arXiv subjects

Guilhem Lavaux

Publications and source records attributed to Guilhem Lavaux.

At least 19 recordsLinked to original sources

arXiv2026

The Manticore Project II: Bayesian digital twins of cosmic structure across the SDSS and BOSS volumes

We present Manticore-Deep, a high-resolution Bayesian field-level reconstruction of cosmic large-scale structure over a comoving volume of $(4~h^{-1}\mathrm{Gpc})^{3}$ to $z\approx0.7$ at ${\sim}4$~Mpc/h resolution. Extending the companion Manticore-Local analysis (Paper~I), Manticore-Deep jointly constrains five galaxy redshift surveys 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 LCDM, 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 \textit{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 \textit{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 ${\sim}3σ$ overdensity consistent with LCDM 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.

astro-ph.CO↗

arXiv2026

Alignment of the Milky Way and M31 with their cosmic environment. New insights from constrained Local Group simulations

The large-scale environment is thought to play an important role in setting galaxy properties. The Milky Way (MW) and Andromeda (M31) reside in the Local Group, embedded in the Local Sheet (LS). To study the sheet's influence on the dark matter (DM) halo shapes, spins, and disks orientations of MW and M31 analogues, we use a new suite of constrained Local Group simulations that reproduce the observed configuration of the two main halos and the LS. We determine their shapes and alignments relative to the LS analogues, and the effect of infall and coalescence of massive mergers. We find that the DM halo shapes of our MW and M31 analogues are on average slightly rounder than literature reports for similar-mass galaxies in random environments. We find preferential alignment between the sheet normal and the halos' minor axes, but not with the halos' spins. The present-day disk angular momenta ($L_{\rm disk}$) closely align with the halos' minor axes (median $15^{+15}_{-8}$ degrees at $R_{\rm vir}$) and with the halos' spins. The direction of $L_{\rm disk}$ is often set by one of the two highest mass ratio mergers during the last 8-10 Gyr. While recent ($\leq 2$ Gyr) massive mergers can reorient the outer halo's minor axis leading to twisted shapes, $L_{\rm disk}$ retains the imprint of the earlier accretion event. These results can explain the peculiar alignment of the MW's disk and DM halo shape and their orientation relative to the LS. The prolate-like morphology and orientation of the MW's outer halo can be explained by the Magellanic Clouds (and perhaps Sagittarius) accreting from within the LS. As their orbital planes are nearly perpendicular to the Galactic disk, the disk orientation must be set earlier, possibly by the GES merger. This merger's estimated infall direction, highly inclined relative to the present-day LS, is broadly consistent with the LS's direction of maximum collapse.

astro-ph.GA↗

arXiv2026

Forward-modelling Milky Way Cepheids: selection effects and physical priors in the Gaia-HST calibration

The advent of high-precision Gaia parallaxes for Milky Way Cepheids enables per cent-level calibration of the local distance ladder and the Hubble constant $H_0$. We revisit the Milky Way Cepheid calibration from Gaia EDR3 parallaxes using a fully forward-modelled Bayesian framework that simultaneously infers the period--luminosity relation, the Gaia parallax zero-point offset, and individual stellar distances while explicitly incorporating the disc geometry of the Galaxy through the distance prior and the selection functions specified in two HST SH0ES campaigns. We derive an analytic treatment of the detection probability that accounts for magnitude, parallax, period, and extinction cuts and reduces it to a tractable integral over distance and sky position. Posterior predictive checks show that this generative model matches the observed distributions of parallaxes, magnitudes, and periods. Modelling Galactic structure and survey truncation self-consistently in a Bayesian framework yields period--luminosity parameters that agree with the SH0ES maximum-likelihood values at the ${<}0.5\,σ$ level, a consequence of the small intrinsic scatter of the Cepheid period--luminosity relation. Adopting the uniform-in-volume prior recently advocated by Högås & Mörtsell (2026), without simultaneously accounting for selection, leads to a ${\sim}\,0.05~\mathrm{mag}$ bias in the period--luminosity zero-point and posterior predictive distributions incompatible with the observed data; this shift is mostly driven by the omission of the selection model, and produces an apparent and unjustified shift in $H_0$ that reflects this mismodelling. A consistent Bayesian treatment of Galactic structure and selection effects reinforces the local distance-ladder determination of $H_0$, and hence the Hubble tension with early-Universe inferences.

astro-ph.GA↗

arXiv2026

Two per cent measurement of $H_0$ from Cepheids alone

One of the most pressing problems in current cosmology is the cause of the Hubble tension. We revisit a two-rung distance ladder, composed only of Cepheid periods and magnitudes, anchor distances in the Milky Way, Large Magellanic Cloud, NGC 4258, and host galaxy redshifts. We adopt the SH0ES data for the most up-to-date and carefully vetted measurements, where the Cepheid hosts were selected to harbour also Type Ia supernovae. We introduce two important improvements: a rigorous selection modelling and a state-of-the-art density and peculiar velocity model using Manticore-Local, based on the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm. We infer $H_0 = 71.1 \pm 1.4~\mathrm{km}\,\mathrm{s}^{-1}\,\mathrm{Mpc}^{-1}$, assuming the Cepheid host sample was selected by supernova magnitudes. However, the actual selection criteria are not clear, and other assumptions can increase $H_0$ by up to one statistical standard deviation. The posterior has a lower central value and a 41 per cent smaller uncertainty than a previous study using the same distance-ladder data. This result is lower than the supernova-based SH0ES inferred value of $H_0 = 73.2 \pm 0.9~\mathrm{km}\,\mathrm{s}^{-1}\,\mathrm{Mpc}^{-1}$ at about $1.3σ$, and is in $2.8σ$ tension with the latest cosmic microwave background results in the standard cosmological model. These results demonstrate that a measurement of $H_0$ of sufficient precision to weigh in on the Hubble tension is achievable using second-rung data alone, underscoring the importance of robust and accurate statistical and velocity-field modelling.

astro-ph.CO↗

arXiv2026

Learning the Universe: Constrained simulations of the Coma galaxy cluster -- I. Radial X-ray and Compton-y signatures

We present a suite of 50 high-fidelity simulations of Coma cluster analogues constructed from BORG/MANTICORE constrained initial conditions and evolved with the IllustrisTNG galaxy formation model. Regions predicted to form massive clusters comparable to Coma in mass and environment are selected and followed through cosmic time, producing realistic galaxy populations and intracluster medium properties. The ensemble captures both cosmic variance and uncertainties in the local initial conditions, providing a statistically robust framework for interpreting Coma in a cosmological context. We focus on direct comparisons with observed thermodynamical profiles of the intracluster medium. Specifically, we extract X-ray surface brightness profiles from the simulated clusters and confront them with measurements from eROSITA, as well as compute the thermal Sunyaev--Zel'dovich effect via integrated Compton-$y$ profiles for comparison with Planck satellite data. The simulations reproduce the broad shape and normalisation of both observables, while also highlighting the range of scatter expected from environmental and assembly history differences. This enables us to assess how feedback processes, merger activity, and large-scale environment shape observable cluster properties. Our results demonstrate that combining constrained cosmological initial conditions with state-of-the-art galaxy formation physics provides an effective strategy for generating targeted, observation-driven analogues of specific clusters. The resulting dataset offers a valuable resource for testing models of intracluster medium physics, calibrating scaling relations, and interpreting upcoming joint X-ray and Sunyaev--Zel'dovich observations of nearby massive clusters.

astro-ph.CO↗

arXiv2026

PySCo-EFT and ECOSMOG-EFT: a tandem of N-body simulation codes for the Effective Field Theory of Dark Energy

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 them by comparison with clustering and weak lensing data from upcoming large-scale structure surveys, high-resolution cosmological N-body simulations are required to obtain accurate predictions for the matter distribution on non-linear scales. We introduce two new N-body simulation codes for EFTofDE cosmologies: PySCo-EFT, a Python-based particle mesh code, and ECOSMOG-EFT, a RAMSES-based code with adaptive mesh refinement. We consider Horndeski models with a luminal gravitational wave speed. We use iterative solvers and multigrid schemes to solve for the additional scalar field equation in both codes, incorporating the non-linear Vainshtein screening mechanism. We present validation and convergence tests of the codes. We obtain a sub-0.5 percent agreement with linear theory on large scales and a similar agreement between the two codes on non-linear scales. The dominant numerical effects on the matter-power-spectrum boost are 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) for the range of tested values. We investigate the impact of the EFTofDE parameters on the matter-power-spectrum ratios between EFTofDE and $Λ$CDM cases. Depending on the EFTofDE parameters, the screening plays a negligible or dominant role compared to the 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 non-linear screening.

astro-ph.CO↗

arXiv2026

Field-Level Inference of Primordial Non-Gaussianity with the Quijote Simulation Suite

Local primordial non-Gaussianity, parameterised as $f_{\rm NL}^{\rm local}$, will be stringently constrained using state-of-the-art methods applied to next-generation galaxy redshift survey data. In this paper, in preparation for the upcoming data sets, we demonstrate for the first time the joint field-level inference of $f_{\rm NL}^{\rm local}$, nuisance parameters, and the initial conditions in realistic halo catalogues, ones which are generated through full dark-matter-only $N$-body simulations. The field-level inference algorithm optimally constrains $f_{\rm NL}^{\rm local}$ through a Bayesian forward-modelling approach at the field level, which outperforms traditional methods by leveraging the full statistical power of the data at the scales considered. In addition, we assess its performance under various design choices in the forward model, including tests of the structure formation model and resolution. We demonstrate the robustness of our approach by applying it to a subset of the \textit{Quijote} simulation suite, performing the inference at scales down to $k_{\rm max} \approx 0.1 h \rm{Mpc}^{-1}$. Compared with a power spectrum and bispectrum estimator, we find a $\sim1.3$ improvement in $σ(f_{\rm NL}^{\rm local})$ when applying \borg{}, while marginalising over the initial conditions and bias parameters. From the small-scale information sensitivity tests, we show that the constraints on $f_{\rm NL}^{\rm local}$ improve as we increase the resolution of the inference. These findings underscore the transformative potential of field-level inference to leverage the information available in ongoing surveys such as \textit{Euclid}, providing accurate insights into the physics of cosmic inflation and the number of fields driving it.

astro-ph.CO↗

arXiv2026

Revisiting the Great Attractor: The Local Group's streamline trajectory, cosmic velocity and dynamical fate

We revisit the Great Attractor using the Manticore-Local suite of digital twins of the nearby Universe. The Great Attractor concept has been proposed as an answer to three distinct questions: what sources the Local Group velocity in the cosmic microwave background frame, where present-day velocity streamlines converge, and where the Local Group is moving to. Addressing the original motivation of the Great Attractor -- explaining the Local Group cosmic velocity -- we find that mass within $155~h^{-1}\mathrm{Mpc}$ accounts for only ${\sim}72\%$ of that velocity magnitude with ${\sim}38\,°$ directional offset. We show that even in the purely linear regime convergence within this volume is not guaranteed, particularly when also accounting for small-scale contributions to the observer velocity; no single structure, including the proposed Great Attractor, would be expected to dominate the velocity budget. Streamline convergence is smoothing-scale-dependent, transitioning from Virgo at small scales through the Hydra--Centaurus region at intermediate scales to Shapley at large scales; at intermediate smoothing the convergence point lies near Abell 3565 with an asymmetric basin of mass $\log( M / (h^{-1} \mathrm{M}_\odot)) = 16.4 \pm 0.1$ that excludes Norma. To address the third question, we evolve the Manticore-Local realisations to scale factor $a = 10$ in a new Beyond-Present-Time simulation suite and identify the asymptotic future location of the Local Group. We find that the dominant motion is towards Virgo, but even it contributes at most one third of the Local Group velocity. Our results demonstrate that the classical Great Attractor is not a dynamically dominant structure but an artefact of the instantaneous velocity field, and that no single attractor is likely to account for the Local Group motion in the cosmic rest frame.

astro-ph.CO↗

arXiv2026

Reconstructing the largest scales of the Universe with field-level inference applied to the Quaia Quasar Catalogue

The recently released Quaia quasar catalogue, with its broad redshift range and all-sky coverage, enables unprecedented three-dimensional reconstructions of matter across cosmic time. In this work, we apply the field-level inference algorithm BORG to the Quaia catalogues to reconstruct the initial conditions and present-day matter distribution of the Universe. We employ a physics-based forward model of large-scale structure using Lagrangian perturbation theory, incorporating light-cone effects, redshift-space distortions, quasar bias, and survey selection effects. This approach enables a detailed and physically motivated inference of the three-dimensional density field and initial conditions over the entire cosmic volume considered. We analyse both the G < 20.0 (Quaia Clean) and G < 20.5 (Quaia Deep) samples, where G denotes the Gaia broad optical-band magnitude, imposing conservative sky cuts to ensure robustness against foreground contamination. The resulting reconstructions span a comoving volume of (10h^{-1} Gpc)^3 with a maximum spatial resolution of 39.1 h^{-1}Mpc, making this the largest field-level reconstruction of the observable Universe in terms of comoving volume to date. We validate our reconstructions through a range of internal and external consistency checks, including the cross-correlation of the inferred density fields with Planck CMB lensing, where we detect a signal at ~4σsignificance. Beyond delivering high-fidelity data products, including posterior maps of initial conditions, present-day dark matter, and velocity fields, this work establishes a framework for exploiting quasar surveys in field-level cosmology.

astro-ph.CO↗

arXiv2026

The mass distribution in and around the Local Group

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.

astro-ph.GA↗

arXiv2025

The Velocity Field Olympics: Assessing velocity field reconstructions with direct distance tracers

The peculiar velocity field of the local Universe provides direct insights into its matter distribution and the underlying theory of gravity, and is essential in cosmological analyses for modelling deviations from the Hubble flow. Numerous methods have been developed to reconstruct the density and velocity fields at $z \lesssim 0.05$, typically constrained by redshift-space galaxy positions or by direct distance tracers such as the Tully-Fisher relation, the fundamental plane, or Type Ia supernovae. We introduce a validation framework to evaluate the accuracy of these reconstructions against catalogues of direct distance tracers. Our framework assesses the goodness-of-fit of each reconstruction using Bayesian evidence, residual redshift discrepancies, velocity scaling, and the need for external bulk flows. Applying this framework to a suite of reconstructions -- including those derived from the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm and from linear theory -- we find that the non-linear BORG reconstruction consistently outperforms others. We highlight the utility of such a comparative approach for supernova or gravitational wave cosmological studies, where selecting an optimal peculiar velocity model is essential. Additionally, we present calibrated bulk flow curves predicted by the reconstructions and perform a density--velocity cross-correlation using a linear theory reconstruction to constrain the growth factor, yielding $S_8 = 0.793 \pm 0.035$. The result is in good agreement with both weak lensing and Planck, but is in strong disagreement with some peculiar velocity studies.

astro-ph.CO↗

arXiv2025

No evidence for local $H_0$ anisotropy from Tully--Fisher or supernova distances

Claims of local ($z \lesssim 0.05$) anisotropy in the Hubble constant have been made based on direct distance tracers such as Tully-Fisher galaxies and Type Ia supernovae. We revisit these using the CosmicFlows-4 Tully-Fisher W1 subsample, 2MTF and SFI++ Tully-Fisher catalogues, and the Pantheon+ supernova compilation (all restricted to $z < 0.05$), including a dipole in either the Tully-Fisher zero-point or the standardised supernova absolute magnitude. Our forward-modelling framework jointly calibrates the distance relation, marginalises over distances, and accounts for peculiar velocities using a linear-theory reconstruction. We compare the anisotropic and isotropic model using the Bayesian evidence. In the CosmicFlows-4 sample, we infer a zero-point dipole of amplitude $0.087 \pm 0.019$ mag, or $4.1\pm0.9$ per cent when expressed as a dipole in the Hubble parameter. This is consistent with previous estimates but at higher significance: model comparison yields odds of $877:1$ in favour of including the zero-point dipole. In Pantheon+ we infer zero-point dipole amplitude of $0.049 \pm 0.013$ mag, or $2.3\pm 0.6$ per cent when expressed as a dipole in the Hubble parameter. However, by allowing for a radially varying velocity dipole, we show that the anisotropic zero-point model captures local flow features (or possibly systematics) in the data rather than an actual linearly growing effective bulk flow caused by anisotropy in the zero-point or expansion rate. Crucially, inferring a more general bulk flow curve we find results fully consistent with expectations from the standard cosmological model.

astro-ph.CO↗

arXiv2025

Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity

Normalizing Flows (NF) are Generative models which transform a simple prior distribution into the desired target. They however require the design of an invertible mapping whose Jacobian determinant has to be computable. Recently introduced, Neural Hamiltonian Flows (NHF) are Hamiltonian dynamics-based flows, which are continuous, volume-preserving and invertible and thus make for natural candidates for robust NF architectures. In particular, their similarity to classical Mechanics could lead to easier interpretability of the learned mapping. In this paper, we show that the current NHF architecture may still pose a challenge to interpretability. Inspired by Physics, we introduce a fixed-kinetic energy version of the model. This approach improves interpretability and robustness while requiring fewer parameters than the original model. We illustrate that on a 2D Gaussian mixture and on the MNIST and Fashion-MNIST datasets. Finally, we show how to adapt NHF to the context of Bayesian inference and illustrate the method on an example from cosmology.

cs.LG↗

arXiv2025

A Bayesian catalog of 100 high-significance voids in the Local Universe

While cosmic voids are now recognized as a valuable cosmological probe, identifying them in a galaxy catalog is challenging 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 non-trivial to estimate the detection significance and parameter uncertainties for individual voids. 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, effectively representing 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. We use 50 posterior realizations of the large-scale structure in the Manticore-Local suite, obtained from the 2M++ galaxies. Running the VIDE void finder on each realization, we extract 50 independent void catalogs. We perform a posterior clustering analysis to identify high-significance voids at the 5$σ$ level, and we assess the probability distribution of their properties. We produce a catalog of 100 voids with high statistical significance, available at https://voids.cosmictwin.org/, including the probability distributions of the centers and radii of the voids. We characterize the morphology of these regions, effectively producing a template for density environments that can be used in astrophysical applications such as galaxy evolution studies. 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 account rigorously for the observational systematics intrinsic to direct detection, and provide a Bayesian characterization of their properties.

astro-ph.CO↗

arXiv2025

The Manticore Project I: a digital twin of our cosmic neighbourhood from Bayesian field-level analysis

We present the first results from the Manticore project, dubbed Manticore-Local, a suite of Bayesian constrained simulations of the nearby Universe, generated by fitting a physical structure formation model to the 2M++ galaxy catalogue using the BORG algorithm. This field-level inference yields physically consistent realizations of cosmic structure, leveraging a nonlinear gravitational solver, a refined galaxy bias model, and physics-informed priors. The Manticore-Local posterior realizations evolve within a parent cosmological volume statistically consistent with LCDM, demonstrated through extensive posterior predictive tests of power spectra, bispectra, initial condition Gaussianity, and the halo mass function. The inferred local supervolume shows no significant deviation from cosmological expectations; notably, we find no evidence for a large local underdensity. Our model identifies high-significance counterparts for fourteen prominent galaxy clusters each within one degree of its observed sky position. Across the posterior ensemble, these counterparts are consistently detected with 2-4 sigma significance, and their reconstructed masses and redshifts agree closely with observational estimates, confirming the inference's spatial and dynamical fidelity. The peculiar velocity field recovered by Manticore-Local achieves the highest Bayesian evidence across five datasets, surpassing state-of-the-art models. Unlike methods yielding only point estimates or using simplified dynamics, Manticore-Local provides a full Bayesian posterior over cosmic structure and evolution, enabling rigorous uncertainty quantification. These results establish Manticore-Local as the most advanced constrained realization suite of the Local Universe to date, offering a robust statistical foundation for future studies of galaxy formation, velocity flows, and environmental dependencies in our cosmic neighbourhood.

astro-ph.CO↗

arXiv2025

Inference of Hubble constant using standard sirens and reconstructed matter density field

We summarise a new approach for measuring the Hubble constant using standard sirens and the reconstructed matter density field obtained from observed galaxy surveys. Specifically, we describe and test this method using the Bayesian forward-modelled software BORG. This software evolves the initial density field to the present, sampling plausible density fields from the posterior, accounting for peculiar velocities, and automatically incorporating higher-order correlation functions. The advantage of adding additional information from correlations is expected to make this method more effective in low-signal-to-noise regimes, such as those with modest galaxy number density or incomplete surveys. Our results show that developing a cross-correlation framework between gravitational waves and galaxy surveys, based on the forward-modelled reconstructed density field, to measure H0 is promising. This review is based on the research conducted as part of Boruah's Ph.D. thesis.

astro-ph.CO↗

arXiv2025

The effect of environment on the mass assembly history of the Milky Way and M31

We study the mass growth histories of the halos of Milky Way and M31 analogues formed in constrained cosmological simulations of the Local Group. These simulations constitute a fair and representative set of $Λ$CDM realisations conditioned on properties of the main Local Group galaxies, such as their masses, relative separation, dynamics and environment. Comparing with isolated analogues extracted from the TNG dark-matter-only simulations, we find that while our M31 halos have a comparable mass growth history to their isolated counterparts, our Milky Ways typically form earlier and their growth is suppressed at late times. Mass growth associated to major and minor mergers is also biased early for the Milky Way in comparison to M31, with most accretion occurring 1 - 4 Gyr after the Big Bang, and a relatively quiescent history at later times. 32% of our Milky Ways experienced a Gaia-Enceladus/Sausage (GES)-like merger, while 13% host an LMC-like object at the present day, with 5% having both. In one case, an SMC- and a Sagittarius-analogue are also present, showing that the most important mergers of the Milky Way in its Local Group environment can be reproduced in $Λ$CDM. We find that the material that makes up the Milky Way and M31 halos at the present day first collapsed onto a plane roughly aligned with the Local Sheet and Supergalactic plane; after $z \sim 2$, accretion occurred mostly within this plane, with the tidal effects of the heavier companion, M31, significantly impacting the late growth history of the Milky Way.

astro-ph.GA↗

arXiv2024

Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators

Analysing next-generation cosmological data requires balancing accurate modeling of non-linear gravitational structure formation and computational demands. We propose a solution by introducing a machine learning-based field-level emulator, within the Hamiltonian Monte Carlo-based Bayesian Origin Reconstruction from Galaxies (BORG) inference algorithm. Built on a V-net neural network architecture, the emulator enhances the predictions by first-order Lagrangian perturbation theory to be accurately aligned with full $N$-body simulations while significantly reducing evaluation time. We test its incorporation in BORG for sampling cosmic initial conditions using mock data based on non-linear large-scale structures from $N$-body simulations and Gaussian noise. The method efficiently and accurately explores the high-dimensional parameter space of initial conditions, fully extracting the cross-correlation information of the data field binned at a resolution of $1.95h^{-1}$ Mpc. Percent-level agreement with the ground truth in the power spectrum and bispectrum is achieved up to the Nyquist frequency $k_\mathrm{N} \approx 2.79h \; \mathrm{Mpc}^{-1}$. Posterior resimulations - using the inferred initial conditions for $N$-body simulations - show that the recovery of information in the initial conditions is sufficient to accurately reproduce halo properties. In particular, we show highly accurate $M_{200\mathrm{c}}$ halo mass function and stacked density profiles of haloes in different mass bins $[0.853,16]\times 10^{14}M_{\odot}h^{-1}$. As all available cross-correlation information is extracted, we acknowledge that limitations in recovering the initial conditions stem from the noise level and data grid resolution. This is promising as it underscores the significance of accurate non-linear modeling, indicating the potential for extracting additional information at smaller scales.

astro-ph.CO↗