Identifying and Fitting Eclipse Maps of Exoplanets with Cross-Validation
Mark Hammond, Neil T. Lewis, Sasha Boone, Xueqing Chen, Jo\~ao M., Mendon\c{c}a, Vivien Parmentier, Jake Taylor, Taylor Bell, Leonardo dos, Santos, Nicolas Crouzet, Laura Kreidberg, Michael Radica, Michael Zhang

TL;DR
This paper introduces a cross-validation based method for more reliably detecting and fitting eclipse maps of exoplanets, addressing the challenge of imbalanced information content in light curve data.
Contribution
The authors develop a novel cross-validation approach that tests for eclipse mapping signals and optimizes map complexity, improving the reliability of exoplanet surface mapping.
Findings
Successfully identified eclipse mapping signals in JWST data for WASP-43b.
Detected no signals in other datasets, indicating potential overfitting in previous maps.
Produced a new, more spatially flexible map of WASP-43b showing a flatter east-west structure.
Abstract
Eclipse mapping uses the shape of the eclipse of an exoplanet to measure its two-dimensional structure. Light curves are mostly composed of longitudinal information, with the latitudinal information only contained in the brief ingress and egress of the eclipse. This imbalance can lead to a spuriously confident map, where the longitudinal structure is constrained by out-of-eclipse data and the latitudinal structure is wrongly determined by the priors on the map. We present a new method to address this issue. The method tests for the presence of an eclipse mapping signal by using k-fold cross-validation to compare the performance of a simple mapping model to the null hypothesis of a uniform disk. If a signal is found, the method fits a map with more degrees of freedom, optimising its information content. The information content is varied by penalising the model likelihood by a factor…
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Taxonomy
TopicsAstronomy and Astrophysical Research
