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Machine-learned Identification of RR Lyrae Stars from Sparse, Multi-band Data: The PS1 Sample

Sesar, Branimir and Hernitschek, Nina and Mitrović, Sandra and Ivezić, Željko and Rix, Hans-Walter and Cohen, Judith G. and Bernard, Edouard J. and Grebel, Eva K. and Martin, Nicolas F. and Schlafly, Edward F. and Burgett, William S. and Draper, Peter W. and Flewelling, Heather and Kaiser, Nick and Kudritzki, Rolf P. and Magnier, Eugene A. and Metcalfe, Nigel and Tonry, John L. and Waters, Christopher (2017) Machine-learned Identification of RR Lyrae Stars from Sparse, Multi-band Data: The PS1 Sample. Astronomical Journal, 153 (5). Art. No. 204. ISSN 1538-3881. doi:10.3847/1538-3881/aa661b.

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RR Lyrae stars may be the best practical tracers of Galactic halo (sub-)structure and kinematics. The PanSTARRS1 (PS1) 3π 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.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Sesar, Branimir0000-0002-0834-3978
Hernitschek, Nina0000-0003-1681-0430
Ivezić, Željko0000-0001-5250-2633
Rix, Hans-Walter0000-0003-4996-9069
Cohen, Judith G.0000-0002-8039-4673
Grebel, Eva K.0000-0002-1891-3794
Martin, Nicolas F.0000-0002-1349-202X
Schlafly, Edward F.0000-0002-3569-7421
Draper, Peter W.0000-0002-7204-9802
Flewelling, Heather0000-0002-1050-4056
Kaiser, Nick0000-0001-6511-4306
Magnier, Eugene A.0000-0002-7965-2815
Metcalfe, Nigel0000-0001-9034-4402
Tonry, John L.0000-0003-2858-9657
Additional Information:© 2017 The American Astronomical Society. Received 2016 November 25; revised 2017 March 7; accepted 2017 March 7; published 2017 April 7. B.S., N.H., and H.-W.R. acknowledge funding from the European Research Council under the European Unions Seventh Framework Programme (FP 7) ERC Grant Agreement n. [321035]. H.-W.R. acknowledges support of the Miller Institute at UC Berkeley through a visiting professorship during the completion of this work. We thank the anonymous referee for the thorough review, positive comments, and constructive remarks on this manuscript. The Pan-STARRS1 Surveys (PS1) have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg, and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen's University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, and the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), and the Los Alamos National Laboratory.
Group:Astronomy Department
Funding AgencyGrant Number
European Research Council (ERC)321035
University of MarylandUNSPECIFIED
Eotvos Lorand UniversityUNSPECIFIED
Los Alamos National LaboratoryUNSPECIFIED
Subject Keywords:catalogs – Galaxy: halo – methods: data analysis – methods: statistical – stars: variables: RR Lyrae – surveys
Issue or Number:5
Record Number:CaltechAUTHORS:20170410-132108269
Persistent URL:
Official Citation:Branimir Sesar et al 2017 AJ 153 204
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:76479
Deposited By: Tony Diaz
Deposited On:10 Apr 2017 21:00
Last Modified:15 Nov 2021 17:00

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