Uncovering dark matter density profiles in dwarf galaxies with graph neural networks

Abstract

Dwarf galaxies are small, dark matter-dominated galaxies, some of which are embedded within the Milky Way. Their lack of baryonic matter (e.g., stars and gas) makes them perfect test beds for probing the properties of dark matter -- understanding the spatial dark matter distribution in these systems can be used to constrain microphysical dark matter interactions that influence the formation and evolution of structures in our Universe. We introduce a new method that leverages simulation-based inference and graph-based machine learning in order to infer the dark matter density profiles of dwarf galaxies from observable kinematics of stars gravitationally bound to these systems. Our approach aims to address some of the limitations of established methods based on dynamical Jeans modeling. We show that this novel method can place stronger constraints on dark matter profiles and, consequently, has the potential to weigh in on some of the ongoing puzzles associated with the small-scale structure of dark matter halos, such as the core-cusp discrepancy.

9 + 11 pages, 4 + 9 figures

References in corpus (15)

• Array Programming with NumPy
• The Kinematics of the Ultra-Faint Milky Way Satellites: Solving the Missing Satellite Problem
• High-resolution mass models of dwarf galaxies from LITTLE THINGS
• Cosmological puzzle resolved by stellar feedback in high redshift galaxies
• Stellar Velocities in the Carina, Fornax, Sculptor and Sextans dSph Galaxies: Data from the Magellan/MMFS Survey
• The Velocity Dispersion Profile of the Remote Dwarf Spheroidal Galaxy Leo I: A Tidal Hit and Run?
• Dwarf galaxy annihilation and decay emission profiles for dark matter experiments
• The Most Dark Matter Dominated Galaxies: Predicted Gamma-ray Signals from the Faintest Milky Way Dwarfs
• A Comprehensive Search for Dark Matter Annihilation in Dwarf Galaxies
• Spherical Jeans analysis for dark matter indirect detection in dwarf spheroidal galaxies - Impact of physical parameters and triaxiality
• Determining the Nature of Dark Matter with Astrometry
• A discrete chemo-dynamical model of the dwarf spheroidal galaxy Sculptor: mass profile, velocity anisotropy and internal rotation
• When the Jeans don't fit: How stellar feedback drives stellar kinematics and complicates dynamical modeling in low-mass galaxies
• A model-independent analysis of the Fermi Large Area Telescope gamma-ray data from the Milky Way dwarf galaxies and halo to constrain dark matter scenarios
• Breaking Beta: A comparison of mass modelling methods for spherical systems

Cited by in corpus (8)

• Astrophysical Tests of Dark Matter Self-Interactions
• The Supersonic Project: The eccentricity and rotational support of SIGOs and DM GHOSts
• Trial by FIRE: Probing the dark matter density profile of dwarf galaxies with GraphNPE
• Central densities of dark matter halos in FIRE-2 simulations of low-mass galaxies with cold dark matter and self-interacting dark matter
• Galaxy mass profiles with convolutional neural networks
• Towards characterizing dark matter subhalo perturbations in stellar streams with graph neural networks
• The dynamical memory of tidal stellar streams: Joint inference of the Galactic potential and the progenitor of GD-1 with flow matching
• Beyond single tracers: CNN-based inference of galaxy mass profiles from combined gas and stellar kinematics