407 citations · 4.5k across the 60 of their papers we have counts for
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Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?
Andrea Sante, Andreea S. Font, Sandra Ortega-Martorell +2
We present several machine learning (ML) models developed to efficiently separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later a…
ARTEMIS emulator: exploring the effect of cosmology and galaxy formation physics on Milky Way-mass haloes and their satellites
Shaun T. Brown, Azadeh Fattahi, Ian G. McCarthy +3
We present the new ARTEMIS Emulator suite of high resolution (baryon mass of M) zoom-in simulations of Milky Way mass systems. Here, three ha…
Differences in the properties of disrupted and surviving satellites of Milky-Way-mass galaxies in relation to their host accretion histories
Salvador E. Grimozzi, Andreea S. Font, María Emilia De Rossi
From the chemo-dynamical properties of tidal debris in the Milky Way, it has been inferred that the dwarf satellites that have been disrupted had different chemical abundances from…