Constrained cosmological simulations of the Local Group using Bayesian hierarchical field-level inference

We present a novel approach based on Bayesian field-level inference capable of resolving individual galaxies within the Local Group (LG), enabling detailed studies of its structure and formation via posterior simulations. We extend the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm with a multi-resolution approach, allowing us to reach smaller mass scales and apply observational constraints based on LG galaxies. Our updated data model simultaneously accounts for observations of mass tracers within the dark haloes of the Milky Way (MW) and M31, their observed separation and relative velocity, and the quiet surrounding Hubble flow represented through the positions and velocities of galaxies at distances from one to four Mpc. Our approach delivers representative posterior samples of ΛCDM realisations that are statistically and simultaneously consistent with all these observations, leading to significantly tighter mass constraints than found if the individual datasets are considered separately. In particular, we estimate the virial masses of the MW and M31 to be log_10(M_200c/M_⊙) = 12.07±0.08 and 12.33±0.10, respectively, their sum to be log_10(Σ M_200c/M_⊙)= 12.52±0.07, and the enclosed mass within spheres of radius R to be log_10(M(R)/M_⊙)= 12.71±0.06 and 12.96±0.08 for R=1 Mpc and 3 Mpc, respectively. The M31-MW orbit is nearly radial for most of our ΛCDM LG's, and most lie in a dark matter sheet that aligns approximately with the Supergalactic Plane, even though the surrounding density field was not used explicitly as a constraint. The approximate simulations employed in our inference are accurately reproduced by high-fidelity structure formation simulations, demonstrating the potential for future high-resolution, full-physics ΛCDM posterior simulations of LG look-alikes.