Bringing 2D Eclipse Mapping out of the Shadows with Leave-one-out Cross-validation
Ryan C. Challener, Luis Welbanks, and Peter McGill

TL;DR
This paper applies Leave-one-out Cross-Validation to eclipse mapping of exoplanets, demonstrating its effectiveness in understanding model complexity, degeneracies, and guiding future analyses with JWST data.
Contribution
It introduces the use of LOO-CV for eclipse mapping, providing insights into model constraints, degeneracies, and the influence of eclipse features on brightness map complexity.
Findings
LOO-CV reveals the scale of features constrained by different eclipse phases.
Model complexity is driven by ingress and egress shapes, not outliers.
Degeneracy between hotspot and plateau models is clarified by LOO-CV analysis.
Abstract
Eclipse mapping is a technique for inferring 2D brightness maps of transiting exoplanets from the shape of an eclipse light curve. With JWST's unmatched precision, eclipse mapping is now possible for a large number of exoplanets. However, eclipse mapping has only been applied to two planets and the nuances of fitting eclipse maps are not yet fully understood. Here, we use Leave-one-out Cross- Validation (LOO-CV) to investigate eclipse mapping, with application to a JWST NIRISS/SOSS observation of the ultra-hot Jupiter WASP-18b. LOO-CV is a technique that provides insight into the out-of-sample predictive power of models on a data-point-by-data-point basis. We show that constraints on planetary brightness patterns behave as expected, with large-scale variations driven by the phase-curve variation in the light curve and smaller-scale structures constrained by the eclipse ingress and…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Astro and Planetary Science
