A Next-Generation Exoplanet Atmospheric Retrieval Framework for Transmission Spectroscopy (NEXOTRANS): Comparative Characterization for WASP-39 b Using JWST NIRISS, NIRSpec PRISM, and MIRI Observations

The advent of JWST has marked a new era in exoplanetary atmospheric studies, offering higher-resolution data and greater precision across a broader spectral range than previous space-based telescopes. Accurate analysis of these datasets requires advanced retrieval frameworks capable of navigating complex parameter spaces. We present NEXOTRANS, an atmospheric retrieval framework that integrates Bayesian inference using UltraNest/PyMultiNest with four machine learning algorithms: Random Forest, Gradient Boosting, K-Nearest Neighbor, and Stacking Regressor. This hybrid approach enables a comparison between traditional Bayesian methods and computationally efficient machine learning techniques. Additionally, NEXOTRANS incorporates NEXOCHEM, a module for solving equilibrium chemistry. We applied NEXOTRANS to JWST observations of the Saturn-mass exoplanet WASP-39 b, spanning wavelengths from 0.6 microns to 12.0 microns using NIRISS, NIRSpec PRISM, and MIRI. Four chemistry models - free, equilibrium, modified hybrid equilibrium, and modified equilibrium-offset chemistry - were explored to retrieve precise Volume Mixing Ratios (VMRs) for H2O, CO2, CO, H2S, and SO2. Absorption features in both NIRSpec PRISM and MIRI data constrained SO2 log VMRs to values between -6.25 and -5.73 for all models except equilibrium chemistry. High-altitude aerosols, including ZnS and MgSiO3, were inferred, with constraints on their VMRs, particle sizes, and terminator coverage fractions, providing insights into cloud composition. For the best-fit modified hybrid equilibrium model, we derived super-solar elemental abundances of O/H = 14.12 (+2.86/-1.82) x solar, C/H = 21.37 (+4.93/-3.18) x solar, and S/H = 5.37 (+0.79/-0.65) x solar, along with a C/O ratio of 1.35 (+0.05/-0.02) x solar, demonstrating NEXOTRANS's potential for atmospheric characterization in the JWST era and beyond.

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ArXiv.org
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2025-04-26
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Astro and Planetary Science
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article

A Next-Generation Exoplanet Atmospheric Retrieval Framework for Transmission Spectroscopy (NEXOTRANS): Comparative Characterization for WASP-39 b Using JWST NIRISS, NIRSpec PRISM, and MIRI Observations

ArXiv.org
Astro and Planetary Science
article

A Next-Generation Exoplanet Atmospheric Retrieval Framework for Transmission Spectroscopy (NEXOTRANS): Comparative Characterization for WASP-39 b Using JWST NIRISS, NIRSpec PRISM, and MIRI Observations

article en

Abstract

The advent of JWST has marked a new era in exoplanetary atmospheric studies, offering higher-resolution data and greater precision across a broader spectral range than previous space-based telescopes. Accurate analysis of these datasets requires advanced retrieval frameworks capable of navigating complex parameter spaces. We present NEXOTRANS, an atmospheric retrieval framework that integrates Bayesian inference using UltraNest/PyMultiNest with four machine learning algorithms: Random Forest, Gradient Boosting, K-Nearest Neighbor, and Stacking Regressor. This hybrid approach enables a comparison between traditional Bayesian methods and computationally efficient machine learning techniques. Additionally, NEXOTRANS incorporates NEXOCHEM, a module for solving equilibrium chemistry. We applied NEXOTRANS to JWST observations of the Saturn-mass exoplanet WASP-39 b, spanning wavelengths from 0.6 microns to 12.0 microns using NIRISS, NIRSpec PRISM, and MIRI. Four chemistry models - free, equilibrium, modified hybrid equilibrium, and modified equilibrium-offset chemistry - were explored to retrieve precise Volume Mixing Ratios (VMRs) for H2O, CO2, CO, H2S, and SO2. Absorption features in both NIRSpec PRISM and MIRI data constrained SO2 log VMRs to values between -6.25 and -5.73 for all models except equilibrium chemistry. High-altitude aerosols, including ZnS and MgSiO3, were inferred, with constraints on their VMRs, particle sizes, and terminator coverage fractions, providing insights into cloud composition. For the best-fit modified hybrid equilibrium model, we derived super-solar elemental abundances of O/H = 14.12 (+2.86/-1.82) x solar, C/H = 21.37 (+4.93/-3.18) x solar, and S/H = 5.37 (+0.79/-0.65) x solar, along with a C/O ratio of 1.35 (+0.05/-0.02) x solar, demonstrating NEXOTRANS's potential for atmospheric characterization in the JWST era and beyond.

ArXiv.org
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Astro and Planetary Science
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