Eclipsing Binary Science Via the Merging of Transit and Doppler Exoplanet Survey Data - A Case Study With the MARVELS Pilot Project and SuperWASP

Details Eclipsing Binary Science Via the Merging of Transit and Doppler Exoplanet Survey Data - A Case Study With the MARVELS Pilot Project and SuperWASP Eclipsing Binary Science Via the Merging of Transit and Doppler Exoplanet Survey Data - A Case Study With the MARVELS Pilot Project and SuperWASP

2011-05-10

arxiv.org/abs/1105.2027v1

Astronomy and Astrophysics

Astrophysics

Solar and Stellar Astrophysics

Accepted for publication in AJ

Scientific paper

Exoplanet transit and Doppler surveys discover many binary stars during their operation that can be used to conduct a variety of ancillary science. Specifically, eclipsing binary stars can be used to study the stellar mass-radius relationship and to test predictions of theoretical stellar evolution models. By cross-referencing 24 binary stars found in the MARVELS Pilot Project with SuperWASP photometry, we find two new eclipsing binaries, TYC 0272-00458-1 and TYC 1422-01328-1, which we use as case studies to develop a general approach to eclipsing binaries in survey data. TYC 0272-00458-1 is a single-lined spectroscopic binary for which we calculate a mass of the secondary and radii for both components using reasonable constraints on the primary mass through several different techniques. For a primary mass of M_1 = 0.92 +/- 0.1 M_solar, we find M_2 = 0.610 +/- 0.036 M_solar, R_1 = 0.932 +/- 0.076 R_solar and R_2 = 0.559 +/- 0.102 R_solar, and find that both stars have masses and radii consistent with model predictions. TYC 1422-01328-1 is a triple-component system for which we can directly measure the masses and radii of the eclipsing pair. We find that the eclipsing pair consists of an evolved primary star (M_1 = 1.163 +/- 0.034 M_solar, R_1 = 2.063 +/- 0.058 R_solar) and a G-type dwarf secondary (M_2 = 0.905 +/- 0.067 M_solar, R_2 = 0.887 +/- 0.037 R_solar). We provide the framework necessary to apply this analysis to much larger datasets.

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