Description
We have developed a fully automated pipeline for systematically identifying and analyzing eclipsing binaries within large data sets of light curves. The pipeline is made up of multiple tiers that subject the light curves to increasing levels of scrutiny. After each tier, light curves that did not conform to a given criteria were filtered out of the pipeline, reducing the load on the following, more computationally intensive tiers. As a central component of the pipeline, we created the fully automated Detached Eclipsing Binary Light curve fitter (DEBiL), which rapidly fits large numbers of light curves to a simple model. Using the results of DEBiL, light curves of interest can be flagged for follow-up analysis. As a test case, we analyzed the 218,699 light curves within the bulge fields of the OGLE II survey and produced 10,862 model fits. We point out a small number of extreme examples, as well as unexpected structure found in several of the population distributions. We expect this approach to become increasingly important as light-curve data sets continue growing in both size and number.
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