2D Retrieval Frameworks for Hot Jupiter Phase Curves
Y. Katherina Feng, Michael R. Line, Jonathan J. Fortney

TL;DR
This paper introduces a 2D retrieval framework for hot Jupiter phase curves, improving atmospheric property inferences by capturing phase-dependent geometry, and demonstrates its advantages over traditional 1D models through simulations and real data application.
Contribution
The paper develops a novel 2D retrieval approach for exoplanet phase curves, addressing biases in 1D models and enhancing accuracy in atmospheric characterization.
Findings
2D models reduce biases in molecular abundance estimates.
Joint fitting of all phases improves abundance precision by a factor of 2.
2D retrievals are strongly favored for JWST data.
Abstract
Spectroscopic phase curves provide unique access to the three-dimensional properties of transiting exoplanet atmospheres. However, a modeling framework must be developed to deliver accurate inferences of atmospheric properties for these complex data sets. Here, we develop an approach to retrieve temperature structures and molecular abundances from phase curve spectra at any orbital phase. In the context of a representative hot Jupiter with a large day-night temperature contrast, we examine the biases in typical one-dimensional (1D) retrievals as a function of orbital phase/geometry, compared to two-dimensional (2D) models that appropriately capture the disk-integrated phase geometry. We guide our intuition by applying our new framework on a simulated HST+Spitzer phase curve data set in which the "truth" is known, followed by an application to the spectroscopic phase curve of the…
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