A 1.48–2.48 μm <i>R</i> = 28 000 spectroscopic atlas of the L7.5 and T0.5 components of the nearest pair of brown dwarfs: Luhman 16AB
Bibliographic record
Abstract
ABSTRACT We present a high signal-to-noise (SNR $\sim$ 450), high-dispersion ($R \equiv \lambda / \Delta \lambda \sim$ 28 000) $H$- and $K$-band spectroscopic atlas of the L7.5 and T0.5 components of the Luhman 16AB binary (WISE J104915.57$-$531906.1AB): the closest pair of brown dwarfs, and one of the best substellar benchmarks. The spectra were combined from a 70-d spectroscopic monitoring campaign of the binary with IGRINS on Gemini South. We fit model photospheres to the combined high-quality spectra to estimate atmospheric parameters. The model is based on the Sonora model atmosphere further incorporating the effects of clouds and disequilibrium. We detect ammonia (NH3) lines in both binary components, making Luhman 16A the warmest object where individual NH3 lines were identified. We discover hydrogen (H2), hydrogen sulfide (H2S), and hydrogen fluoride (HF) lines in both components, following recent reports of these species in either cooler (H2, H2S in a T6 dwarf) or warmer (HF in young late-M or mid-L dwarfs) objects. Methane (CH4) shows a small contribution, with lines sensitive to the slight temperature difference spanning the L/T transition. Against model expectations, we do not detect FeH lines, implying more efficient iron rainout than incorporated in the models. We find various unidentified features in water-dominated regions, likely the result of residual inaccuracies in the water line lists. We searched for planetary-mass companions by periodogram analysis of radial velocities over 70 d but detected no significant signal. The upper limits of projected planetary mass are $M\sin {i}=$ 0.2 $M_{\mathrm{J}}$ and 0.3 $M_{\mathrm{J}}$ at P $\sim$ 1 d, and 0.4 $M_{\mathrm{J}}$ and 0.7 $M_{\mathrm{J}}$ at P $\sim$ 10 d for Luhman 16A and B, respectively.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".