Abstract
Abstract RR Lyrae stars may be the best practical tracers of Galactic halo (sub-)structure and kinematics. The PanSTARRS1 (PS1) 3 π 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's sparse, asynchronous multi-band light curves ( ≲ 12 epochs in each of five bands, taken over a 4.5 year period). We present a novel template fitting technique that uses well-defined and physically motivated multi-band light curves of RR Lyrae stars, and demonstrate that we get accurate period estimates, precise to 2 s in > 80 % of cases. We augment these light-curve fits with other features from photometric time-series and provide them to progressively more detailed machine-learned classification models. From these models, we are able to select the widest (three-fourths of the sky) and deepest (reaching 120 kpc) sample of RR Lyrae stars to date. The PS1 sample of ∼45,000 RRab stars is pure (90%) and complete (80% at 80 kpc) at high galactic latitudes. It also provides distances that are precise to 3%, measured with newly derived period–luminosity relations for optical/near-infrared PS1 bands. With the addition of proper motions from Gaia and radial velocity measurements from multi-object spectroscopic surveys, we expect the PS1 sample of RR Lyrae stars to become the premier source for studying the structure, kinematics, and the gravitational potential of the Galactic halo. The techniques presented in this study should translate well to other sparse, multi-band data sets, such as those produced by the Dark Energy Survey and the upcoming Large Synoptic Survey Telescope Galactic plane sub-survey.
Highlights
The Galactic halo contains remnants of accreted satellites that were disrupted by tidal forces and stretched into stellar tidal streams and clouds (e.g., Ibata et al 2001; Belokurov et al 2007; Sesar et al 2015; Bernard et al 2016)
The techniques presented in this study should translate well to other sparse, multi-band data sets, such as those produced by the Dark Energy Survey and the upcoming Large Synoptic Survey Telescope Galactic plane sub-survey
To verify whether the choice of the development set significantly affects the tuning of hyperparameters, we evaluate the performance of the tuned model on the evaluation set, and repeat the tuning process, but this time we use the evaluation set for tuning and the development set for evaluation
Summary
The Galactic halo contains remnants of accreted satellites (i.e., dwarf galaxies and globular clusters) that were disrupted by tidal forces and stretched into stellar tidal streams and clouds (e.g., Ibata et al 2001; Belokurov et al 2007; Sesar et al 2015; Bernard et al 2016). To measure the total mass of the Milky Way and find the faintest dwarf satellites, we need to trace the spatial and kinematic structure and substructure (i.e., stellar streams) of the Galactic halo over the greatest possible distances and with the highest possible precision in distance and velocity, and the best tracers for this task are RR Lyrae stars. RR Lyrae stars are old (age > 10 Gyr), metal-poor ([Fe/H] < −0.5 dex), pulsating horizontal branch stars with periodically variable light curves (periods ranging from 0.2 to 0.9 days; Smith 2004) They are bright stars (MV = 0.6±0.1 mag) with distinct light curves which makes them easy to identify with time-domain imaging surveys, even to large distances (5-120 kpc for surveys with a 14 < V < 21 magnitude range; e.g., Sesar et al 2010). The purer samples of RR Lyrae stars that this work delivers are especially important for studies of the Galactic halo (e.g., when searching for low-luminosity dwarf satellites), as stars incorrectly identified as RR Lyrae stars may cause appearance of spurious halo substructures (Sesar et al 2010)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
