From Dust to Nanodust: Resolving Circumstellar Dust from the Colliding-wind Binary Wolf-Rayet 140
Bibliographic record
Abstract
Abstract Wolf-Rayet (WR) 140 is the archetypal periodic dust-forming colliding-wind binary that hosts a carbon-rich WR (WC) star and an O-star companion with an orbital period of 7.93 yr and an orbital eccentricity of 0.9. Throughout the past few decades, multiple dust-formation episodes from WR 140 have been observed that are linked to the binary orbit and occur near the time of periastron passage. Given its predictable dust-formation episodes, WR 140 presents an ideal astrophysical laboratory to investigate the formation and evolution of dust in the hostile environment around a massive binary system. In this paper, we present near- and mid-infrared (IR) spectroscopic and imaging observations of WR 140 with Subaru/SCExAO+CHARIS, Keck/NIRC2+PyWFS, and Subaru/Cooled Mid-Infrared Camera and Spectrograph taken between 2020 June and September that resolve the circumstellar dust emission linked to its most recent dust-formation episode in 2016 December. Our spectral energy distribution analysis of WR 140's resolved circumstellar dust emission reveals the presence of a hot (T d ∼ 1000 K) near-IR dust component that is co-spatial with the previously known and cooler (T d ∼ 500 K) mid-IR dust component composed of 300–500 Å sized dust grains. We attribute the hot near-IR dust emission to the presence of nano-sized (nanodust) grains and suggest they were formed from grain–grain collisions or the rotational disruption of the larger grain size population by radiative torques in the strong radiation field from the central binary. Lastly, we speculate on the astrophysical implications of nanodust formation around colliding-wind WC binaries, which may present an early source of carbonaceous nanodust in the interstellar medium.
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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".