cosmology Telescope (ACT) Data Release 6 temperature maps over $\geq$ 4,000 deg$^2$. We explore the kSZ dependence with various galaxy parameters and find no significant trend with redshift, but clear trends with stellar mass and absolute magnitude in $g$, $r$, and $z$ bands. Our analysis suggests that the gas extends beyond the dark matter halo (99.5\% confidence, i.e. PTE = 0.005). We find a tentative preference for hydrodynamical simulation models with stronger feedback that drives gas further out (Illustris $z=0.5$, PTE = 0.37) over weaker-feedback cases (IllustrisTNG $z=0.8$, PTE = 0.045), though with limited statistical significance. In all cases, a free multiplicative amplitude was fit to the simulated profiles, and further modeling work is required to firm up these conclusions. We find consistency between kSZ profiles around spectroscopic and photometric LRG, with comparable statistical power, thus increasing our confidence in the photometric analysis. Additionally, we present the first kSZ measurement around DESI Y1 bright galaxy sample (BGS) and emission-line galaxies (ELG), whose features match qualitative expectations. Finally, we forecast $S/N \sim 50$ for future stacked kSZ measurements using data from ACT, DESI Y3, and Rubin Observatory. These measurements will serve as an input for galaxy formation models and baryonic uncertainties in galaxy lensing.

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arXiv2025

Analytical and EZmock covariance validation for the DESI 2024 results

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full Shape, two approaches are usually considered. First: analytical estimates of the covariance matrix use Gaussian approximations and (nonlinear) clustering measurements to estimate the matrix, which allows a relatively fast and computationally cheap way to generate matrices that adapt to an arbitrary clustering measurement. On the other hand, sample covariances are an empirical estimate of the matrix based on en ensemble of clustering measurements from fast and approximate simulations. While more computationally expensive due to the large amount of simulations and volume required, these allow us to take into account systematics that are impossible to model analytically. In this work we compare these two approaches in order to enable DESI's key analyses. We find that the configuration space analytical estimate performs satisfactorily in BAO analyses and its flexibility in terms of input clustering makes it the fiducial choice for DESI's 2024 BAO analysis. On the contrary, the analytical computation of the covariance matrix in Fourier space does not reproduce the expected measurements in terms of Full Shape analyses, which motivates the use of a corrected mock covariance for DESI's Full Shape analysis.

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arXiv2025

Dynamical Dark Energy in light of the DESI DR2 Baryonic Acoustic Oscillations Measurements

Understanding whether cosmic acceleration arises from a cosmological constant or a dynamical component is a central goal of cosmology, and the Dark Energy Spectroscopic Instrument (DESI) enables stringent tests with high-precision distance measurements. We analyze baryon acoustic oscillation (BAO) measurements from DESI Data Release 1 (DR1) and Data Release 2 (DR2), combined with Type Ia supernovae and a cosmic microwave background (CMB) distance prior. With the larger statistical power and wider redshift coverage of DR2, the preference for dynamical dark energy does not diminish relative to DR1. Using both a shape-function reconstruction and non-parametric approaches with a Horndeski-motivated correlation prior, we find that the dark-energy equation of state $w(z)$ varies with redshift. BAO data alone yield modest constraints, but in combination with independent supernova compilations and the CMB prior they strengthen the evidence for dynamics. Bayesian model comparison shows moderate support for departures from $Λ$CDM when multiple degrees of freedom in $w(z)$ are allowed, corresponding to $\approx3σ$ tension with $Λ$CDM (and higher for some data sets). Despite methodological differences, our results are consistent with companion DESI papers, underscoring the complementarity of approaches. Possible systematics remain under study; forthcoming DESI, \emph{Euclid}, and next-generation CMB data will provide decisive tests.

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arXiv2025

Stellar reddening map from DESI imaging and spectroscopy

We present new Galactic dust reddening maps of the high Galactic latitude sky using DESI imaging and spectroscopy. We directly measure the reddening of 2.6 million stars by comparing the observed stellar colors in $g-r$ and $r-z$ from DESI imaging with the synthetic colors derived from DESI spectra from the first two years of the survey. The reddening in the two colors is on average consistent with the Fitzpatrick (1999) extinction curve with $R_\mathrm{V}=3.1$. We find that our reddening maps differ significantly from the commonly used Schlegel et al. (1998) (SFD) reddening map (by up to 80 mmag in $E(B-V)$), and we attribute most of this difference to systematic errors in the SFD map. To validate the reddening map, we select a galaxy sample with extinction correction based on our reddening map, and this yields significantly better uniformity than the SFD extinction correction. Finally, we discuss the potential systematic errors in the DESI reddening measurements, including the photometric calibration errors that are the limiting factor on our accuracy. The $E(g-r)$ and $E(r-z)$ maps presented in this work, and for convenience their corresponding $E(B-V)$ maps with SFD calibration, are publicly available.

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arXiv2025

Neural Network-based model of galaxy power spectrum: Fast full-shape galaxy power spectrum analysis

We present a Neural Network based emulator for the galaxy redshift-space power spectrum that enables several orders of magnitude acceleration in the galaxy clustering parameter inference, while preserving 3$σ$ accuracy better than 0.5\% up to $k_{\mathrm{max}}$=0.25$h^{-1}Mpc$ within $Λ$CDM and around 0.5\% $w_0$-$w_a$CDM. Our surrogate model only emulates the galaxy bias-invariant terms of 1-loop perturbation theory predictions, these terms are then combined analytically with galaxy bias terms, counter-terms and stochastic terms in order to obtain the non-linear redshift space galaxy power spectrum. This allows us to avoid any galaxy bias prescription in the training of the emulator, which makes it more flexible. Moreover, we include the redshift $z \in [0,1.4]$ in the training which further avoids the need for re-training the emulator. We showcase the performance of the emulator in recovering the cosmological parameters of $Λ$CDM by analysing the suite of 25 AbacusSummit simulations that mimic the DESI Luminous Red Galaxies at $z=0.5$ and $z=0.8$, together as the Emission Line Galaxies at $z=0.8$. We obtain similar performance in all cases, demonstrating the reliability of the emulator for any galaxy sample at any redshift in $0 < z < 1.4$

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arXiv2025

Constraining the phase shift of relativistic species in DESI BAOs

In the early Universe, neutrinos decouple quickly from the primordial plasma and propagate without further interactions. The impact of free-streaming neutrinos is to create a temporal shift in the gravitational potential that impacts the acoustic waves known as baryon acoustic oscillations (BAOs), resulting in a non-linear spatial shift in the Fourier-space BAO signal. In this work, we make use of and extend upon an existing methodology to measure the phase shift amplitude $β_ϕ$ and apply it to the DESI Data Release 1 (DR1) BAOs with an anisotropic BAO fitting pipeline. We validate the fitting methodology by testing the pipeline with two publicly available fitting codes applied to highly precise cubic box simulations and realistic simulations representative of the DESI DR1 data. We find further study towards the methods used in fitting the BAO signal will be necessary to ensure accurate constraints on $β_ϕ$ in future DESI data releases. Using DESI DR1, we present individual measurements of the anisotropic BAO distortion parameters and the $β_ϕ$ for the different tracers, and additionally a combined fit to $β_ϕ$ resulting in $β_ϕ = 2.7 \pm 1.7$. After including a prior on the distortion parameters from constraints using \textit{Planck} we find $β_ϕ = 2.7^{+0.60}_{-0.67} $ suggesting $β_ϕ > 0$ at 4.3$σ$ significance. This result may hint at a phase shift that is not purely sourced from the standard model expectation for $N_{\rm{eff}}$ or could be a upwards statistical fluctuation in the measured $β_ϕ$; this result relaxes in models with additional freedom beyond $Λ$CDM.

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arXiv2024

ELG Spectroscopic Systematics Analysis of the DESI Data Release 1

Dark Energy Spectroscopic Instrument (DESI) uses more than 2.4 million Emission Line Galaxies (ELGs) for 3D large-scale structure (LSS) analyses in its Data Release 1 (DR1). Such large statistics enable thorough research on systematic uncertainties. In this study, we focus on spectroscopic systematics of ELGs. The redshift success rate ($f_{\rm goodz}$) is the relative fraction of secure redshifts among all measurements. It depends on observing conditions, thus introduces non-cosmological variations to the LSS. We, therefore, develop the redshift failure weight ($w_{\rm zfail}$) and a per-fibre correction ($η_{\rm zfail}$) to mitigate these dependences. They have minor influences on the galaxy clustering. For ELGs with a secure redshift, there are two subtypes of systematics: 1) catastrophics (large) that only occur in a few samples; 2) redshift uncertainty (small) that exists for all samples. The catastrophics represent 0.26\% of the total DR1 ELGs, composed of the confusion between O\,\textsc{ii} and sky residuals, double objects, total catastrophics and others. We simulate the realistic 0.26\% catastrophics of DR1 ELGs, the hypothetical 1\% catastrophics, and the truncation of the contaminated $1.31<z<1.33$ in the \textsc{AbacusSummit} ELG mocks. Their $P_\ell$ show non-negligible bias from the uncontaminated mocks. But their influences on the redshift space distortions (RSD) parameters are smaller than $0.2σ$. The redshift uncertainty of \Yone ELGs is 8.5 km/s with a Lorentzian profile. The code for implementing the catastrophics and redshift uncertainty on mocks can be found in https://github.com/Jiaxi-Yu/modelling_spectro_sys.

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arXiv2024

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological Implications from two Decades of Spectroscopic Surveys at the Apache Point observatory

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Ly$α$ forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, $r_d$, from eight different samples and six measurements of the growth rate parameter, $fσ_8$, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, $Λ$CDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization the BAO data provide nearly an order of magnitude improvement on curvature constraints. The RSD measurements indicate a growth rate that is consistent with predictions from Planck primary data and with General Relativity. When combining the results of SDSS BAO and RSD with external data, all multiple-parameter extensions remain consistent with a $Λ$CDM model. Regardless of cosmological model, the precision on $Ω_Λ$, $H_0$, and $σ_8$, remains at roughly 1\%, showing changes of less than 0.6\% in the central values between models. The inverse distance ladder measurement under a o$w_0w_a$CDM yields $H_0= 68.20 \pm 0.81 \, \rm km\, s^{-1} Mpc^{-1}$, remaining in tension with several direct determination methods. (abridged)

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arXiv2024

The 2-point correlation function covariance with fewer mocks

We present an approach for accurate estimation of the covariance of 2-point correlation functions that requires fewer mocks than the standard mock-based covariance. This can be achieved by dividing a set of mocks into jackknife regions and fitting the correction term first introduced in Mohammad & Percival (2022), such that the mean of the jackknife covariances corresponds to the one from the mocks. This extends the model beyond the shot-noise limited regime, allowing it to be used for denser samples of galaxies. We test the performance of our fitted jackknife approach, both in terms of accuracy and precision, using lognormal mocks with varying densities and approximate EZmocks mimicking the DESI LRG and ELG samples in the redshift range of z = [0.8, 1.2]. We find that the Mohammad-Percival correction produces a bias in the 2-point correlation function covariance matrix that grows with number density and that our fitted jackknife approach does not. We also study the effect of the covariance on the uncertainty of cosmological parameters by performing a full-shape analysis. We find that our fitted jackknife approach based on 25 mocks is able to recover unbiased and as precise cosmological parameters as the ones obtained from a covariance matrix based on 1000 or 1500 mocks, while the Mohammad-Percival correction produces uncertainties that are twice as large. The number of mocks required to obtain an accurate estimation of the covariance for 2-point correlation function is therefore reduced by a factor of 40-60.

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arXiv2023

SUNBIRD: A simulation-based model for full-shape density-split clustering

Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point correlation function (2PCF) analyses. However, modelling these density-dependent statistics down to the non-linear regime has so far remained challenging. We present a simulation-based model that is able to capture the cosmological dependence of the full shape of the density-split clustering (DSC) statistics down to intra-halo scales. Our models are based on neural-network emulators that are trained on high-fidelity mock galaxy catalogues within an extended-$Λ$CDM framework, incorporating the effects of redshift-space, Alcock-Paczynski distortions and models of the halo-galaxy connection. Our models reach sub-percent level accuracy down to $1\,h^{-1}{\rm Mpc}$ and are robust against different choices of galaxy-halo connection modelling. When combined with the galaxy 2PCF, DSC can tighten the constraints on $ω_{\rm cdm}$, $σ_8$, and $n_s$ by factors of 2.9, 1.9, and 2.1, respectively, compared to a 2PCF-only analysis. DSC additionally puts strong constraints on environment-based assembly bias parameters. Our code is made publicly available on Github.

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arXiv2023

Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample

We present a clustering analysis of the BOSS DR12 CMASS galaxy sample, combining measurements of the galaxy two-point correlation function and density-split clustering down to a scale of $1\,h^{-1}{\rm Mpc}$. Our theoretical framework is based on emulators trained on high-fidelity mock galaxy catalogues that forward model the cosmological dependence of the clustering statistics within an extended-$Λ$CDM framework, including redshift-space and Alcock-Paczynski distortions. Our base-$Λ$CDM analysis finds $ω_{\rm cdm} = 0.1201\pm 0.0022$, $σ_8 = 0.792\pm 0.034$, and $n_s = 0.970\pm 0.018$, corresponding to $fσ_8 = 0.462\pm 0.020$ at $z \approx 0.525$, which is in agreement with Planck 2018 predictions and various clustering studies in the literature. We test single-parameter extensions to base-$Λ$CDM, varying the running of the spectral index, the dark energy equation of state, and the density of massless relic neutrinos, finding no compelling evidence for deviations from the base model. We model the galaxy-halo connection using a halo occupation distribution framework, finding signatures of environment-based assembly bias in the data. We validate our pipeline against mock catalogues that match the clustering and selection properties of CMASS, showing that we can recover unbiased cosmological constraints even with a volume 84 times larger than the one used in this study.

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arXiv2023

Constraining νΛCDM with density-split clustering

The dependence of galaxy clustering on local density provides an effective method for extracting non-Gaussian information from galaxy surveys. The two-point correlation function (2PCF) provides a complete statistical description of a Gaussian density field. However, the late-time density field becomes non-Gaussian due to non-linear gravitational evolution and higher-order summary statistics are required to capture all of its cosmological information. Using a Fisher formalism based on halo catalogues from the Quijote simulations, we explore the possibility of retrieving this information using the density-split clustering (DS) method, which combines clustering statistics from regions of different environmental density. We show that DS provides more precise constraints on the parameters of the $νΛ$CDM model compared to the 2PCF, and we provide suggestions for where the extra information may come from. DS improves the constraints on the sum of neutrino masses by a factor of $7$ and by factors of 4, 3, 3, 6, and 5 for $Ω_{\rm m}$, $Ω_{\rm b}$, $h$, $n_s$, and $σ_8$, respectively. We compare DS statistics when the local density environment is estimated from the real or redshift-space positions of haloes. The inclusion of DS autocorrelation functions, in addition to the cross-correlation functions between DS environments and haloes, recovers most of the information that is lost when using the redshift-space halo positions to estimate the environment. We discuss the possibility of constructing simulation-based methods to model DS clustering statistics in different scenarios.

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arXiv2023

An emulator-based halo model in modified gravity -- I. The halo concentration-mass relation and density profile

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 \textsc{FORGE} and \textsc{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 $Ω_{\mathrm{m0}}, H_0, σ_8$, and one MG parameter, either $\bar{f}_{R0}$ or $r_{\mathrm{c}}$. Our halo property emulators achieve an accuracy of $\lesssim 1\%$ 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.

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