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Spitzer, Gaia, and the Potential of the Milky Way

1 Pith paper cite this work. Polarity classification is still indexing.

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abstract

Near-future data from ESA's Gaia mission will provide precise, full phase-space information for hundreds of millions of stars out to heliocentric distances of ~10 kpc. This "horizon" for full phase-space measurements is imposed by the Gaia parallax errors degrading to worse than 10%, and could be significantly extended by an accurate distance indicator. Recent work has demonstrated how Spitzer observations of RR Lyrae stars can be used to make distance estimates accurate to 2%, effectively extending the Gaia, precise-data horizon by a factor of ten in distance and a factor of 1000 in volume. This Letter presents one approach to exploit data of such accuracy to measure the Galactic potential using small samples of stars associated with debris from satellite destruction. The method is tested with synthetic observations of 100 stars from the end point of a simulation of satellite destruction: the shape, orientation, and depth of the potential used in the simulation are recovered to within a few percent. The success of this simple test with such a small sample in a single debris stream suggests that constraints from multiple streams could be combined to examine the Galaxy's dark matter halo in even more detail --- a truly unique opportunity that is enabled by the combination of Spitzer and Gaia with our intimate perspective on the Galaxy.

fields

astro-ph.GA 1

years

2019 1

verdicts

UNVERDICTED 1

representative citing papers

Applying Liouville's Theorem to Gaia Data

astro-ph.GA · 2019-07-01 · unverdicted · novelty 5.0

Phase-space density is recovered from Gaia data for M4 and disrupted streams by correcting entropy injection and minimizing stream entropy, enabling original mass inference via Liouville's theorem.

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Showing 1 of 1 citing paper.

  • Applying Liouville's Theorem to Gaia Data astro-ph.GA · 2019-07-01 · unverdicted · none · ref 51 · internal anchor

    Phase-space density is recovered from Gaia data for M4 and disrupted streams by correcting entropy injection and minimizing stream entropy, enabling original mass inference via Liouville's theorem.