Toward Characterizing Dark Matter Subhalo Perturbations in Stellar Streams with Graph Neural Networks

The phase space of stellar streams is proposed to detect dark substructure in the Milky Way through the perturbations created by passing subhalos—and thus is a powerful test of the cold dark matter paradigm and its alternatives. Using graph convolutional neural network (GCNN) data compression and si...

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Bibliographic Details

Published in:	The Astrophysical Journal
Main Authors:	Peter Xiangyuan Ma, Keir K. Rogers, Ting S. Li, Renée Hložek, Jeremy J. Webb, Ruth Huang, Julian Meunier
Format:	Article
Language:	English
Published:	IOP Publishing 2025-01-01
Subjects:	Galaxy dynamics Galaxy dark matter halos Neural networks Astronomical simulations
Online Access:	https://doi.org/10.3847/1538-4357/add698