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Register a new userAction-space clustering of tidal streams to infer the Galactic potential
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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 observational errors and the number of streams in the sample; using KIII giants as tracers, we measure the enclosed mass at the average radius of the sample stars accurate to 3% and precise to 20-40%. Recovery of the scale radius is precise to 25%, and is biased 50% high by the small galactocentric distance range of stars in our mock sample (1-25 kpc, or about three scale radii, with mean 6.5 kpc). About 15 streams, with at least 100 stars per stream, are needed to obtain upper and lower bounds on the enclosed mass and scale radius when observational errors are taken into account; 20-25 streams are required to stabilize the size of the confidence interval. If radial velocities are provided for stars out to 100 kpc (10 scale radii), all parameters can be determined with 10% accuracy and 20% precision (1.3% accuracy in the case of the enclosed mass), underlining the need for ground-based spectroscopic follow-up to complete the radial velocity catalog for faint halo stars observed by Gaia.
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Stream stars removed by tides from their progenitor satellite galaxy or globular cluster act as a group of test particles on neighboring 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, Pal 5, Orphan and Helmi streams, exploiting both the individual and combined data sets. We describe the Galactic potential with a Stackel 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 $M(< 20 mathrm{kpc}) = 2.96^{+0.25}_{-0.26} times 10^{11} M_{odot}$. When including the Helmi stream in the data set, the mass uncertainty increases to $M(< 20 mathrm{kpc}) = 3.12^{+3.21}_{-0.46} times 10^{11} M_{odot}$.
We explore the use of tidal streams from Galactic satellites to recover the potential of the Milky Way. Our study is motivated both by the discovery of the first lengthy stellar stream in the halo (cite{it98}) and by the prospect of measuring proper motions of stars brighter than 20th magnitude in such a stream with an accuracy of $sim 4mu as/$yr, as will be possible with the Space Interferometry Mission (SIM). We assume that the heliocentric radial velocities of these stars can be determined from supporting ground-based spectroscopic surveys, and that the mass and phase-space coordinates of the Galactic satellite with which they are associated will also be known to SIM accuracy. Using results from numerical simulations as trial data sets, we find that, if we assume the correct form for the Galactic potential, we can predict the distances to the stars as a consequence of the narrow distribution of energy expected along the streams. We develop an algorithm to evaluate the accuracy of any adopted potential by requiring that the satellite and stars recombine within a Galactic lifetime when their current phase-space coordinates are integrated backwards. When applied to a four-dimensional grid of triaxial logarithmic potentials, with varying circular velocities, axis ratios and orientation of the major-axis in the disk plane, the algorithm can recover the parameters used for the Milky Way in a simulated data set to within a few percent using only 100 stars in a tidal stream.
Dwarf galaxies that come too close to larger galaxies suffer tidal disruption; the differential gravitational force between one side of the galaxy and the other serves to rip the stars from the dwarf galaxy so that they instead orbit the larger galaxy. This process produces tidal streams of stars, which can be found in the stellar halo of the Milky Way, as well as in halos of other galaxies. This chapter provides a general introduction to tidal streams, including the mechanism through which the streams are created, the history of how they were discovered, and the observational techniques by which they can be detected. In addition, their use in unraveling galaxy formation history and the distribution of dark matter in galaxies is discussed, as is the interaction between these dwarf galaxy satellites and the disk of the larger galaxy.
The origins of most stellar streams in the Milky Way are unknown. With improved proper motions provided by Gaia EDR3, we show that the orbits of 23 Galactic stellar streams are highly clustered in orbital phase space. Based on their energies and angular momenta, most streams in our sample can plausibly be associated with a specific (disrupted) dwarf galaxy host that brought them into the Milky Way. For eight streams we also identify likely globular cluster progenitors (four of these associations are reported here for the first time). Some of these stream progenitors are surprisingly far apart, displaced from their tidal debris by a few to tens of degrees. We identify stellar streams that appear spatially distinct, but whose similar orbits indicate they likely originate from the same progenitor. If confirmed as physical discontinuities, they will provide strong constraints on the mass-loss from the progenitor. The nearly universal ex-situ origin of existing stellar streams makes them valuable tracers of galaxy mergers and dynamical friction within the Galactic halo. Their phase-space clustering can be leveraged to construct a precise global map of dark matter in the Milky Way, while their internal structure may hold clues to the small-scale structure of dark matter in their original host galaxies.
In the currently favored cosmological paradigm galaxies form hierarchically through the accretion of numerous satellite galaxies. Since the satellites are much less massive than the host halo, they occupy a small fraction of the volume in action space defined by the potential of the host halo. Since actions are conserved when the potential of the host halo changes adiabatically, stars from an accreted satellite are expected to remain clustered in action space as the host halo evolves. In this paper, we identify accreted satellites in three Milky Way like disk galaxies from the cosmological baryonic FIRE-2 simulations by tracking satellite galaxies through simulation snapshots. We then try to recover these satellites by applying the cluster analysis algorithm Enlink to the orbital actions of accreted star particles in the present-day snapshot. We define several metrics to quantify the success of the clustering algorithm and use these metrics to identify well-recovered and poorly-recovered satellites. We plot these satellites in the infall time-progenitor mass (or stellar mass) space, and determine the boundaries between the well-recovered and poorly-recovered satellites in these two spaces with classification tree method. The groups found by Enlink are more likely to correspond to a real satellite if they have high significance, a quantity assigned by Enlink. Since cosmological simulations predict that most stellar halos have a population of insitu stars, we test the ability of Enlink to recover satellites when the sample is contaminated by 10-50% of insitu star particles, and show that most of the satellites well-recovered by Enlink in the absence of insitu stars, stay well-recovered even with 50% contamination. We thus expect that, in the future, cluster analysis in action space will be useful in upcoming data sets (e.g. Gaia) for identifying accreted satellites in the Milky Way.
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