• DOI:10.3847/1538-3881/ab1f46
• Corpus ID: 143423393

Identification of RR Lyrae Stars in Multiband, Sparsely Sampled Data from the Dark Energy Survey Using Template Fitting and Random Forest Classification

@article{Stringer2019IdentificationOR,
  title={Identification of RR Lyrae Stars in Multiband, Sparsely Sampled Data from the Dark Energy Survey Using Template Fitting and Random Forest Classification},
  author={K. M. Stringer and James P. Long and Lucas M. Macri and Jennifer L. Marshall and Alex Drlica-Wagner and Clara E. Mart'inez-V'azquez and Anna Katherina Vivas and Keith C. Bechtol and Eric Morganson and Matias Carrasco Kind and Andrew B. Pace and Alistair R. Walker and C. Nielsen and T. S. Li and Eli S. Rykoff and David L. Burke and Aurelio Carnero Rosell and Eric H. Neilsen and P. S. Ferguson and Sarah A. Cantu and J. L. Myron and Louis E. Strigari and Arya Farahi and F. Paz-Chinch'on and Douglas L. Tucker and Z Lin and Dylan Hatt and Jenny Maner and L. Plybon and Alexander H. Riley and Ethan O. Nadler and Timothy M. C. Abbott and Sahar Allam and James T. Annis and Emmanuel Bertin and David Brooks and Elizabeth Buckley-Geer and Jorge Carretero and Carlos E. Cunha and Chris D'Andrea and Luiz Nicolaci da Costa and Juan de Vicente and Shantanu Desai and Peter Doel and T. F. Eifler and Brenna L. Flaugher and Joshua A. Frieman and Juan Garc'ia-Bellido and Enrique Gazta{\~n}aga and Daniel Gruen and Julia Gschwend and Gaston R. Guti{\'e}rrez and William G. Hartley and Devon L. Hollowood and Ben Hoyle and David J. James and Kyler W. Kuehn and Nikolay Kuropatkin and Peter Melchior and Ramon Miquel and R. L. C. Ogando and Andreas Alejandro Plazas and Eusebio S{\'a}nchez and Bas{\'i}lio Xavier Santiago and Victor E. Scarpine and Michael S. Schubnell and Santiago Serrano and Ignacio Sevilla-Noarbe and M. Smith and R. C. Smith and Marcelle Soares-Santos and Flavia Sobreira and Eric Suchyta and Mollye E. C. Swanson and Gregory G. Tarl{\'e} and D. Thomas and Vinu Vikram and Brian Yanny},
  journal={The Astronomical Journal},
  year={2019},
  volume={158}
}

• K. Stringer, J. P. Long, +75 authors B. Yanny
• Published 1 May 2019
• Physics
• The Astronomical Journal

Many studies have shown that RR Lyrae variable stars (RRL) are powerful stellar tracers of Galactic halo structure and satellite galaxies. The Dark Energy Survey (DES), with its deep and wide coverage (g ∼ 23.5 mag in a single exposure; over 5000 deg2) provides a rich opportunity to search for substructures out to the edge of the Milky Way halo. However, the sparse and unevenly sampled multiband light curves from the DES wide-field survey (a median of four observations in each of grizY over the first three years) pose a challenge for traditional techniques used to detect RRL. We present an empirically motivated and computationally efficient template-fitting method to identify these variable stars using three years of DES data. When tested on DES light curves of previously classified objects in SDSS stripe 82, our algorithm recovers 89% of RRL periods to within 1% of their true value with 85% purity and 76% completeness. Using this method, we identify 5783 RRL candidates, ∼28% of which are previously undiscovered. This method will be useful for identifying RRL in other sparse multiband data sets.