Constrained cosmological simulations of the Local Group using Bayesian hierarchical field-level inference
arxiv(2024)
摘要
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.
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