CASBI – Chemical Abundance Simulation-Based Inference for Galactic Archeology

Giuseppe Viterbo, Tobias Buck

Abstract:

Galaxies evolve hierarchically through merging with lower-mass systems and the
remnants of destroyed galaxies are a key indicator of the past assembly history
of our Galaxy. However, accurately measuring the properties of the accreted
galaxies and hence unraveling the Milky Way’s (MW) formation history is a
challenging task. Here we introduce CASBI (Chemical Abundance Simulation
Based Inference), a novel inference pipeline for Galactic Archeology based on
Simulation-based Inference methods. CASBI leverages on the fact that there is a
well defined mass-metallicity relation for galaxies and performs inference of key
galaxy properties based on multi-dimensional chemical abundances of stars in the
stellar halo. Hence, we recast the problem of unraveling the merger history of the
MW into a SBI problem to recover the properties of the building blocks (e.g. total
stellar mass and infall time) using the multi-dimensional chemical abundances of
stars in the stellar halo as observable. With CASBI we are able to recover the full
posterior probability of properties of building blocks of Milky Way like galaxies.
We highlight CASBI’s potential by inferring posteriors for the stellar masses of
completely phase mixed dwarf galaxies solely from the 2d-distributions of stellar
abundance in the iron vs. oxygen plane and find accurate and precise inference results.