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A Machine Learning Approach to Exoplanet Atmospheric Retrieval: Application to Optical Filter Ranking

  • Authors: Patcharawee Munsaket, Supachai Awiphan, Poemwai Chainakun, Eamonn Kerins, Napaporn A-thano

Patcharawee Munsaket et al 2026 The Astronomical Journal 172 .

  • Provider: AAS Journals

Caption: Figure 7.

Comparison of the performance of nestle and the RFR model in retrieving four planetary parameters from transmission spectra of 50 exoplanets: (top-left) planetary radius (Rp), (top-right) ﹩\mathrm{log}({T}_{p})﹩, (bottom-left) ﹩\mathrm{log}({X}_{{\rm{TiO}}})﹩, and (bottom-right) ﹩\mathrm{log}({X}_{{\rm{V\; O}}})﹩. Orange points represent the retrieval results from nestle, while purple points represent the predictions from the RFR model. The dashed line marks the one-to-one relation. Both methods are able to extract these parameters with high accuracy. See text for more details.

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