Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes

Journal Article · Mon Aug 18 00:00:00 EDT 2025 · The Astrophysical Journal

DOI:https://doi.org/10.3847/1538-4357/adef04· OSTI ID:2587419

Rotman, Yoav ^[1]; Welbanks, Luis ^[1]; Line, Michael R. ^[1]; McGill, Peter ^[2]; Radica, Michael ^[3]; Nixon, Matthew C. ^[4]

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1. Arizona State Univ., Tempe, AZ (United States)
2. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
3. Univ. of Chicago, IL (United States)
4. Univ. of Maryland, College Park, MD (United States)

Atmospheric retrievals are essential tools for interpreting exoplanet transmission and eclipse spectra, enabling quantitative constraints on the chemical composition, aerosol properties, and thermal structure of planetary atmospheres. The James Webb Space Telescope (JWST) offers unprecedented spectral precision, resolution, and wavelength coverage, unlocking transformative insights into the formation, evolution, climate, and potential habitability of planetary systems. However, this opportunity is accompanied by challenges: modeling assumptions and unaccounted-for noise or signal sources can bias retrieval outcomes and their interpretation. To address these limitations, we introduce a Gaussian process (GP)-aided atmospheric retrieval framework that flexibly accounts for unmodeled features and correlated noise in exoplanet spectra. We validate this method on synthetic JWST observations, and show that GP-aided retrievals reduce bias in inferred abundances and better capture model–data mismatches than traditional approaches. We also introduce the concept of mean squared error to quantify the trade-off between bias and variance, arguing that this metric more accurately reflects retrieval performance than bias alone. We then reanalyze the NIRISS/SOSS JWST transmission spectrum of WASP-96 b, finding that GP-aided retrievals yield broader constraints on CO₂ and H₂O, possibly alleviating tension between previous retrieval results and equilibrium predictions. Our GP framework provides precise and accurate constraints while highlighting regions where models fail to explain the data. As JWST matures and future facilities come online, a deeper understanding of the limitations of both data and models will be essential, and GP-enabled retrievals like the one presented here offer a principled path forward.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: National Aeronautics and Space Administration (NASA); USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: AC52-07NA27344
• OSTI ID: 2587419
• Report Number(s): LLNL--JRNL-2003715
• Journal Information: The Astrophysical Journal, Journal Name: The Astrophysical Journal Journal Issue: 2 Vol. 989; ISSN 0004-637X; ISSN 1538-4357
• Publisher: American Astronomical Society
• Country of Publication: United States
• Language: English