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

Author(s): Stringer, KM; Long, JP; Macri, LM; Marshall, JL; Drlica-Wagner, A; et al

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Abstract: 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 similar to 23.5 mag in a single exposure; over 5000 deg(2)) 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, similar to 28% of which are previously undiscovered. This method will be useful for identifying RRL in other sparse multiband data sets.
Publication Date: Jul-2019
Citation: Stringer, KM, Long, JP, Macri, LM, Marshall, JL, Drlica-Wagner, A, Martinez-Vaquez, CE, Vivas, AK, Bechtol, K, Morganson, E, Kind, M Carrasco, Pace, AB, Walker, AR, Nielsen, C, Li, TS, Rykoff, E, Burke, D, Carnero Rosell, A, Neilsen, E, Ferguson, P, Cantu, SA, Myron, JL, Strigari, L, Farahi, A, Paz-Chinchon, F, Tucker, D, Lin, Z, Hatt, D, Maner, JF, Plybon, L, Riley, AH, Nadler, EO, Abbott, TMC, Allam, S, Annis, J, Bertin, E, Brooks, D, Buckley-Geer, E, Carretero, J, Cunha, CE, D Andrea, CB, da Costa, LN, De Vicente, J, Desai, S, Doel, P, Eifler, TF, Flaugher, B, Frieman, J, Garcia-Bellido, J, Gaztanaga, E, Gruen, D, Gschwend, J, Gutierrez, G, Hartley, WG, Hollowood, DL, Hoyle, B, James, DJ, Kuehn, K, Kuropatkin, N, Melchior, P, Miquel, R, Ogando, RLC, Plazas, AA, Sanchez, E, Santiago, B, Scarpine, V, Schubnell, M, Serrano, S, Sevilla-Noarbe, I, Smith, M, Smith, RC, Soares-Santos, M, Sobreira, F, Suchyta, E, Swanson, MEC, Tarle, G, Thomas, D, Vikram, V, Yanny, B, Collaboration, DES. (2019). Identification of RR Lyrae Stars in Multiband, Sparsely Sampled Data from the Dark Energy Survey Using Template Fitting and Random Forest Classification. ASTRONOMICAL JOURNAL, 158 (10.3847/1538-3881/ab1f46
DOI: doi:10.3847/1538-3881/ab1f46
ISSN: 0004-6256
EISSN: 1538-3881
Type of Material: Journal Article
Journal/Proceeding Title: ASTRONOMICAL JOURNAL
Version: Final published version. Article is made available in OAR by the publisher's permission or policy.

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