Warm dusty discs: Exploring the A star 24um debris population
Bibliographic record
Abstract
(Abridged) Studies of debris discs have shown that most systems are analogous to the EKB. In this study we aim to determine how many IRAS 25um excesses towards A stars are real, and investigate where the dust lies. We observe with TIMMI2, VISIR, Michelle and TReCS a sample of A and B-type main sequence stars reported as having mid-IR excess. We constrain the location of the debris through combined modelling of the emission spectrum and a modelling technique designed to constrain the radial extent of emission in mid-IR imaging. We independently confirm the presence of warm dust around 3 of the candidates: HD3003, HD80950 and eta Tel. For the binary HD3003 a stability analysis indicates the dust is either circumstellar and lying at ~4 AU with the binary orbiting at >14AU, or the dust lies in an unstable location; there is some evidence for temporal evolution of its excess emission on a ~20 year timescale. For 7 of the targets we present quantitative limits on the location of dust around the star. We demonstrate that the disc around HD71155 must have spatially distinct components at 2 and 60AU. We model the limits of current instrumentation and show that most of the known A star debris discs which could be readily resolved at 18um on 8m instruments have been resolved. Limits from unresolved imaging can help distinguish between competing models of the disc emission, but resolved imaging is key to the determination of the disc location. Modelling of the detection limits for extended emission can be useful for targeting future observational campaigns. MIRI on the JWST will be able to resolve most of the known A star debris disc population. METIS on the E-ELT will provide the opportunity to explore the hot disc population more thoroughly by detecting extended emission where calibration accuracy limits disc detection through photometry, reaching levels below 1 zodi for stars at <10pc.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".