arXiv subjects

Carlton M. Baugh

Publications and source records attributed to Carlton M. Baugh.

At least 19 recordsLinked to original sources

arXiv2026

Cosmological Galaxy Formation Modelling in the Era of the Square Kilometre Array

Over the past decade, galaxy formation simulations have advanced dramatically, transforming our ability to model the interstellar medium (ISM) and predict galaxies' radio emission. Yet the challenge of bridging physical scales--from sub-parsec star formation to gigaparsec cosmic structure--remains. The Square Kilometre Array (SKA) will map the cold gas and radio continuum of galaxies across cosmic time, demanding models that couple physical realism with cosmological reach. This chapter reviews the state-of-the-art in cosmological galaxy formation modelling in preparation for the SKA. We outline progress in simulating atomic hydrogen (HI), molecular gas, and radio continuum emission from both star formation and active galactic nuclei, highlighting how cosmological hydrodynamical simulations and semi-analytic models now jointly reproduce many observed gas properties. We emphasise the need for a coordinated, ``wedding-cake'' strategy that unites simulations of different scales, for forward modelling of observables to ensure fair comparison with data, and for the integration of new technologies such as AI-driven emulators to accelerate progress. Together, these efforts will enable theoretical models to both interpret and guide SKA science, turning simulations from passive interpreters into active engines for discovery.

astro-ph.GA↗

arXiv2026

A modern halo streaming model for redshift space distortions

Accurate modelling of redshift-space distortions (RSD) in galaxy clustering is essential for extracting cosmological information from current and forthcoming large-scale structure surveys. While perturbation theory is reliable on large scales, much of the constraining power lies at intermediate and small separations, where nonlinear dynamics within and between dark matter haloes dominate. We present a halo streaming model for nonlinear galaxy clustering in redshift space that is accurate and physically interpretable. Our framework combines the streaming model for RSD with a halo-model decomposition of the galaxy clustering into central/satellite and one-/two-halo contributions. We build dedicated emulators for the key physical ingredients, trained on a suite of $N$-body simulations: halo mass functions, real-space halo two-point correlation functions, and pairwise velocity moments. By emulating these modular building blocks rather than the final redshift-space observable, this approach preserves physical transparency, enables targeted optimisation for each ingredient, and remains flexible to changes in tracer populations and galaxy-halo connection models. The resulting halo streaming model reproduces the simulated nonlinear anisotropic clustering signal down to highly nonlinear scales, while achieving the computational efficiency required for cosmological parameter inference. This framework is designed to support full-shape RSD analyses for surveys such as DESI and \textit{Euclid}, facilitating precision measurements of structure growth and tests of gravity. All codes and trained emulators are publicly available in the \href{https://github.com/chzruan/freyja}{\texttt{freyja}} repository.

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arXiv2025

The PAU Survey: Uncovering the connection between intrinsic and observed galaxy properties using symbolic regression

Estimating stellar masses for billions of galaxies in upcoming surveys requires methods that are both accurate and computationally efficient. We present a new approach using symbolic regression trained on a simulation to derive simple, explicit mathematical expressions that estimate galaxy stellar masses from basic observables: photometry and redshift. Using a mock catalogue from the GALFORM semi-analytical model that reproduces the Physics of the Accelerating Universe Survey (PAUS), we show that a linear combination of just four observables -- minimally processed $u$- and $i$- band magnitudes, observed $(g-r)$ colour, and redshift -- can recover stellar masses with accuracy comparable to traditional spectral energy distribution (SED) fitting, but with negligible computational cost. Our expressions can be evaluated instantaneously for millions of galaxies, making them ideal for next-generation surveys like LSST and Euclid. When observational errors are included, symbolic regression achieves a similar accuracy to deep neural networks while maintaining transparency. Validation against CIGALE SED fitting on PAUS data shows agreement within 0.13 dex for galaxies with $M_{*} > 10^8 M_{\odot}$. We demonstrate that the stellar mass function can be recovered at $z < 0.5$, though with distortions at the extremes: the high-mass end is overestimated by a factor of $\sim 3$ at $10^{11.5} h^{-1} M_{\odot}$ due to scatter. Our approach offers a fast, transparent alternative to traditional methods without sacrificing accuracy for the bulk of the galaxy population.

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arXiv2025

Deciphering galaxy images using machine vision -- Combining variational autoencoder and principal component analysis for feature extraction

Here, we present a machine vision approach, combining a VAE framework with PCA, to decipher galaxy images. Using mock gri-band images from the EAGLE simulation, the VAE finds that around 35 features are needed to describe the images. Adding the PCA, we identify an optimal range of 10-12 features needed to capture 99.9% of the variance in galaxy images. The exact optimal number varies with galaxy complexity: disk-dominated galaxies require 12 features, bulge-dominated galaxies need 9, and intermediate systems require 10-11 features. Correlations between extracted PCA features and structural measurements reveal that the VAE prioritizes galaxy size during reconstruction, with half-light radius strongly correlating with the highest-ranked principal components. Subsequent features capture morphology-dependent characteristics: disk-dominated galaxies emphasize size, asymmetry, and position angle; bulge-dominated systems focus on size, concentration, and axis ratio; while intermediate galaxies show enhanced attention to Sersic index, indicating greater emphasis on accurately reproducing both disk and bulge structures. The PCA process significantly reduces the entanglement of the features compared to the raw VAE latent features, decreasing the correlations with the half-light radius and the Sersic index from 14.5+-1.0 and 6.0+-1.5 features, respectively, to only 2.0+-1.0 components after PCA. Using UMAP, we construct two-dimensional visualizations that preserve neighborhood relationships from the high-dimensional feature space. This demonstrates that machine vision can effectively distinguish galaxy populations across different morphological types, including systems with atypical structures that may be overlooked by traditional classification methods, providing a data-driven complement to conventional structural measurements.

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arXiv2025

First Light And Reionisation Epoch Simulations (FLARES) XX: Comparing semi-analytic models at high-redshift

We explore how the choice of galaxy formation model affects the predicted properties of high-redshift galaxies. Using the FLARES zoom resimulation strategy, we compare the EAGLE hydrodynamics model and the GALFORM, L-Galaxies, SC-SAM and SHARK semi-analytic models (SAMs) at $5\leq z \leq 12$. The first part of our analysis examines the stellar mass functions, stellar-to-halo mass relations, star formation rates, and supermassive black hole (SMBH) properties predicted by the different models. Comparisons are made with observations, where relevant. We find general agreement between the range of predicted and observed stellar mass functions. The model predictions differ considerably when it comes to SMBH properties, with GALFORM and SHARK predicting between 1.5-3 dex more massive SMBHs ($M_{\rm BH}>10^6\ {\rm M_\odot}$) than L-Galaxies and SC-SAM, depending on redshift. The second half of our analysis focuses on passive galaxies. We show that in L-Galaxies and SC-SAM, environmental quenching of satellites is the prevalent quenching mechanism, with active galactic nuclei (AGN) feedback having little effect at the redshifts probed. On the other hand, $\sim40\%$ of passive galaxies predicted by GALFORM and SHARK are quenched by AGN feedback at $z=5$. The SAMs are an interesting contrast to the EAGLE model, in which AGN feedback is essential for the formation of passive galaxies, in both satellites and centrals, even at high redshift.

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arXiv2025

Explaining JWST counts with galaxy formation models

A distinct power-law break is apparent m_AB approximately 21 in the deep Near-Infrared PEARLS-JWST galaxy counts. The break becomes more pronounced at longer wavelengths, with the counts slope flattening smoothly with apparent magnitude in the shortest band used at 0.9 microns, trending towards an increasingly broken slope by the longest wavelength passband of JWST NIRCam, 4.4 microns. This behaviour is remarkably well predicted by the GALFORM semi-analytical model of galaxy formation. We use the model to diagnose the origin of this behaviour. We find that the features that are responsible for the break are: 1) the inherent break in the luminosity function; 2) the change in the volume element with redshift and 3) the redshift-dependent nature of the k-correction. We study the contribution to these effects by early and late-type galaxies, using as a proxy for morphology the bulge-to-total stellar mass ratio. We find that the way in which ellipticals populate the bright end of the luminosity function while spirals dominate the faint end is preserved in the galaxy number counts, with a characteristic stellar mass at the break of approximately 10^10 M_sun. We also find that the shape of the number counts is mainly driven by galaxies with relatively low redshift (z < 2) for the PEARLS observational limit of m_AB < 28. We give a comprehensive description of why the galaxy number counts in the near-infrared PEARLS-JWST observation look the way they do and which population of galaxies is dominant at each apparent magnitude.

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arXiv2025

The diverse star formation histories of early massive, quenched galaxies in modern galaxy formation simulations

We present a comprehensive study of the star formation histories of massive-quenched galaxies at $z=3$ in 3 semi-analytic models (SHARK, GAEA, GALFORM) and 3 cosmological hydrodynamical simulations (EAGLE, IllustrisTNG, Simba). We study the predicted number density and stellar mass function of massive-quenched galaxies, their formation and quenching timescales and star-formation properties of their progenitors. Predictions are disparate in all these diagnostics, for instance: (i) some simulations reproduce the observed number density of very massive-quenched galaxies ($>10^{11}\rm M_{\odot}$) but underpredict the high density of intermediate-mass ones, while others fit well the lower masses but underpredict the higher ones; (ii) In most simulations, except for GAEA and EAGLE, most massive-quenched galaxies had starburst periods, with the most intense ones happening at $4 300\rm M_{\odot}\,yr^{-1}$; (iii) quenching timescales are in the range $\approx 20-150$~Myr depending on the simulation; among other differences. These disparate predictions can be tied to the adopted Active Galactic Nuclei (AGN) feedback model. For instance, the explicit black-hole (BH) mass dependence to trigger the "radio mode" in IllustrisTNG and Simba makes it difficult to produce quenched galaxies with intermediate stellar masses, also leading to higher baryon collapse efficiencies ($\approx 15-30$%); while the strong bolometric luminosity dependence of the AGN outflow rate in GAEA leads to BHs of modest mass quenching galaxies. Current observations are unable to distinguish between these different predictions due to the small sample sizes. However, these predictions are testable with current facilities and upcoming observations, allowing a "true physics experiment" to be carried out.

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arXiv2024

ANNZ+: an enhanced photometric redshift estimation algorithm with applications on the PAU Survey

ANNZ is a fast and simple algorithm which utilises artificial neural networks (ANNs), it was known as one of the pioneers of machine learning approaches to photometric redshift estimation decades ago. We enhanced the algorithm by introducing new activation functions like tanh, softplus, SiLU, Mish and ReLU variants; its new performance is then vigorously tested on legacy samples like the Luminous Red Galaxy (LRG) and Stripe-82 samples from SDSS, as well as modern galaxy samples like the Physics of the Accelerating Universe Survey (PAUS). This work focuses on testing the robustness of activation functions with respect to the choice of ANN architectures, particularly on its depth and width, in the context of galaxy photometric redshift estimation. Our upgraded algorithm, which we named ANNZ+, shows that the tanh and Leaky ReLU activation functions provide more consistent and stable results across deeper and wider architectures with > 1 per cent improvement in root-mean-square error ($σ_{\textrm{RMS}}$) and 68th percentile error ($σ_{68}$) when tested on SDSS data sets. While assessing its capabilities in handling high dimensional inputs, we achieved an improvement of 11 per cent in $σ_{\textrm{RMS}}$ and 6 per cent in $σ_{68}$ with the tanh activation function when tested on the 40-narrowband PAUS dataset; it even outperformed ANNZ2, its supposed successor, by 44 per cent in $σ_{\textrm{RMS}}$. This justifies the effort to upgrade the 20-year-old ANNZ, allowing it to remain viable and competitive within the photo-z community today. The updated algorithm ANNZ+ is publicly available at https://github.com/imdadmpt/ANNzPlus.

astro-ph.IM↗

arXiv2024

A comparison of pre-existing $Λ$CDM predictions with the abundance of {\it JWST} galaxies at high redshift

Observations with the {\it James Webb Space Telescope} have revealed a high abundance of bright galaxies at redshift, $z\gtrsim 12$, which has been widely interpreted as conflicting with the $Λ$CDM model. In Cowley et al. (2018) predictions were made -- prior to the {\it JWST} observations -- for the expected abundance of these galaxies using the Durham semi-analytic galaxy formation model, {\sc galform}, which is known to produce a realistic population of galaxies at lower redshifts including the present day. Key to this model is the assumption of a ``top-heavy" initial mass function of stars formed in bursts (required to explain the number counts and redshift distribution of sub-millimetre galaxies). Here, we compare the rest-frame ultraviolet luminosity functions derived from {\it JWST} observations with those predicted by the Cowley et al. model up to $z=14$ and make further predictions for $z=16$. We find that below $z\sim 10$, the Cowley et al. predictions agree very well with observations, while agreement at $z\gtrsim12$ requires extending the model to take into account the timescale for the growth of obscuring dust grains at these very early times and its dependence on gas metallicity. We trace the evolution of these galaxies from $z=14$ to $z=0$ and find that their descendants typically reside in halos with a median mass $2.5\times 10^{13}\,h^{-1}\,\mathrm{M_{\odot}}$. The stellar masses of the descendants range from $3.2\times 10^{6}\,h^{-1}\,\mathrm{M_{\odot}}$ to $3.2\times 10^{11}\,h^{-1}\,\mathrm{M_{\odot}}$. Although these galaxies were all central galaxies at $z=14$, over half of their descendants end up as satellites in massive halos.

astro-ph.GA↗

arXiv2024

The PAU Survey: galaxy stellar population properties estimates with narrowband data

Narrowband galaxy surveys have recently gained interest as a promising method to achieve the necessary accuracy on the photometric redshift estimate of individual galaxies for stage-IV cosmological surveys. One key advantage is the ability to provide higher spectral resolution information about galaxies that should allow a more accurate and precise estimation of galaxy stellar population properties. However, the impact of adding narrow-band photometry on the stellar population properties estimate is largely unexplored. The scope of this work is two-fold: on one side, leveraging the predictive power of broad-band and narrow-band data to infer galaxy physical properties such as stellar masses, ages, star formation rates and metallicities. On the other hand, evaluating the improvement of performance in estimating galaxy properties when we use narrow-band data instead of broad-band. In this work we measure the stellar population properties of a sample of galaxies in the COSMOS field for which both narrowband and broadband data are available. In particular, we employ narrowband data from PAUS and broad-band data from CFHTLS. We use two different spectral energy distribution fitting codes to measure galaxy properties, namely CIGALE and Prospector. We find that the increased spectral resolution of narrow-band photometry does not yield a substantial improvement on constraining galaxy properties using spectral energy distribution fitting. Still we find that we obtain a more diverse distribution of metallicities and dust optical depths with cigale when employing the narrowband data. The effect is not as prominent as expected, which we relate this to the low narrowband SNR of a majority of the galaxies, the respective drawbacks of both codes as well as the coverage only in the optical regime. The measured properties are afterwards compared to the COSMOS2020 catalogue, showing good agreement.

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arXiv2024

The Uchuu-GLAM BOSS and eBOSS LRG lightcones: Exploring clustering and covariance errors

This study investigates the clustering and bias of Luminous Red Galaxies (LRG) in the BOSS-LOWZ, -CMASS, -COMB, and eBOSS samples, using two types of simulated lightcones: (i) high-fidelity lightcones from Uchuu $N$-body simulation, employing SHAM technique to assign LRG to (sub)halos, and (ii) 16000 covariance lightcones from GLAM-Uchuu $N$-body simulations, including LRG using HOD data from Uchuu. Our results indicate that Uchuu and GLAM lightcones closely replicate BOSS/eBOSS data, reproducing correlation function and power spectrum across scales from redshifts $0.2$ to $1.0$, from $2$ to $150\,h^{-1}\mathrm{Mpc}$ in configuration space, from $0.005$ to $0.7\,h\mathrm{Mpc}^{-1}$ in Fourier space, and across different LRG stellar masses. Furthermore, comparing with existing MD-Patchy and EZmock BOSS/eBOSS lightcones based on approximate methods, our GLAM-Uchuu lightcones provide more precise clustering estimates. We identify significant deviations from observations within $20\,h^{-1}\mathrm{Mpc}$ scales in MD-Patchy and EZmock, with our covariance matrices indicating that these methods underestimate errors by between $10\%$ and $60\%$. Lastly, we explore the impact of cosmology on galaxy clustering. Our findings suggest that, given the current level of uncertainties in BOSS/eBOSS data, distinguishing models with and without massive neutrino effects on LSS is challenging. This paper highlights the Uchuu and GLAM-Uchuu simulations' robustness in verifying the accuracy of Planck cosmological parameters, providing a strong foundation for enhancing lightcone construction in future LSS surveys. We also demonstrate that generating thousands of galaxy lightcones is feasible using $N$-body simulations with adequate mass and force resolution.

astro-ph.CO↗

arXiv2024

Understanding the radio luminosity function of star-forming galaxies and its cosmological evolution

We explore the redshift evolution of the radio luminosity function (RLF) of star-forming galaxies using GALFORM, a semi-analytic model of galaxy formation and a dynamo model of the magnetic field evolving in a galaxy. Assuming energy equipartition between the magnetic field and cosmic rays, we derive the synchrotron luminosity of each sample galaxy. In a model where the turbulent speed is correlated with the star formation rate, the RLF is in fair agreement with observations in the redshift range $0 \leq z \leq 2$. At larger redshifts, the structure of galaxies, their interstellar matter and turbulence appear to be rather different from those at $z\lesssim2$, so that the turbulence and magnetic field models applicable at low redshifts become inadequate. The strong redshift evolution of the RLF at $0 \leq z \leq 2$ can be attributed to an increased number, at high redshift, of galaxies with large disc volumes and strong magnetic fields. On the other hand, in models where the turbulent speed is a constant or an explicit function of $z$, the observed redshift evolution of the RLF is poorly captured. The evolution of the interstellar turbulence and outflow parameters appear to be major (but not the only) drivers of the RLF changes. We find that both the small- and large-scale magnetic fields contribute to the RLF but the small-scale field dominates at high redshifts. Polarisation observations will therefore be important to distinguish these two components and understand better the evolution of galaxies and their nonthermal constituents.

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arXiv2024

A new test of gravity -- II: Application of marked correlation functions to luminous red galaxy samples

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

astro-ph.CO↗

arXiv2024

A new test of gravity -- I: Introduction to the method

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

astro-ph.CO↗

arXiv2023

Galaxy evolution in modified gravity simulations: using passive galaxies to constrain gravity with upcoming surveys

We present a quantitative analysis of the properties of galaxies and structures evolving in universes dominated by different modified gravitational models, including two variants of the f(R)-gravity (F) and two of the Dvali-Gabdadze-Poratti (N) braneworld model, which respectively feature the chameleon and Vainshtein screening mechanisms. Using the Simulation HYdrodynamics BeyONd Einstein (SHYBONE) cosmological hydrodynamical full-physics simulations suite, we study the departures in the properties of galaxies residing in different environments with respect to the standard model (GR). Using two different criteria to compare, we find that structures formed within modified gravity tend to show a denser gas density profile than their GR counterparts. Within the different modified gravity models, N1 and F5 gravity models show greater departures from the standard model, with gas density profiles $ρ_{\rm IGM} \geq 30\%$ denser in the outskirts for the N1 model, and in the inner parts for the F5 model. Additionally, we find that haloes evolving in MG universes show, in general, larger quenched fractions than GR, reaching up to $20\%$ larger quenching fractions in F5 regardless of the stellar mass of the galaxy. With respect to the other models, F6, N1 and N5 show slightly larger quenched fractions, but no strong differences can be found. These results directly impact the colour distribution of galaxies, making them in MG models redder and older than their GR counterparts. Like GR, once the environment starts to play a role, galaxies rapidly get quenched and the differences between models vanish.

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arXiv2023

How limiting is optical follow-up for fast radio burst applications? Forecasts for radio and optical surveys

Fast radio bursts (FRBs) are the first cosmological radio sources that vary on millisecond timescales, which makes them a unique probe of the Universe. Many proposed applications of FRBs require associated redshifts. These can only be obtained by localizing FRBs to their host galaxies and subsequently measuring their redshifts. Upcoming FRB surveys will provide arcsecond localization for many FRBs, not all of which can be followed up with dedicated optical observations. We aim to estimate the fraction of FRB hosts that will be catalogued with redshifts by existing and future optical surveys. We use the population synthesis code frbpoppy to simulate several FRB surveys, and the semi-analytical galaxy formation code GALFORM to simulate their host galaxies. We obtain redshift distributions for the simulated FRBs and the fraction with host galaxies in a survey. Depending on whether FRBs follow the cosmic star formation rate or stellar mass, 20 to 40 per cent of CHIME FRB hosts will be observed in an SDSS-like survey, all at $z<0.5$. The deeper DELVE survey will detect 63 to 85 per cent of ASKAP FRBs found in its coherent search mode. CHIME FRBs will reach $z\sim 3$, SKA1-Mid FRBs $z\sim 5$, but ground based follow-up is limited to $z\lesssim 1.5$. We discuss consequences for several FRB applications. If $\sim1/2$ of ASKAP FRBs have measured redshifts, 1000 detected FRBs can be used to constrain $Ω_\text{b} h_{70}$ to within $\sim10$ per cent at 95 per cent credibility. We provide strategies for optimized follow-up, when building on data from existing surveys. Data and codes are made available.

astro-ph.HE↗

arXiv2023

A machine learning approach to mapping baryons onto dark matter haloes using the EAGLE and C-EAGLE simulations

High-resolution cosmological hydrodynamic simulations are currently limited to relatively small volumes due to their computational expense. However, much larger volumes are required to probe rare, overdense environments, and measure clustering statistics of the large scale structure. Typically, zoom simulations of individual regions are used to study rare environments, and semi-analytic models and halo occupation models applied to dark matter only (DMO) simulations are used to study the Universe in the large-volume regime. We propose a new approach, using a machine learning framework to explore the halo-galaxy relationship in the periodic EAGLE simulations, and zoom C-EAGLE simulations of galaxy clusters. We train a tree based machine learning method to predict the baryonic properties of galaxies based on their host dark matter halo properties. The trained model successfully reproduces a number of key distribution functions for an infinitesimal fraction of the computational cost of a full hydrodynamic simulation. By training on both periodic simulations as well as zooms of overdense environments, we learn the bias of galaxy evolution in differing environments. This allows us to apply the trained model to a larger DMO volume than would be possible if we only trained on a periodic simulation. We demonstrate this application using the $(800 \; \mathrm{Mpc})^3$ P-Millennium simulation, and present predictions for key baryonic distribution functions and clustering statistics from the EAGLE model in this large volume.

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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.

astro-ph.CO↗