The Digital Press

The new NEXOTRANS framework combines Bayesian inference with machine learning to analyze JWST exoplanet atmospheres more efficiently and accurately. Applying it to WASP-39 b data reveals detailed atmospheric chemistry, cloud properties, and elemental abundances.

Why it matters: NEXOTRANS improves precision in decoding exoplanet atmospheres using JWST’s broad spectral data.

The big picture: Integrating machine learning with Bayesian methods accelerates atmospheric retrievals while maintaining accuracy.

Stunning stat: WASP-39 b’s oxygen abundance is nearly 8 times solar, with a carbon-to-oxygen ratio 1.17 times solar.

Quick takeaway: High-altitude aerosols and multiple sulfur-bearing gases were detected, refining cloud and chemical composition models.