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We use Density Estimation Likelihood-Free Inference, $Lambda$ Cold Dark Matter simulations of $sim 2M$ galaxy pairs, and data from Gaia and the Hubble Space Telescope to infer the sum of the masses of the Milky Way and Andromeda (M31) galaxies, the two main components of the Local Group. This method overcomes most of the approximations of the traditional timing argument, makes the writing of a theoretical likelihood unnecessary, and allows the non-linear modelling of observational errors that take into account correlations in the data and non-Gaussian distributions. We obtain an $M_{200}$ mass estimate $M_{rm MW+M31} = 4.6^{+2.3}_{-1.8} times 10^{12} M_{odot}$ ($68 %$ C.L.), in agreement with previous estimates both for the sum of the two masses and for the individual masses. This result is not only one of the most reliable estimates of the sum of the two masses to date, but is also an illustration of likelihood-free inference in a problem with only one parameter and only three data points.
Dwarf galaxies are known to have remarkably low star formation efficiency due to strong feedback. Adopting the dwarf galaxies of the Milky Way as a laboratory, we explore a flexible semi-analytic galaxy formation model to understand how the feedback
We present the first comparison between the lifetime star formation histories (SFHs) of M31 and Milky Way (MW) satellites. Using the Advanced Camera for Surveys aboard the Hubble Space Telescope, we obtained deep optical imaging of Andromeda II (M$_{
We present a suite of high-resolution cosmological zoom-in simulations to $z=4$ of a $10^{12},{rm M}_{odot}$ halo at $z=0$, obtained using seven contemporary astrophysical simulation codes widely used in the numerical galaxy formation community. Phys
Studying our Galaxy, the Milky Way (MW), gives us a close-up view of the interplay between cosmology, dark matter, and galaxy formation. In the next decade our understanding of the MWs dynamics, stellar populations, and structure will undergo a revol
Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We combine the redshift information from the galaxy photometry with constraints