@Article{Villanueva-Domingo_etal2023,
author="Villanueva-Domingo, P.
and Villaescusa-Navarro, F.
and Genel, S.
and Angles-Alcazar, D.
and Hernquist, L.
and Marinacci, F.
and Spergel, D. N.
and Vogelsberger, M.
and Narayanan, D.",
title="Weighing the Milky Way and Andromeda galaxies with artificial intelligence",
journal="Physical Review D",
year="2023",
publisher="Amer Physical Soc",
volume="107",
number="10",
pages="103003--8pp",
abstract="We present new constraints on the masses of the halos hosting the Milky Way and Andromeda galaxies derived using graph neural networks. Our models, trained on 2,000 state-of-the-art hydrodynamic simulations of the CAMELS project, only make use of the positions, velocities and stellar masses of the galaxies belonging to the halos, and are able to perform likelihood-free inference on halo masses while accounting for both cosmological and astrophysical uncertainties. Our constraints are in agreement with estimates from other traditional methods, within our derived posterior standard deviation.",
optnote="WOS:000988340900001",
optnote="exported from refbase (https://references.ific.uv.es/refbase/show.php?record=5539), last updated on Sun, 11 Jun 2023 17:47:04 +0000",
issn="2470-0010",
doi="10.1103/PhysRevD.107.103003",
opturl="https://arxiv.org/abs/2111.14874",
opturl="https://doi.org/10.1103/PhysRevD.107.103003",
language="English"
}