Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes
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 spectr...
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IOP Publishing
2025-01-01
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| Series: | The Astrophysical Journal |
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| Online Access: | https://doi.org/10.3847/1538-4357/adef04 |
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| author | Yoav Rotman Luis Welbanks Michael R. Line Peter McGill Michael Radica Matthew C. Nixon |
| author_facet | Yoav Rotman Luis Welbanks Michael R. Line Peter McGill Michael Radica Matthew C. Nixon |
| author_sort | Yoav Rotman |
| collection | DOAJ |
| description | 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 CO _2 and H _2 O, 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. |
| format | Article |
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| institution | Kabale University |
| issn | 1538-4357 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
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| series | The Astrophysical Journal |
| spelling | doaj-art-fef66bf4d53b48a49a51a6375500d9202025-08-20T04:03:17ZengIOP PublishingThe Astrophysical Journal1538-43572025-01-01989220110.3847/1538-4357/adef04Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian ProcessesYoav Rotman0https://orcid.org/0000-0003-4459-9054Luis Welbanks1https://orcid.org/0000-0003-0156-4564Michael R. Line2https://orcid.org/0000-0001-6247-8323Peter McGill3https://orcid.org/0000-0002-1052-6749Michael Radica4https://orcid.org/0000-0002-3328-1203Matthew C. Nixon5https://orcid.org/0000-0001-8236-5553School of Earth and Space Exploration, Arizona State University , Tempe, AZ 85287, USA ; yrotman@asu.edu, luis.welbanks@asu.eduSchool of Earth and Space Exploration, Arizona State University , Tempe, AZ 85287, USA ; yrotman@asu.edu, luis.welbanks@asu.eduSchool of Earth and Space Exploration, Arizona State University , Tempe, AZ 85287, USA ; yrotman@asu.edu, luis.welbanks@asu.eduSpace Science Institute , Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94550, USADepartment of Astronomy & Astrophysics, University of Chicago , 5640 South Ellis Avenue, Chicago, IL 60637, USADepartment of Astronomy, University of Maryland , College Park, MD 20742, USAAtmospheric 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 CO _2 and H _2 O, 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.https://doi.org/10.3847/1538-4357/adef04Exoplanet atmospheresExoplanet astronomyInfrared spectroscopyExoplanetsHot JupitersBayesian statistics |
| spellingShingle | Yoav Rotman Luis Welbanks Michael R. Line Peter McGill Michael Radica Matthew C. Nixon Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes The Astrophysical Journal Exoplanet atmospheres Exoplanet astronomy Infrared spectroscopy Exoplanets Hot Jupiters Bayesian statistics |
| title | Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes |
| title_full | Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes |
| title_fullStr | Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes |
| title_full_unstemmed | Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes |
| title_short | Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes |
| title_sort | enabling robust exoplanet atmospheric retrievals with gaussian processes |
| topic | Exoplanet atmospheres Exoplanet astronomy Infrared spectroscopy Exoplanets Hot Jupiters Bayesian statistics |
| url | https://doi.org/10.3847/1538-4357/adef04 |
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