Machine-learned Identification of RR lyrae stars from sparse, multi-band data: the PS1 Sample
RR Lyrae stars may be the best practical tracers of Galactic halo (sub-)structure and kinematics. The PanSTARRS1 (PS1) $3\pi$ survey offers multi-band, multi-epoch, precise photometry across much of the sky, but a robust identification of RR Lyrae stars in this data set poses a challenge, given PS1&...
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| Main Authors: | , |
|---|---|
| Format: | Article (Journal) Chapter/Article |
| Language: | English |
| Published: |
2017
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| In: |
Arxiv
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| Online Access: | Verlag, kostenfrei, Volltext: http://arxiv.org/abs/1611.08596
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| Author Notes: | Branimir Sesar, Nina Hernitschek, Sandra Mitrović, Željko Ivezić, Hans-Walter Rix, Judith G. Cohen, Edouard J. Bernard, Eva K. Grebel, Nicolas F. Martin, Edward F. Schlafly, William S. Burgett, Peter W. Draper, Heather Flewelling, Nick Kaiser, Rolf P. Kudritzki, Eugene A. Magnier, Nigel Metcalfe, John L. Tonry, and Christopher Waters |
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