arXiv · 2502.11758
EBOP MAVEN: A machine learning model for predicting eclipsing binary light curve fitting parameters
Abstract
Detached eclipsing binary stars (dEBs) are a key source of data on fundamental stellar parameters. While there is a vast source of candidate systems in the light curve databases of survey missions such as Kepler and TESS, published catalogues of well-characterised systems fall short of reflecting this abundance. We seek to improve the efficiency of efforts to process these data with the development of a machine learning model to inspect dEB light curves and predict the input parameters for subsequent formal analysis by the jktebop code.
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Stephen Overall, John Southworth. 2025-02-17. EBOP MAVEN: A machine learning model for predicting eclipsing binary light curve fitting parameters. https://arxiv.org/abs/2502.11758
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