Clouds and Chemistry Across the Brown Dwarf T-Y Sequence: Insights from JWST Atmospheric Retrievals

TL;DR

This study uses JWST data to analyze the atmospheres of 22 late-T to Y brown dwarfs, revealing cloud properties, chemical disequilibrium, and atmospheric composition trends across the T-Y sequence.

Contribution

It applies Bayesian retrievals and machine learning to characterize brown dwarf atmospheres, highlighting the role of clouds and disequilibrium chemistry in the coldest objects.

Findings

Cloud-free models favored for hotter T dwarfs

Evidence of disequilibrium chemistry in several objects

Increasing H2O, CH4, NH3 abundances with decreasing temperature

Abstract

The James Webb Space Telescope (JWST) offers exceptional spectral resolution and wavelength coverage, which are essential for studying the coldest brown dwarfs, particularly Y dwarfs. These objects are at the cold end of the sub-stellar sequence and exhibit atmospheric phenomena such as cloud formation, chemical disequilibrium, and radiative-convective coupling. We examine a curated sample of 22 late-T to Y dwarfs through Bayesian atmospheric retrieval (nested sampling) and supervised machine learning (random forests). Bayesian model comparison indicates that cloud-free models are generally favored for the hottest objects in the sample (T6-T8). Conversely, later-type dwarfs exhibit varying preferences, with both gray-cloud and cloud-free models providing comparable fits. The atmospheric parameters retrieved are consistent across the applied methodologies. Evidence of vertical mixing and disequilibrium chemistry is found in several objects; notably, the Y1 dwarf WISEPAJ1541-22 favors a gray cloud model and shows elevated abundances of both CO and CO2 compared to equilibrium chemistry calculations. As anticipated, the abundances of H2O, CH4, and NH3 increase with decreasing effective temperature over the T-Y sequence.