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ABSTRACT One of the most promising tracers of the Galactic potential in the halo region is stellar streams. However, individual stream fits can be limited by systematic biases. To study these individual stream systematics, we fit streams in Milky Way-like galaxies from Feedback In Realistic Environments cosmological galaxy formation simulations with an analytical gravitational potential by maximizing the clustering of stream stars in action space. We show that for coherent streams the quality of the constraints depends on the orbital phase of the observed stream stars, despite the fact that the phase information is discarded in action-clustering methods. Streams on intermediate phases give the most accurate results, whereas pericentre streams can be highly biased. This behaviour is tied to the amount of correlation present between positions and momenta in each stream’s data: weak correlation in pericentre streams prohibits efficient differentiation between potentials, while strong correlation in intermediate streams promotes it. Although simultaneous fitting of multiple streams is generally prescribed as the remedy to combat individual stream biases, we find that combining multiple pericentric streams is not enough to yield a bias-free result. We finally show that adopting the two-component Stäckel model does not fundamentally induce a biased mass estimate. With our full data set of two multiwrap streams, we recovered the true rotation curve of the simulated galaxy within $12{{\ \rm per\ cent}}$ over the entire range of radii covered by our set of stars (10–176 kpc) and within $6.5{{\ \rm per\ cent}}$ between the 5 and 95 percentile distance range (23–109 kpc). 

ABSTRACT Stream stars removed by tides from their progenitor satellite galaxy or globular cluster act as a group of test particles on neighbouring orbits, probing the gravitational field of the Milky Way. While constraints from individual streams have been shown to be susceptible to biases, combining several streams from orbits with various distances reduces these biases. We fit a common gravitational potential to multiple stellar streams simultaneously by maximizing the clustering of the stream stars in action space. We apply this technique to members of the GD-1, Palomar 5 (Pal 5), Orphan, and Helmi streams, exploiting both the individual and combined data sets. We describe the Galactic potential with a Stäckel model, and vary up to five parameters simultaneously. We find that we can only constrain the enclosed mass, and that the strongest constraints come from the GD-1, Pal 5, and Orphan streams whose combined data set yields $M(\lt 20\, \mathrm{kpc}) = 2.96^{+0.25}_{-0.26} \times 10^{11} \, \mathrm{ M}_{\odot}$. When including the Helmi stream in the data set, the mass uncertainty increases to $M(\lt 20\, \mathrm{kpc}) = 3.12^{+3.21}_{-0.46} \times 10^{11} \, \mathrm{M}_{\odot}$.