A simulation-based inference of the Milky Way merger history
Andrea Sante, Andreea S. Font, Daisuke Kawata, T. Lucas Makinen, Robert J. J. Grand

TL;DR
This paper uses a simulation-based inference framework with chemo-dynamical signatures to estimate the properties and merger history of the Milky Way's accreted satellite galaxies, aligning well with previous estimates and providing new insights.
Contribution
It introduces a novel application of normalizing flows to infer the properties of disrupted satellites from chemo-dynamical data in the Milky Way.
Findings
Predicted total stellar mass accreted from merger events: 2.2^{+1.1}_{-0.6}×10^9 M_sun.
Estimated stellar mass from fully disrupted progenitors: 1.3^{+1.0}_{-0.5}×10^9 M_sun.
Predicted MW halo mass after Sgr merger: 5.9^{+1.4}_{-1.1}×10^{11} M_sun.
Abstract
Accreted stars in the Milky Way (MW) preserve information about the progenitor galaxies where they formed in their chemical and kinematic properties. In this study, we use the chemo-dynamical signatures in the merger debris to approximate the posterior distribution of disrupted satellite properties at the time of infall. Adopting a simulation-based inference framework, we train an ensemble of normalizing flows using samples of merger debris from the Auriga suite of simulations of MW-like galaxies. Applying this methodology to a local sample of accreted stars in the MW, we infer the lookback times, stellar and halo masses, and halo mass merger ratios of several known accretion events in the Galaxy: Gaia Enceladus-Sausage (GES), Helmi streams, Heracles, I'itoi, LMS-1/Wukong, Sagittarius (Sgr), Sequoia and Thamnos. Our predictions align with the accretion time and mass estimates from the…
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Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Gamma-ray bursts and supernovae · Astronomy and Astrophysical Research
