PDRs4All
Bibliographic record
Abstract
Context. Interstellar dust particles, in particular carbonaceous nano-grains (like polycyclic aromatic hydrocarbons, fullerenes, and amorphous hydrogenated carbon), are critical players for the composition, energy budget, and dynamics of the interstellar medium (ISM). The dust properties, specifically the composition and size of dust grains are not static; instead, they exhibit considerable evolution triggered by variations in local physical conditions such as the density and gas temperature within the ISM, as is the case in photon-dominated regions (PDRs). The evolution of dust and its impact on the local physical and chemical conditions is thus a key question for understanding the first stages of star formation. Aims. From the extensive spectral and imaging data of the JWST PDRs4All program, we study the emission of dust grains within the Orion Bar – a well-known, highly far-UV (FUV)-irradiated PDR situated at the intersection between cold, dense molecular clouds, and warm ionized regions. The Orion Bar because of its edge-on geometry provides an exceptional benchmark for characterizing dust evolution and the associated driving processes under varying physical conditions. Our goal is to constrain the local properties of dust by comparing its emission to models. Taking advantage of the recent JWST data, in particular the spectroscopy of dust emission, we identify new constraints on dust and further previous works of dust modelling. Methods. To characterize interstellar dust across the Orion Bar, we follow its emission as traced by JWST NIRCam (at 3.35 and 4.8 μm) and MIRI (at 7.7, 11.3, 15.0, and 25.5 μm) broad band images, along with NIRSpec and MRS spectroscopic observations. First, we constrain the minimum size and hydrogen content of carbon nano-grains from a comparison between the observed dust emission spectra and the predictions of the Heterogeneous dust Evolution Model for Interstellar Solids (THEMIS) coupled to the numerical code DustEM. Using this dust model, we then perform 3D radiative transfer simulations of dust emission with the SOC code (Scattering with OpenCL) and compare to data obtained along well chosen profiles across the Orion Bar. Results. The JWST data allows us, for the first time, to spatially resolve the steep variation of dust emission at the illuminated edge of the Orion Bar PDR. By considering a dust model with carbonaceous nano-grains and submicronic coated silicate grains, we derive unprecedented constraints on the properties of across the Orion Bar. To explain the observed emission profiles with our simulations, we find that the nano-grains must be strongly depleted with an abundance (relative to the gas) 15 times less than in the diffuse ISM. The NIRSpec and MRS spectroscopic observations reveal variations in the hydrogenation of the carbon nano-grains. The lowest hydrogenation levels are found in the vicinity of the illuminating stars suggesting photo-processing while more hydrogenated nano-grains are found in the cold and dense molecular region, potentially indicative of larger grains.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.065 | 0.035 |
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".