arXiv subjects

Baojiu Li

Publications and source records attributed to Baojiu Li.

At least 19 recordsLinked to original sources

arXiv2026

Impact of galaxy intrinsic alignments on non-Gaussian weak lensing statistics for modified gravity

Non-Gaussian weak lensing statistics improve the constraining power of cosmic shear data by harvesting information unavailable to two-point statistics, within and beyond the GR+$Λ$CDM scenario. Dark energy, total neutrino mass and deviations from GR have all been shown to be better measured with non-Gaussian lensing probes, in simplified conditions. Previous studies typically overlook the impact of secondary lensing signals, which can be large and therefore can significantly affect the conclusions. Here we investigate the impact on measurements of cosmological and modified gravity parameters in the presence of galaxy intrinsic alignments. We focus on the power spectra, lensing PDF, peaks and minima counts, void abundance and void profiles. These non-Gaussian statistics are measured from the MGLenS mock weak lensing maps, in which three cosmological parameters and one gravitational parameter are varied, either in the $f(R)$ or nDGP scenario, assuming Stage-IV lensing survey precision. These simulations are infused with the non-linear linear alignment model, allowing us to build emulators for each statistic with or without IA, and to study biases in full MCMC analyses. We show that in the absence of IA, lensing void profiles and abundance generally yield the highest Figure of Merit in the $S_8 - f_{R0}$ and $S_8 - H_0 r_{\rm c}$ planes, at times improving by an order of magnitude over two-point functions. When IA is unaccounted for, major parameter biases are observed in the cosmology sector, while the modified gravity sector is relatively unaffected. We find that these biases can generally be flagged from poor goodness-of-fit measurements, except for a few cases where IA can fully masquerade as a lower $Ω_{\rm m}$ and lower $S_8$ cosmology.

astro-ph.CO↗

arXiv2026

Galaxy formation in modified gravity -- II. galaxy halo connection and assembly bias

Modern surveys such as DESI and \textit{Euclid}, which collect data for hundreds of millions of galaxies to map the large-scale structure (LSS) of the Universe, hold the key to determining the cosmological parameters and testing new physics. This ambition, however, is limited by uncertainties in the galaxy-halo connection: the link between observed galaxies and the underlying, unobservable matter field, by accounting for effects such as galaxy bias and assembly bias (AB). These are particularly poorly-understood for modified gravity (MG) models, which are popular alternatives to the cosmological constant to explain accelerated expansion. We approach this problem using mock emission line galaxy (ELG) and luminous red galaxy (LRG) catalogues in $f(R)$ gravity matching the specifications of ongoing Stage-IV galaxy surveys, generated from state-of-the-art MG hydrodynamical simulations. While the interplay between MG -- especially the chameleon screening mechanism -- and galaxy formation leaves complicated imprints in the galaxy-halo connection, a simple physical picture emerges in which halo and galaxy formation are enhanced for progressively more massive haloes over time. We confirm that the basic galaxy-halo connection model, the halo occupation distribution (HOD), in which galaxy occupation is determined solely by halo mass, underestimates galaxy clustering strength in $Λ$CDM by $10$--$20\%$ at $z\lesssim1$ when neglecting AB, and demonstrate that MG introduces further complexity. Extending this model with a suitably-chosen environment density as a secondary HOD variable reduces the AB effect in all models to $2$--$3\%$ for $z\lesssim0.5$. This provides a well-motivated starting point for further works on minimising the impact of AB when testing non-standard cosmological models with LSS.

astro-ph.CO↗

arXiv2026

N-body Simulations of Large-Scale Structure in the Generalized Cubic Covariant Galileon Model

We present the first N-body simulations of structure formation in the Generalized Cubic Covariant Galileon (GCCG) model. This theory extends the cubic covariant Galileon through power-law kinetic and cubic derivative interactions and admits tracker solutions leading to late-time cosmic acceleration. Previous studies of GCCG have mostly focused on the background, linear perturbations, or semi-analytic nonlinear prescriptions. Here we implement the nonlinear scalar-field equation in the ECOSMOG adaptive-mesh refinement code, allowing us to follow the coupled evolution of matter clustering and Vainshtein screening in the fully nonlinear regime. We quantify the impact of GCCG on the nonlinear matter power spectrum and compare the simulation results with predictions from the halo-model reaction approach. For the parameter choices considered, the GCCG model enhances the matter power spectrum relative to the corresponding QCDM cosmology, with the effect increasing towards low redshift and reaching approximately $7\%$ at $z=0$ in the transition to the nonlinear regime. At smaller scales, the enhancement decreases as a consequence of Vainshtein screening. We find that the reaction framework captures the qualitative behaviour of the simulations, while residual differences appear on deeply nonlinear scales. We also analyse the abundance of dark matter haloes, finding an enhancement relative to QCDM that becomes more pronounced towards lower redshift and in the high-mass tail. These simulations provide the first nonlinear calibration of structure formation in GCCG and establish the range of validity of efficient semi-analytical predictions for applications to forthcoming large-scale-structure surveys.

astro-ph.CO↗

arXiv2026

EFT-Ramses: a code to simulate the effective field theory of dark energy

While the standard $Λ$CDM paradigm is in excellent agreement with most current cosmological observations, theoretical challenges surrounding the cosmological constant ($Λ$) have strongly motivated the exploration of dynamical dark energy (DE) and modified gravity (MG) models. Investigating the physical nature of the cosmic acceleration requires N-body simulations to probe the non-linear growth of cosmic structure and prepare for the high-precision data from Stage-IV surveys. In this paper, we present EFT-RAMSES, a comprehensive extension of the ECOSMOG cosmological simulation code designed to explore non-linear structure formation in DE and MG scenarios. We embed the effective field theory of dark energy (EFTofDE) framework into this new numerical pipeline, utilising the $α$-basis parameterisation to provide a versatile, model-agnostic, computational engine. By consolidating diverse scalar and vector-tensor theories---including the normal and self-accelerating Dvali-Gabadadze-Porrati (DGP) models, cubic Galileons (cubic scalar Galileon (csG), cubic vector Galileon (cvG) and generalised cubic covariant Galileon (GCCG)), and generic effective field theory (EFT) parameterisation---into a single "master" Vainshtein equation, this pipeline bypasses the need for model-specific solvers and easily specialises to any particular model. As validations, we perform high-resolution N-body simulations for the normal-branch DGP (nDGP), csG, GCCG, and EFT models, comparing the resulting matter power spectra against dependent and independent codes such as legacy ECOSMOG and HiCOLA, as well as linear theory, and find excellent agreement. EFT-RAMSES provides a robust and versatile computational tool for precision cosmological tests of DE and MG using upcoming cosmological surveys. The code is available for download from the GitHub EFT-RAMSES repository.

astro-ph.CO↗

arXiv2026

Non-linear Structure Formation in Planck+DESI Favoured Interacting Dark Energy Cosmologies

Following our previous work constraining interacting dark energy (IDE) models, which showed their potential to alleviate the Hubble tension, in this work we investigate the non-linear effects of the IDE scenario favoured by CMB and DESI observations. The implications of IDE for the $S_8$ tension remain unclear, since current weak-lensing and large-scale-structure analyses either exclude highly non-linear scales or model the non-linear regime using prescriptions calibrated within $Λ$CDM. We address this issue by implementing a fully self-consistent IDE pipeline. We perform N-body simulations of the IDE model with a transfer rate $Q=ξ{\cal H}ρ_x$ using a modified implementation of RAMSES. Since the dark matter Euler equation remains unchanged with respect to $Λ$CDM, the interaction can be incorporated through the modified background evolution and an effective time-dependent dark matter particle mass. We find scale-dependent deviations in the quasi-linear and non-linear regimes of the matter power spectrum, together with modifications to the density-field morphology and halo abundance. Our results show that the impact of IDE on quasi-linear and non-linear structure formation cannot be captured by standard $Λ$CDM-calibrated prescriptions, highlighting the importance of model-consistent non-linear modelling for future weak-lensing and large-scale-structure constraints on interacting dark energy cosmologies.

astro-ph.CO↗

arXiv2026

Biased tracers, Hybrid Effective Field Theory and Modified Gravity

The modelling of the power spectrum of biased tracers has become a central topic in the analysis of modern cosmological galaxy surveys. Perturbative templates formulated in both Eulerian and Lagrangian frameworks have been extensively developed over the last decades, with their implementation in $Λ$CDM thoroughly investigated and validated. In parallel, approaches combining perturbation theory with the output of dark-matter-only simulations have emerged as powerful tools for modelling the nonlinear regime, most notably the Hybrid Effective Field Theory (HEFT) framework~\cite{Modi:2019qbt}. In this work, we discuss the perturbative biased expansion within the local Lagrangian bias scheme and its implementation in the HEFT framework for modified gravity cosmologies. We focus on $f(R)$ gravity, a theory characterized by scale-dependent growth and chameleon screening, making it one of the most challenging scenarios for the computation of Lagrangian Perturbation Theory growth functions and for the generation of accurate numerical simulations. We present a detailed overview of the ingredients required to compute loop-corrected biased power spectra analytically and compare these predictions against fully non-perturbative simulation results. Finally, we propose a strategy to extend existing HEFT-based $Λ$CDM emulators, such as \texttt{bacco} and \texttt{Aemulus}, to beyond-$Λ$CDM cosmologies.

astro-ph.CO↗

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.

astro-ph.CO↗

arXiv2026

Illuminating the Physics of Cosmic Origin and Evolution: A UK Space Frontiers 2035 White Paper

Understanding the Universe's origins and evolution remains one of the most fundamental challenges in modern cosmology. This white paper explores three key science priorities in this field: unravelling the physics of cosmic inflation, investigating the accelerating expansion of the Universe, and precisely measuring the sum of the neutrino masses. Achieving these goals requires a dedicated survey to map the large-scale structure at high redshift in unprecedented detail. We describe how this can be achieved through a mission concept called SIRMOS, providing a high-throughput, highly multiplexed spectroscopic capability to obtain accurate redshifts for over 100 million galaxies over a wide sky area. Such a survey would leverage the deepest existing wide-area photometric catalogues for targeting, with spectra offering continuous 1.25-2.5~$μ$m wavelength coverage at moderate resolution, allowing precise redshift measurements in the $1<z<4$ range with minimal bias. We outline the scientific opportunities this presents. Recent years have seen significant advances in instrumentation, including digital micromirror devices, complex telescope mirrors, large detector arrays, and data processing pipelines. While these technologies have been demonstrated in terrestrial applications, such a survey is a unique opportunity to apply these proven capabilities in space to address fundamental questions in cosmology. Participation in such a mission will simultaneously deliver a compelling science case, help align UK Space Agency and STFC strategies, demonstrate the UK's growing capability in end-to-end space missions, and strengthen the national space economy through high-value industrial participation.

astro-ph.IM↗

arXiv2025

Nonlinear reconstruction of general dark energy theories

The large variety and number of dark energy (DE) theories make it impractical to perform detailed analyses on a case-by-case basis, which has motivated proposals to ``parameterize" theories to reduce the size of theory space. The leading approach to do this is the effective field theory of dark energy (EFTofDE), which can describe general Horndeski-type theories with a small number of observationally accessible time-dependent functions. However, the EFTofDE primarily works for linear perturbations, and extending it to obtain a fully non-linear description of DE theories, which is critical for theories with screening mechanisms, is challenging. In this paper, we present a general method for reconstructing the non-linear DE Lagrangian from the background expansion history and certain linear-perturbation quantities, building upon the EFTofDE framework. Using numerical examples, we demonstrate that this method is applicable to a wide range of single-scalar-field dark energy and modified gravity theories, including quintessence, scalar-tensor theory, $k$-essence, and generalized cubic Galileon with shift symmetry. For each of these theories, we discuss the validity of the method and factors affecting its results. While this method involves solving differential equations, we find that the initial conditions are not important for quintessence, scalar-tensor theory and $k$-essence, while for shift-symmetric cubic Galileon, the generic tracker solution can help transform differential equations into algebraic equations. This offers a useful framework to connect cosmological observations at the background and linear-perturbation levels to the underlying non-linear dynamics of dark energy, and will enable cosmological simulations to analyze and examine DE theories systematically and in much greater detail.

astro-ph.CO↗

arXiv2025

The Poisson noise in modeling the redshift-space distortion at large scales

We investigate the errors in modeling the redshift-space distortion (RSD) effect at large linear scales, using data from the Millennium simulation. While standard theoretical templates, such as the Kaiser formula and the TNS method, could precisely model RSD for individual large-scale modes, we find that for tracers with number densities lower than $\sim10^{-3}({\rm Mpc}/h)^{-3}$, there is a few-percent level bias in the predicted power spectrum. This error arises due to the amplification of intrinsic Poisson noise during RSD modeling from real-space power spectrum. This amplified noise can be analytically expressed as $1 + ε/[{\bar{n}P}({1+ε})]$, with $ε=2β/3+β^2/5$, where $P$ denotes the real-space tracer power spectrum and $β\equiv f/b$. Specifically, for halos with a number density of around $5\times10^{-4}({\rm Mpc}/h)^{-3}$, this phenomenon results in an additional systematic error of 2.5\%. Our result suggests that caution is necessary when directly modeling redshift-space distortions (RSD) using real-space power spectra of tracers obtained from simulations or actual surveys. This caution is particularly pertinent in scenarios where emulators trained on simulation data forecast the real-space tracer power spectrum, as well as in baryon acoustic oscillation (BAO) reconstruction using galaxy samples, for which we estimate that shot noise could introduce random errors of about one-third in the displacement field, potentially diminishing the effectiveness of the BAO peak sharpening.

astro-ph.CO↗

arXiv2025

Fast Higher-Order Interpolation and Restriction in ExaHyPE Avoiding Non-physical Reflections

Wave equations help us to understand phenomena ranging from earthquakes to tsunamis. These phenomena materialise over very large scales. It would be computationally infeasible to track them over a regular mesh. Yet, since the phenomena are localised, adaptive mesh refinement (AMR) can be used to construct meshes with a higher resolution close to the regions of interest. ExaHyPE is a software engine created to solve wave problems using AMR, and we use it as baseline to construct our numerical relativity application called ExaGRyPE. To advance the mesh in time, we have to interpolate and restrict along resolution transitions in each and every time step. ExaHyPE's vanilla code version uses a d-linear tensor-product approach. In benchmarks of a stationary black hole this performs slowly and leads to errors in conserved quantities near AMR boundaries. We therefore introduce a set of higher-order interpolation schemes where the derivatives are calculated at each coarse grid cell to approximate the enclosed fine cells. The resulting methods run faster than the tensor-product approach. Most importantly, when running the stationary black hole simulation using the higher order methods the errors near the AMR boundaries are removed.

cs.CE↗

arXiv2025

Negative neutrino masses as a mirage of dark energy

The latest cosmological constraints on the sum of the neutrino masses depend on prior physical assumptions about the mass spectrum. To test the accordance of cosmological and laboratory constraints in the absence of such priors, we introduce an effective neutrino mass parameter that extends consistently to negative values. For the $Λ$CDM model, we analyze data from Planck, ACT, and DESI and find a $2.8-3.3σ$ tension with the constraints from oscillation experiments. Motivated by recent hints of evolving dark energy, we analyze the $w_0w_a$ and mirage dark energy models, showing that they favour larger masses consistent with laboratory data, respectively $\sum m_{ν,\mathrm{eff}} = 0.06_{-0.10}^{+0.15}\,\mathrm{eV}$ and $\sum m_{ν,\mathrm{eff}} = 0.04_{-0.11}^{+0.15}\,\mathrm{eV}$ (both at 68%).

astro-ph.CO↗

arXiv2025

The FLAMINGO project: the coupling between baryonic feedback and cosmology in light of the $S_8$ tension

Large-scale structure surveys have reported measurements of the density of matter, $Ω_\mathrm{m}$, and the amplitude of clustering, $σ_8$, that are in tension with the values inferred from observations of the cosmic microwave background. While this may be a sign of new physics that slows the growth of structure at late times, strong astrophysical feedback processes could also be responsible. In this work, we argue that astrophysical processes are not independent of cosmology and that their coupling naturally leads to stronger baryonic feedback in cosmological models with suppressed structure formation or when combined with a mechanism that removes dark matter from halos. We illustrate this with two well-motivated extensions of the Standard Model known to suppress structure formation: massive neutrinos and decaying dark matter. Our results, based on the FLAMINGO suite of hydrodynamical simulations, show that the combined effect of baryonic and non-baryonic suppression mechanisms is greater than the sum of its parts, particularly for decaying dark matter. We also show that the dependence of baryonic feedback on cosmology can be modelled as a function of the ratio $f_\mathrm{b}/c^2_\mathrm{v}\sim f_\mathrm{b}/(Ω_\mathrm{m}σ_8)^{1/4}$ of the universal baryon fraction, $f_\mathrm{b}$, to a velocity-based definition of halo concentration, $c^2_\mathrm{v}$, giving an accurate fitting formula for the baryonic suppression of the matter power spectrum. Although the combination of baryonic and non-baryonic suppression mechanisms can resolve the tension, the models with neutrinos and decaying dark matter are challenged by constraints on the expansion history.

astro-ph.CO↗

arXiv2024

Emulation of $f(R)$ modified gravity from $Λ$CDM using conditional GANs

A major aim of cosmological surveys is to test deviations from the standard $Λ$CDM model, but the full scientific value of these surveys will only be realised through efficient simulation methods that keep up with the increasing volume and precision of observational data. $N$-body simulations of modified gravity (MG) theories are computationally expensive since highly non-linear equations must be solved. This represents a significant bottleneck in the path to reach the data volume and resolution attained by equivalent $Λ$CDM simulations. We develop a field-level neural network-based emulator that generates density and velocity divergence fields under the $f(R)$ gravity MG model from the corresponding $Λ$CDM simulated fields. Using attention mechanisms and a complementary frequency-based loss function, our model is able to learn this intricate mapping. We use the idea of latent space extrapolation to generalise our emulator to $f(R)$ models with differing field strengths. The predictions of our emulator agree with the $f(R)$ simulations to within 5% for matter density and to within 10% for velocity divergence power spectra up to $k \sim 2\,h$ $\mathrm{Mpc}^{-1}$. But for a few select cases, higher-order statistics are reproduced with $\lesssim$10% agreement. Latent extrapolation allows our emulator to generalise to different parameterisations of the $f(R)$ model without explicitly training on those variants. Given a $Λ$CDM simulation, the GPU-based emulator can reproduce the equivalent $f(R)$ realisation $\sim$600 times faster than full $N$-body simulations. This lays the foundations for a valuable tool for realistic yet rapid mock field generation and robust cosmological analyses.

astro-ph.CO↗

arXiv2024

ExaGRyPE: Numerical General Relativity Solvers Based upon the Hyperbolic PDEs Solver Engine ExaHyPE

ExaGRyPE describes a suite of solvers for numerical relativity, based upon ExaHyPE 2, the second generation of our Exascale Hyperbolic PDE Engine. The presented generation of ExaGRyPE solves the Einstein equations in the CCZ4 formulation under a 3+1 foliation and focuses on black hole spacetimes. It employs a block-structured Cartesian grid carrying a higher-order order Finite Difference scheme with adaptive mesh refinement, it facilitates massive parallelism combining message passing, domain decomposition and task parallelism, and it supports the injection of particles into the grid as data probes or tracers. We introduce the ExaGRyPE-specific building blocks within ExaHyPE 2, and discuss its software architecture and compute-n-feel: For this, we formalize the creation of any specific simulation with ExaGRyPE as a sequence of lowering operations, where abstract logical tasks are successively broken into finer tasks until we obtain an abstraction level that can be mapped onto a C++ executable. The overall program logic is fully specified via a domain-specific Python interface, we map this logic onto a more detailed set of numerical tasks, subsequently lower this representation onto technical tasks that the underlying ExaHyPE engine uses to parallelize the application, before eventually the technical tasks are mapped onto task graphs including the actual PDE term evaluations, initial conditions, boundary conditions, and so forth. We end up with a rigorous separation of concerns which shields ExaGRyPE users from technical details and hence simplifies the development of novel physical models. We present the simulations and data for the gauge wave, static single black holes and rotating binary black hole systems, demonstrating that the code base is mature and usable. However, we also uncover domain-specific numerical challenges that need further study by the community in future work.

gr-qc↗

arXiv2024

Constraining modified gravity with weak lensing peaks

It is well established that maximizing the information extracted from upcoming and ongoing stage-IV weak-lensing surveys requires higher-order summary statistics that complement the standard two-point statistics. In this work, we focus on weak-lensing peak statistics to test two popular modified gravity models, $f(R)$ and nDGP, using the FORGE and BRIDGE weak-lensing simulations, respectively. From these simulations we measure the peak statistics as a function of both cosmological and modified gravity parameters simultaneously. Our findings indicate that the peak abundance is sensitive to the strength of modified gravity, while the peak two-point correlation function is sensitive to the nature of the screening mechanism in a modified gravity model. We combine these simulated statistics with a Gaussian Process Regression emulator and a Gaussian likelihood to generate stage-IV forecast posterior distributions for the modified gravity models. We demonstrate that, assuming small scales can be correctly modelled, peak statistics can be used to distinguish GR from $f(R)$ and nDGP models at the two-sigma level with a stage-IV survey area of $300 \, \rm{deg}^2$ and $1000 \, \rm{deg}^2$, respectively. Finally, we show that peak statistics can constrain $\log_{10}\left(|f_{R0}|\right) = -6$ to 2\% precision, and $\log_{10}(H_0 r_c) = 0.5$ to 25\% precision.

astro-ph.CO↗

arXiv2024

Estimation of line-of-sight velocities of individual galaxies using neural networks I. Modelling redshift-space distortions at large scales

We present a scheme based on artificial neural networks (ANN) to estimate the line-of-sight velocities of individual galaxies from an observed redshift-space galaxy distribution. We find an estimate of the peculiar velocity at a galaxy based on galaxy counts and barycenters in shells around it. By training the network with environmental characteristics, such as the total mass and mass center within each shell surrounding every galaxy in redshift space, our ANN model can accurately predict the line-of-sight velocity of each individual galaxy. When this velocity is used to eliminate the RSD effect, the two-point correlation function (TPCF) in real space can be recovered with an accuracy better than 1% at $s$ > 8 $h^{-1}\mathrm{Mpc}$, and 4% on all scales compared to ground truth. The real-space power spectrum can be recovered within 3% on $k$< 0.5 $\mathrm{Mpc}^{-1}h$, and less than 5% for all $k$ modes. The quadrupole moment of the TPCF or power spectrum is almost zero down to $s$ = 10 $h^{-1}\mathrm{Mpc}$ or all $k$ modes, indicating an effective correction of the spatial anisotropy caused by the RSD effect. We demonstrate that on large scales, without additional training with new data, our network is adaptable to different galaxy formation models, different cosmological models, and mock galaxy samples at high redshifts and high biases, achieving less than 10% error for scales greater than 15 $h^{-1}\mathrm{Mpc}$. As it is sensitive to large-scale densities, it does not manage to remove Fingers of God in large clusters, but works remarkably well at recovering real-space galaxy positions elsewhere. Our scheme provides a novel way to predict the peculiar velocity of individual galaxies, to eliminate the RSD effect directly in future large galaxy surveys, and to reconstruct the 3-D cosmic velocity field accurately.

astro-ph.CO↗

arXiv2024

Galaxy clustering in modified gravity from full-physics simulations. I: two-point correlation functions

We present an in-depth investigation of galaxy clustering based on a new suite of realistic large-box galaxy-formation simulations in $f(R)$ gravity, with a subgrid physics model that has been recalibrated to reproduce various observed stellar and gas properties. We focus on the two-point correlation functions of the luminous red galaxies (LRGs) and emission line galaxies (ELGs), which are primary targets of ongoing and future galaxy surveys such as DESI. One surprising result is that, due to several nontrivial effects of modified gravity on matter clustering and the galaxy-halo connection, the clustering signal does not depend monotonically on the fifth-force strength. For LRGs this complicated behaviour poses a challenge to meaningfully constraining this model. For ELGs, in contrast, this can be straightforwardly explained by the time evolution of the fifth force, which means that weaker $f(R)$ models can display nearly the same -- up to $25\%$ -- deviations from $Λ$CDM as the strongest ones, albeit at lower redshifts. This implies that even very weak $f(R)$ models can be strongly constrained, unlike with most other observations. Our results show that galaxy formation acquires a significant environment dependence in $f(R)$ gravity which, if not properly accounted for, may lead to biased constraints on the model. This highlights the essential role of hydrodynamical simulations in future tests of gravity exploring precision galaxy-clustering data from the likes of DESI and Euclid.

astro-ph.CO↗