Action-space clustering of tidal streams to infer the Galactic potential
Robyn E. Sanderson, Amina Helmi, David W. Hogg

TL;DR
This paper introduces a novel method for constraining the Milky Way's gravitational potential by analyzing the clustering of tidal stream stars in action space, without needing stream membership identification.
Contribution
The method uses action-space clustering quantified by Kullback-Leibler Divergence to infer potential parameters from full 3D stellar data, improving accuracy without stream membership.
Findings
Achieves 3% accuracy in enclosed mass measurement.
Requires 15-25 streams for reliable parameter bounds.
Radial velocities significantly improve parameter precision.
Abstract
We present a new method for constraining the Milky Way halo gravitational potential by simultaneously fitting multiple tidal streams. This method requires full three-dimensional positions and velocities for all stars to be fit, but does not require identification of any specific stream or determination of stream membership for any star. We exploit the principle that the action distribution of stream stars is most clustered when the potential used to calculate the actions is closest to the true potential. Clustering is quantified with the Kullback-Leibler Divergence (KLD), which also provides conditional uncertainties for our parameter estimates. We show, for toy Gaia-like data in a spherical isochrone potential, that maximizing the KLD of the action distribution relative to a smoother distribution recovers the true values of the potential parameters. The precision depends on the…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Scientific Research and Discoveries
