Guilhem Lavaux

Modified gravity theories constitute viable alternatives to the standard cosmological model for explaining the observed late-time accelerated expansion of the Universe. The effective field theory of dark energy (EFTofDE) is an efficient framework to describe a wide range of such theories with a limited number of parameters. To robustly constrain these theories, high-resolution cosmological N -body simulations are required to obtain accurate predictions for the matter distribution on non-linear scales, which can then be quantitatively compared with clustering and weak gravitational lensing measurements from forthcoming galaxy surveys. We introduce two new N -body simulation codes for cosmologies governed by cubic luminal Horndeski gravity models of the EFTofDE under quasi-static approximation: PySCo-EFT , a fast Python-based particle-mesh code, and ECOSMOG-EFT , an accurate RAMSES -based code with adaptive mesh refinement. We used iterative solvers and multigrid schemes to solve for the additional scalar field equation in both codes, including the non-linear Vainshtein screening mechanism. The standard gravitational force was augmented by a fifth force from the scalar field. We present several validation and convergence tests of the codes. We obtained a sub 0.5% agreement with linear theory on large scales and a similar agreement between the two codes in particle-mesh mode for the power spectrum boost, although they implement different solvers. The dominant numerical effects on the matter power spectrum boost are finite mass resolution, finite-volume effects, refinement threshold, and starting redshift, but they are limited to below 2% at the largest wavenumbers, k = 10 h Mpc ⁻¹ , for the range of tested values. Finally, we investigated the impact of the EFTofDE parameters on the matter power spectrum ratios between EFTofDE and Lambda cold dark matter scenarios. Depending on the values of the EFTofDE parameters, the screening can play a negligible or dominant role compared to the often-used linearised field equations. Our codes provide tools for generating fast and accurate predictions of the impact of the EFTofDE on the clustering of matter, incorporating the non-linear Vainshtein screening mechanism.

We present Manticore-Deep, a high-resolution Bayesian field-level reconstruction of cosmic large-scale structure over a comoving volume of (4 h−1Gpc)3 to z ≈ 0.7 at ~4 h−1 Mpc resolution. Extending the companion Manticore-Local analysis (Paper I), Manticore-Deep jointly constrains five galaxy redshift surveys—2M++, 6dFGS, 2dFGRS, SDSS, and BOSS—within a single hierarchical Bayesian framework using the BORG algorithm. The inference reconstructs primordial initial conditions evolved under gravity, yielding a posterior ensemble of three-dimensional density and velocity fields that causally reproduce the observed large-scale structure. A novel tiled inference strategy extends the reconstructed volume by more than an order of magnitude beyond Paper I. Posterior realisations are consistent with ΛCDM, reproducing Gaussian isotropic initial conditions and the expected z = 0 matter power spectrum, bispectrum, and halo mass function over the resolved scales. We validate the reconstruction using two independent template-free posterior-predictive tests against observations excluded from the inference. Cross-correlation with the Planck PR3 CMB lensing map yields a cumulative detection significance of 7.4 σ, while velocity-weighted stacking of 64, 750 galaxy clusters on the Planck 217 GHz map detects the kinetic Sunyaev–Zel’dovich effect at 3.5σ, with a model-independent approach–recession split confirming the inferred velocities. Together, these tests validate both the projected-density and three-dimensional velocity fields recovered by Manticore-Deep. The BOSS Great Wall is recovered as a ~3σ overdensity consistent with ΛCDM across the posterior ensemble. Manticore-Deep establishes a benchmark for survey-depth constrained cosmological digital twins and reproducible field-level validation of large-scale structure reconstructions.

A primary target of the Euclid space mission is to constrain early-universe physics by searching for deviations from a primordial Gaussian random field. A significant detection of primordial non-Gaussianity would rule out the simplest models of cosmic inflation and transform our understanding of the origin of the Universe. This paper forecasts how well field-level inference of galaxy redshift surveys can constrain the amplitude of local primordial non-Gaussianity, f _NL ^local , within a Bayesian hierarchical framework, in the upcoming Euclid data. We designed and simulated mock datasets and performed Markov chain Monte Carlo analyses using a full-field forward modelling approach. By including the formation history of the cosmic matter field in the analysis, the method takes into account all available probes of primordial non-Gaussianity, and goes beyond statistical summary estimators of f _NL ^local . Probes include, for example, two-point and higher-order statistics, peculiar velocity fields, and scale-dependent galaxy biases. Furthermore, the method simultaneously handles systematic survey effects, such as selection effects, survey geometries, and galaxy biases. The forecast shows that, using simulated Euclid data, the method can achieve a precision of σ ( f _NL ^local ) = 2.6 (68.3% confidence level), assuming a grid resolution of Δ L = 31.25 h ⁻¹ Mpc and a cut-off scale of k _NF = 0.1 h Mpc ⁻¹ . We also provide data products, including realistic simulations with non-zero values of f _NL ^local and maps of adiabatic curvature fluctuations. The results underscore the feasibility and advantages of field-level inference to constrain f _NL ^local in galaxy redshift surveys. Our approach consistently captures all the information available in the large-scale structure to constrain f _NL ^local , and resolves the degeneracy between early-universe physics and late-time gravitational effects, while mitigating the impact of systematic and observational effects.

The Euclid mission of the European Space Agency will deliver galaxy and cosmic shear surveys, which will be used to constrain initial conditions and statistics of primordial fluctuations. We present highlights for the Euclid scientific capability to test initial conditions beyond Λ cold dark matter with the three-dimensional galaxy clustering from the spectroscopic survey, the tomographic approach to 3 results can be enhanced when combined with current and future measurements of the cosmic microwave background (CMB) anisotropies. statistics (information) from photometric galaxy survey, and their combination. We then present how these Euclid We provide Fisher forecasts from the combination of Euclid spectroscopic and photometric surveys for spatial curvature, running of the spectral index of the power spectrum of curvature perturbations, isocurvature perturbations, and primordial features. For the parameters of these models, we also provide the combination of Euclid forecasts (pessimistic and optimistic) with three different CMB specifications, i.e. Planck , the Simons Observatory (SO), and CMB-S4. We provide Fisher forecasts for how the power spectrum and bispectrum from the Euclid spectroscopic survey will constrain the local, equilateral, and orthogonal shapes of primordial non-Gaussianity. We also review how Bayesian field-level inference of primordial non-Gaussianity can constrain local primordial non-Gaussianity. We find that the combination of the Euclid main probes will provide an uncertainty of σ(Ω_K) = 0.0044 (0.003) at a 68% confidence level (CL) in pessimistic (optimistic) settings, assuming flat spatial sections as fiducial cosmology. We also find that the combination of the Euclid main probes can detect the running of the scalar spectral index for the fiducial value α_s = - 0.01 with approximately 2σ (4σ) uncertainty and provide the uncertainty of σ(α_s) = 0.004 (0.0015) for the fiducial value α_s = - 0.001 at a 68% CL, always with pessimistic (optimistic) settings. We show how Euclid will have the capability to provide constraints on isocurvature perturbations with a blue spectral index that are one order of magnitude tighter than current bounds. For primordial non-Gaussianity, the combined power spectrum and bispectrum Fisher forecast for the Euclid spectroscopic survey leads to σ (f_ ̊m NL ^ ̊m local ) = 2.2, σ (f_ ̊m NL ^ ̊m equil ) = 108, and σ ( ) = 33 by assuming k_ ̊m ortho ̊m max ̊m Mpc ^ -1 and universality for the halo mass function. We show how Bayesian field-level inference can reach the combined power spectrum and bispectrum Fisher forecast uncertainty on f_ ̊m NL ^ ̊m local at these large scales, although it is more conservative as it is based on more realistic three-dimensional mock data and masks. For the Euclid main probes, we find relative errors on the amplitude of primordial oscillations (with a fiducial value of 0.01), of 21% (18%) for linear frequency and of 22% (18%) for logarithmic frequency at a 68% CL in the pessimistic (optimistic) case. These uncertainties can be further improved by adding the information from the bispectrum and the non-linear reconstruction. We show how Euclid , with its unique combination of three-dimensional galaxy clustering from the spectroscopic survey and 3 's expected uncertainties are complementary to those obtained by CMB primary anisotropy, returning the tightest combined constraints on the physics of the early Universe. statistics from the photometric survey, will provide the tightest constraints on low redshift to date. By targeting a markedly different range in redshift and scale, Euclid

We present the strategy used to identify and mitigate potential sources of angular systematics in the spectroscopic galaxy survey, and we quantify their impact on galaxy clustering measurements and cosmological parameter estimation. We first surveyed the processing pipeline to identify all evident, potential sources of systematics, and classified them into two broad classes: angular systematics, which modulate the galaxy number density across the sky, and catastrophic redshift errors, which lead to interlopers in the galaxy sample. We then used simulated spectroscopic surveys to test our ability to mitigate angular systematics by constructing a random catalogue that represents the `visibility mask' of the survey; this is a dense set of intrinsically unclustered objects, subject to the same selection effects as the data catalogue. The construction of this random catalogue relies on a detection model, which gives the probability of reliably measuring the galaxy redshift as a function of the signal-to-noise ratio (S/N) of its emission lines. We demonstrate that, in the ideal case of a perfect knowledge of the visibility mask, the galaxy power spectrum in the presence of systematics is recovered, to within sub-per cent accuracy, by convolving a theory power spectrum with a window function obtained from the random catalogue itself. In the case of only approximate knowledge of the visibility mask, we test the stability of power spectrum measurements and cosmological parameter posteriors by using perturbed versions of the random catalogue. We find that significant effects are limited to very large scales, and parameter estimation remains robust; the most impacting effects are connected to the calibration of the detection model. Euclid Euclid

Context. The Euclid galaxy survey is designed to measure the spectroscopic redshift of emission-line galaxies (ELGs) by identifying the H α emission line in their slitless spectra. The efficacy of this approach crucially depends on the signal-to-noise ratio (S/N) of the line, as sometimes noise fluctuations in the spectrum continuum can be misidentified as H α . In addition, other genuine strong emission lines can be mistaken for H α , depending on the redshift of the source. Both effects lead to ambiguities in the redshift measurement that can result in catastrophic redshift errors and the inclusion of ‘interloper’ galaxies in the sample. Aims. This paper forecasts the impact on the galaxy clustering analysis of the expected redshift errors in the Euclid spectroscopic sample. Specifically, it investigates the effect of the redshift interloper contamination on the galaxy two-point correlation function (2PCF) and, in turn, on the inferred growth rate of structure fσ ₈ and Alcock–Paczynski (AP) parameters α _∥ and α _⊥ . Methods. This work is based on the analysis of 1000 synthetic spectroscopic catalogues, the EuclidLargeMocks, which mimic the area and selection function of the Euclid Data Release 1 (DR1) sample. We estimated the 2PCF of contaminated catalogues and separated the different contributions, particularly those coming from galaxies with correctly measured redshift and from contaminants. We explored different models of increasing complexity to describe the measured 2PCF at a fixed cosmology, with the aim of identifying the most efficient model to reproduce the data. Finally, we performed a cosmological inference and evaluated the systematic error on the inferred fσ ₈ , α _∥ , and α _⊥ values associated with different models. Results. Our results demonstrate that a minimal modelling approach, which only accounts for an attenuation of the clustering signal regardless of the type of contaminants, is sufficient to recover the correct values of fσ ₈ , α _∥ , and α _⊥ at DR1. The accuracy and precision of the estimated AP parameters are largely insensitive to the presence of interlopers. The adoption of a minimal modelling induces a 1%–3% systematic error on the growth rate of structure estimation, depending on the considered redshift. However, this error remains smaller than the statistical error expected for the Euclid DR1 analysis.

Our Galaxy, Andromeda and their companion dwarf galaxies form the Local Group. Most of the mass in and around it is believed to be dark matter rather than gas or stars, so its distribution must be inferred from the effect of gravity on the motion of visible objects. Modelling efforts have long struggled to reproduce the quiet Hubble flow around the Local Group, as they require unrealistically little mass beyond the haloes of the two main galaxies. Here we revisit this using Λ CDM simulations of Local Group analogues with initial conditions constrained to match the observed dynamics of the two main haloes and the surrounding flow. The observations are reconcilable within Λ CDM, but only if mass is strongly concentrated in a plane out to 10 Mpc, with the surface density rising away from the Local Group and with deep voids above and below. This configuration, dynamically inferred, mirrors known structures in the nearby galaxy distribution. The resulting Hubble flow is quiet yet strongly anisotropic, a fact obscured by the paucity of tracers at high supergalactic latitude. This flattened geometry reconciles the dynamical mass estimates of the Local Group with the surrounding velocity field, thus demonstrating full consistency within the standard cosmological model.

Context. While cosmic voids are now recognized as a valuable cosmological probe, it is challenging to identify them in a galaxy catalog for multiple reasons: Observational effects such as holes in the mask or magnitude selection hinder the detection process; galaxies are biased tracers of the underlying dark matter distribution; and it is nontrivial to estimate the detection significance and parameter uncertainties for individual voids. Aims. Our goal is to extract a catalog of voids from constrained simulations of the large-scale structure that are consistent with the observed galaxy positions and effectively represent statistically independent realizations of the probability distribution of the cosmic web. This allows us to carry out a full Bayesian analysis of the structures emerging in the Universe. Methods. We used 50 posterior realizations of the large-scale structure in the Manticore-Local suite, obtained from the 2M++ galaxies, with z ≲ 0.1 and a sky area between ∼23 000 − 36 000 deg ² . Running the VIDE void finder on each realization, we extracted 50 independent void catalogs. We performed a posterior clustering analysis to identify high-significance voids at the 5 σ level, and we assessed the probability distribution of their properties by combining the contributions of independent large-scale structure realizations. Results. We produced a publicly available catalog of 100 voids with a high statistical significance, including the probability distributions of the centers and the radii of the voids. We characterized the morphology of these regions and effectively produced a template for density environments that can be used in astrophysical applications such as galaxy evolution studies. Conclusions. While providing the community with a detailed catalog of voids in the nearby Universe, this work also constitutes an approach to identifying cosmic voids from galaxy surveys that allows us to rigorously account for the observational systematics intrinsic to direct detection, and to provide a Bayesian characterization of their properties.