Spatial distribution of the aromatic and aliphatic carbonaceous nanograin features in the protoplanetary disk around HD 100546
Bibliographic record
Abstract
Context. Carbonaceous nanograins are present at the surface of protoplanetary disks around Herbig Ae/Be stars, where most of the ultraviolet energy from the central star is dissipated. Efficiently coupled to the gas, they are unavoidable to understand the physics and chemistry of these disks. Furthermore, nanograins are able to trace the outer flaring parts of the disk and possibly the gaps from which the larger grains are missing. However, their evolution through the disks, from internal to external regions, is only poorly understood so far. Aims. Our aim is to examine the spatial distribution and evolution of the nanodust emission in the emblematic (pre-)transitional protoplanetary disk HD 100546. This disk shows many structures (annular gaps, rings, and spirals) and reveals very rich carbon nanodust spectroscopic signatures (aromatic, aliphatic) in a wide spatial range of the disk (~20−200 au). Methods. We analysed adaptive optics spectroscopic observations in the 3–4 μm range (angular resolution of ~0.1′′) and imaging and spectroscopic observations in the 8–12 μm range (angular resolution of ~0.3′′). The hyperspectral cube was decomposed into a sum of spatially coherent dust components using a Gaussian decomposition algorithm. We compared the data to model predictions using the heterogeneous dust evolution model for interstellar solids (THEMIS), which is integrated in the radiative transfer code POLARIS by calculating the thermal and stochastic heating of micro- and nanometre-sized dust grains for a given disk structure. Results. We find that the aromatic features at 3.3, 8.6, and 11.3 μm, and the aliphatic features between 3.4 and 3.5 μm are spatially extended; each band shows a specific morphology dependent on the local physical conditions. The aliphatic-to-aromatic band ratio, 3.4/3.3, increases with the distance from the star from ~0.2 (at 0.2′′ or 20 au) to ~0.45 (at 1′′ or 100 au), suggesting UV processing. In the 8–12 μm observed spectra, several features characteristic of aromatic particles and crystalline silicates are detected. Their relative contribution changes with the distance to the star. The model predicts that the features and adjacent continuum are due to different combinations of grain sub-populations, in most cases with a high dependence on the intensity of the UV field. The model reproduces the spatial emission profiles of the bands well, except for the inner 20-40 au, where the observed emission of the 3.3 and 3.4 μm bands is, unlike the predictions, flat and no longer increases with the UV field. Conclusions. With our approach that combines observational data in the near- to mid-IR and disk modelling, we deliver constraints on the spatial distribution of nano-dust particles as a function of the disk structure and radiation field.
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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 | 0.000 |
| 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 | 0.000 |
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".