Panchromatic characterization of the Y0 brown dwarf WISEP J173835.52+273258.9 using JWST/MIRI
Bibliographic record
Abstract
Context . Cold brown dwarf atmospheres provide a good training ground for the analysis of atmospheres of temperate giant planets. WISEP J173835.52+273258.9 (WISE 1738) is an isolated cold brown dwarf and a Y0 spectral standard with a temperature between 350-400 K, lying at the boundary of the T-Y transition. Although its atmosphere has been extensively studied in the near-infrared, its bulk physical parameters and atmospheric chemistry and dynamics are not well understood. Aims . Using a Mid-Infrared Instrument (MIRI) medium-resolution spectrum (5-18 μm), combined with near-infrared spectra (0.982.2 μm) from Hubble Space Telescope’s (HST) Wide Field Camera 3 (WFC3) and Gemini Observatory’s Near-Infrared Spectrograph (GNIRS), we aim to accurately characterize the atmospheric chemistry and bulk physical parameters of WISE 1738. Methods . We perform a combined atmospheric retrieval on the MIRI, GNIRS, and WFC3 spectra using a machine learning algorithm called Neural Posterior Estimation (NPE) assuming a cloud-free model implemented using petitRADTRANS . We demonstrate how this combined retrieval approach ensures robust constraints on the abundances of major atmospheric species, the pressure-temperature ( P - T ) profile, bulk C/O, and metallicity [M/H], along with bulk physical properties such as effective temperature, radius, surface gravity, mass, and luminosity. We estimate 1D and 2D marginal posterior distributions for the constrained parameters and evaluate our results using several qualitative and quantitative Bayesian diagnostics, including Local Classifier 2-Sample Test (L-C2ST), coverage, and posterior predictive checks. Results . The combined atmospheric retrieval confirms previous constraints on H 2 O, CH 4 , NH 3 , and for the first time provides constraints on CO, CO 2 , and 15 NH 3 . It also gives better constraints on the physical parameters and the P - T profile while also revealing potential biases in characterizing objects using data from limited wavelength ranges. The retrievals further suggest the presence of disequilibrium chemistry, as evidenced by the constrained abundances of CO and CO 2 , which are otherwise expected to be depleted and hence not visible beyond the near-infrared wavelengths under equilibrium conditions. We estimate the physical parameters of the object as follows: an effective temperature of 402 −9 +12 K, surface gravity (log g ) of 4.43 −0.34 +0.26 cm s −2 , mass of 13 −7 +11 M Jup , radius of 1.14 −0.03 +0.03 R Jup , and a bolometric luminosity of −6.52 −0.04 +0.05 log L/L ⊙ . Based on these values, the evolutionary models suggest an age between 1 and 4 Gyr, which is consistent with a high rotation rate of 6 h of the brown dwarf. We further obtain an upper bound on the 15 NH 3 abundance, enabling a 3σ lower bound calculation of the 14 N/ 15 N ratio = 275, unable to interpret the formation pathway as core collapse. Additionally, we calculate a C/O ratio of 1.35 −0.31 +0.39 and a metallicity of 0.34 −0.11 +0.12 without considering any oxygen sequestration effects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".